U.S. patent application number 13/271568 was filed with the patent office on 2012-11-15 for search engine optimization for social marketplace.
Invention is credited to Aron England, Manish C. Mehta, Ronald Vincent Rose, Steven Tedjamulia.
Application Number | 20120290553 13/271568 |
Document ID | / |
Family ID | 47142508 |
Filed Date | 2012-11-15 |
United States Patent
Application |
20120290553 |
Kind Code |
A1 |
England; Aron ; et
al. |
November 15, 2012 |
Search Engine Optimization for Social Marketplace
Abstract
A method and system are disclosed for optimizing search engine
operations to increase the likelihood of attaining financial goals
in a syndicated commerce environment. An SEO algorithm is
implemented to determine keyword options for a predetermined
product based upon the product's description, its web page content,
and other related information. The SEO algorithm is then used to
determine the product's associated search traffic and
rank-per-keyword from various search engines. This information, in
addition to sales conversion rate information, is then used to
estimate the likelihood of monetization for one or more keyword.
The product web page content is then automatically revised with an
optimized combination of keywords. Once optimized, various search
engines are automatically notified of the revisions to the web
content pages to improve organic search rankings.
Inventors: |
England; Aron; (Austin,
TX) ; Tedjamulia; Steven; (Austin, TX) ;
Mehta; Manish C.; (Austin, TX) ; Rose; Ronald
Vincent; (Austin, TX) |
Family ID: |
47142508 |
Appl. No.: |
13/271568 |
Filed: |
October 12, 2011 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61485767 |
May 13, 2011 |
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Current U.S.
Class: |
707/706 ;
707/E17.017 |
Current CPC
Class: |
G06Q 50/01 20130101;
G06Q 30/0282 20130101; G06Q 30/0631 20130101 |
Class at
Publication: |
707/706 ;
707/E17.017 |
International
Class: |
G06F 17/30 20060101
G06F017/30 |
Claims
1. A computer-implementable method for optimizing search engine
operations, comprising: processing a first set of product data to
generate a set of candidate keywords, the first set of product data
corresponding to a product; submitting the set of candidate
keywords to a search engine; receiving a set of candidate keyword
performance values corresponding to the set of candidate keywords,
the set of candidate keyword performance values provided by the
search engine; and processing the set of candidate keyword
performance values, search traffic data corresponding to the
product data, and sales conversion data corresponding to the
product to generate a monetization value for the set of candidate
keywords.
2. The computer-implementable method of claim 1, wherein the first
set of product data comprises at least one of the set of: product
title data; product description data; product promotion data;
product pricing data; associated content data; and backlink
data.
3. The computer-implementable method of claim 1, wherein: a set of
alternative keywords and a set of alternative keyword performance
values is received from the search engine, the set of alternative
keywords corresponding to the set of candidate keywords and the set
of alternative keyword performance values corresponding to the set
of alternative keywords; the set of candidate keyword performance
values and the set of alternative keyword performance values is
processed to generate a set of optimized keywords; the first set of
product data and the set of optimized keywords is processed to
generate a second set of product data.
4. The computer-implementable method of claim 3, wherein the second
set of product data comprises at least one of the set of: a keyword
meta tag; a title tag; H1 Hypertext Markup Language (HTML) heading
text; an alt tag; a site map; a sitemap.xml file; and a robots.txt
file.
5. The computer-implementable method of claim 3, wherein the search
engine is notified of the generation of the second set of product
data.
6. The computer-implementable method of claim 1, wherein the sales
conversion data comprises historical purchase data associated with
the keywords.
7. A system comprising: a processor; a data bus coupled to the
processor; and a computer-usable medium embodying computer program
code, the computer-usable medium being coupled to the data bus, the
computer program code interacting with a plurality of computer
operations and comprising instructions executable by the processor
and configured for: processing a first set of product data to
generate a set of candidate keywords, the first set of product data
corresponding to a product; submitting the set of candidate
keywords to a search engine; receiving a set of candidate keyword
performance values corresponding to the set of candidate keywords,
the set of candidate keyword performance values provided by the
search engine; and processing the set of candidate keyword
performance values, search traffic data corresponding to the
product data, and sales conversion data corresponding to the
product to generate a monetization value for the set of candidate
keywords.
8. The system of claim 7, wherein the first set of product data
comprises at least one of the set of: product title data; product
description data; product promotion data; product pricing data;
associated content data; and backlink data.
9. The system of claim 7, wherein: a set of alternative keywords
and a set of alternative keyword performance values is received
from the search engine, the set of alternative keywords
corresponding to the set of candidate keywords and the set of
alternative keyword performance values corresponding to the set of
alternative keywords; the set of candidate keyword performance
values and the set of alternative keyword performance values is
processed to generate a set of optimized keywords; the first set of
product data and the set of optimized keywords is processed to
generate a second set of product data.
10. The system of claim 9, wherein the second set of product data
comprises at least one of the set of: a keyword meta tag; a title
tag; H1 Hypertext Markup Language (HTML) heading text; an alt tag;
a site map; a sitemap.xml file; and a robots.txt file.
11. The system of claim 9, wherein the search engine is notified of
the generation of the second set of product data.
12. The system of claim 7, wherein the sales conversion data
comprises historical purchase data associated with the
keywords.
13. A computer-usable medium embodying computer program code, the
computer program code comprising computer executable instructions
configured for: processing a first set of product data to generate
a set of candidate keywords, the first set of product data
corresponding to a product; submitting the set of candidate
keywords to a search engine; receiving a set of candidate keyword
performance values corresponding to the set of candidate keywords,
the set of candidate keyword performance values provided by the
search engine; and processing the set of candidate keyword
performance values, search traffic data corresponding to the
product data, and sales conversion data corresponding to the
product to generate a monetization value for the set of candidate
keywords.
14. The computer usable medium of claim 13, wherein the first set
of product data comprises at least one of the set of: product title
data; product description data; product promotion data; product
pricing data; associated content data; and backlink data.
15. The computer usable medium of claim 14, wherein: a set of
alternative keywords and a set of alternative keyword performance
values is received from the search engine, the set of alternative
keywords corresponding to the set of candidate keywords and the set
of alternative keyword performance values corresponding to the set
of alternative keywords; the set of candidate keyword performance
values and the set of alternative keyword performance values is
processed to generate a set of optimized keywords; the first set of
product data and the set of optimized keywords is processed to
generate a second set of product data.
16. The computer usable medium of claim 15, wherein the second set
of product data comprises at least one of the set of: a keyword
meta tag; a title tag; H1 Hypertext Markup Language (HTML) heading
text; an alt tag; a site map; a sitemap.xml file; and a robots.txt
file.
17. The computer usable medium of claim 15, wherein the search
engine is notified of the generation of the second set of product
data.
18. The computer usable medium of claim 13, wherein the sales
conversion data comprises historical purchase data associated with
the keywords.
19. The computer usable medium of claim 13, wherein the computer
executable instructions are deployable to a client computer from a
server at a remote location.
20. The computer usable medium of claim 13, wherein the computer
executable instructions are provided by a service provider to a
customer on an on-demand basis.
Description
CROSS-REFERENCE TO RELATED APPLICATION
[0001] This application claims the benefit under 35 U.S.C.
.sctn.119(e) of U.S. Provisional Application No. 61/485,767, filed
May 13, 2011, entitled "Social Marketplace." U.S. Provisional
Application No. 61/485,767 includes exemplary systems and methods
and is incorporated by reference in its entirety.
BACKGROUND OF THE INVENTION
[0002] 1. Field of the Invention
[0003] Embodiments of the invention relate generally to information
handling systems. More specifically, embodiments of the invention
provide a method and system for optimizing search engine operations
to increase the likelihood of attaining financial goals in a
syndicated commerce environment.
[0004] 2. Description of the Related Art
[0005] As the value and use of information continues to increase,
individuals and businesses seek additional ways to process and
store information. One option available to users is information
handling systems. An information handling system generally
processes, compiles, stores, and/or communicates information or
data for business, personal, or other purposes thereby allowing
users to take advantage of the value of the information. Because
technology and information handling needs and requirements vary
between different users or applications, information handling
systems may also vary regarding what information is handled, how
the information is handled, how much information is processed,
stored, or communicated, and how quickly and efficiently the
information may be processed, stored, or communicated. The
variations in information handling systems allow for information
handling systems to be general or configured for a specific user or
specific use such as financial transaction processing, airline
reservations, enterprise data storage, or global communications. In
addition, information handling systems may include a variety of
hardware and software components that may be configured to process,
store, and communicate information and may include one or more
computer systems, data storage systems, and networking systems.
[0006] These same information handling systems have played a key
role in the rapid growth of electronic commerce on the Internet.
One known aspect of electronic commerce is affiliate networks,
which allow online merchants to reach a larger audience through
participation in various affiliate programs. Typically, potential
customers are referred to the merchant's website from an
affiliate's web site, which receives a share of any resulting sale
as compensation for the referral. Various affiliate network
services and benefits generally include referral tracking,
reporting tools, payment processing, and access to a large base of
participants. Over time, affiliate networks have made progress in
simplifying the process of registering affiliate participants fore
or more merchant affiliate programs. However, affiliates still face
integration challenges when attempting to provide their users a
customized subset of the merchant's website.
[0007] In recent years, information handling systems have also been
instrumental in the widespread adoption of social media into the
mainstream of everyday life. Social media commonly refers to the
use of web-based technologies for the creation and exchange of
user-generated content for social interaction. As such, it
currently accounts for approximately 22% of all time spent on the
Internet. More recently, various aspects of social media have
become an increasingly popular for enabling customer feedback, and
by extension, have likewise evolved into a viable marketing channel
for vendors. This new marketing channel, sometimes referred to as
"social marketing," has proven to not only have a higher customer
retention rate than traditional marketing channels, but to also
provide higher demand generation "lift."
[0008] Another aspect of social marketing that is gaining
popularity is syndicated commerce, where a scaled-down version of a
merchant's online storefront is embedded in an affiliate's web page
or social media site. Such syndicated commerce sites provide the
opportunity to increase sales, a portion of which is typically
provided to the affiliate. However, these embedded storefronts
often fail to attain their financial goals due to insufficient
traffic and low sales conversion rates. It is not uncommon for such
failure to be attributed to either a lack, misapplication, or
misunderstanding of various search engine optimization (SEO)
approaches. As an example, one or more keywords used in an SEO
approach may not prove effective in driving traffic due to low
search engine ranking. As another example, the keywords may be
associated with content generated by a social network user whose
social graph is insufficient to drive significant traffic.
Conversely, the keywords may be selected from non-authoritative
sites, resulting in low conversion rates from sufficient, yet
inappropriate traffic.
SUMMARY OF THE INVENTION
[0009] A method and system are disclosed for optimizing search
engine operations to increase the likelihood of attaining financial
goals in a syndicated commerce environment. In various embodiments,
a SEO algorithm is implemented in a syndicated commerce environment
to predict the amount of financial compensation an individual or
social commerce marketplace entity can receive from the sale of a
predetermined product. In certain embodiments, the SEO algorithm is
further implemented to optimize their associated web pages to
increase site traffic, and as a result, the likelihood of reaching
their financial goals.
[0010] In these and other embodiments, the SEO algorithm determines
keyword options for a predetermined product based upon the
product's description, its web page content, and other related
information. The social commerce marketplace system then uses the
SEO algorithm to determine the product's associated search traffic
and rank-per-keyword from various search engines. This information,
in addition to sales conversion rate information, is used to
estimate the likelihood of monetization for a single keyword or a
group of keywords. In certain embodiments, the SEO algorithm
refines its estimates by tracking and analyzing historical purchase
records for a given path and visitor segment. The system then
automatically modifies the website pages with optimal combinations
of keywords. Once optimized, various search engines are
automatically notified of the changes to the web pages to improve
organic search rankings.
[0011] In various embodiments, the SEO algorithm is implemented to
determine the likelihood of a relationship or visitor associated
with the user's social graph to purchase a predetermined product.
Once the likelihood is determined, the social commerce marketplace
system creates tasks for the user, monitors the progress of their
completion, and makes ongoing recommendations to assist the user in
reaching their revenue goals. In one embodiment, a crawler
sub-module is implemented with the SEO algorithm to crawl a
predetermined domain or website to analyze the market opportunity
or financial value of the site. In this embodiment, the output of
the analysis is a list of recommendations and tasks to complete to
capitalize on each opportunity.
BRIEF DESCRIPTION OF THE DRAWINGS
[0012] The present invention may be better understood, and its
numerous objects, features and advantages made apparent to those
skilled in the art by referencing the accompanying drawings. The
use of the same reference number throughout the several figures
designates a like or similar element.
[0013] FIG. 1 is a generalized illustration of the components of an
information handling system as implemented in the system and method
of the present invention;
[0014] FIG. 2 is a simplified block diagram showing the
implementation of a social commerce marketing system;
[0015] FIG. 3 is a simplified block diagram showing a high-level
architecture of a social commerce marketplace system;
[0016] FIGS. 4a-b are a simplified block diagram showing a
plurality of social commerce modules implemented within a plurality
of host environments;
[0017] FIG. 5 is a generalized flow chart of social commerce
initiation operations performed on behalf of an affiliate;
[0018] FIGS. 6a-d are generalized depictions of social commerce
initiation operations performed on behalf of an affiliate within a
plurality of user interface windows;
[0019] FIG. 7 is a generalized flow chart of the performance of
social commerce operations;
[0020] FIG. 8 is a generalized flow chart of the performance of
social commerce advertising network management operations;
[0021] FIGS. 9a-b show the creation of an affiliate offer within a
user interface window;
[0022] FIG. 10 shows the display of affiliate offers within a user
interface window;
[0023] FIG. 11 shows the display of affiliate network feeds and
associated offers within a user interface window;
[0024] FIG. 12 is a generalized flow chart of the performance of
content syndication operations;
[0025] FIG. 13 is a generalized flow chart of the performance of
billboard management operations;
[0026] FIG. 14 is a generalized flow chart of the performance of
product categorization operations;
[0027] FIG. 15 is a generalized flow chart of the performance of
product moderation operations;
[0028] FIGS. 16a-b are a generalized flow chart of the performance
of search engine optimization (SEO) goal attainment operations;
[0029] FIG. 17 shows a ranked list of keywords within a user
interface window that are predicted to result in the highest amount
of traffic and corresponding conversion rates;
[0030] FIG. 18 shows estimated traffic and SEO elements within a
user interface window that are anticipated to affect an online
store's ability to reach its financial goals;
[0031] FIG. 19 is a generalized flow chart of the performance of
keyword submission optimization operations;
[0032] FIG. 20 shows information that is proactively submitted to a
commercial search engine and its associated SEO effect within a
user interface window; and
[0033] FIGS. 21a-b are a generalized flow chart of the performance
of product and store performance optimization operations.
DETAILED DESCRIPTION
[0034] A method and system are disclosed for optimizing search
engine operations to increase the likelihood of attaining financial
goals in a syndicated commerce environment. For purposes of this
disclosure, an information handling system may include any
instrumentality or aggregate of instrumentalities operable to
compute, classify, process, transmit, receive, retrieve, originate,
switch, store, display, manifest, detect, record, reproduce,
handle, or utilize any form of information, intelligence, or data
for business, scientific, control, or other purposes. For example,
an information handling system may be a personal computer, a
network storage device, or any other suitable device and may vary
in size, shape, performance, functionality, and price. The
information handling system may include random access memory (RAM),
one or more processing resources such as a central processing unit
(CPU) or hardware or software control logic, ROM, and/or other
types of nonvolatile memory. Additional components of the
information handling system may include one or more disk drives,
one or more network ports for communicating with external devices
as well as various input and output (I/O) devices, such as a
keyboard, a mouse, and a video display. The information handling
system may also include one or more buses operable to transmit
communications between the various hardware components.
[0035] FIG. 1 is a generalized illustration of an information
handling system 100 that can be used to implement the system and
method of the present invention. The information handling system
100 includes a processor (e.g., central processor unit or "CPU")
102, input/output (I/O) devices 104, such as a display, a keyboard,
a mouse, and associated controllers, a hard drive or disk storage
106, and various other subsystems 108. In various embodiments, the
information handling system 100 also includes network port 110
operable to connect to a network 140, which is likewise accessible
by a service provider server 142. The information handling system
100 likewise includes system memory 112, which is interconnected to
the foregoing via one or more buses 114. System memory 112 further
comprises operating system (OS) 116 and in various embodiments may
also comprise a social commerce marketplace system 118, a plurality
of social commerce affiliate management modules 120, a plurality of
merchant/network management modules 122, and a merchant online
cart/checkout system 124. In one embodiment, the information
handling system 100 is able to download the social commerce
marketplace system 118, the plurality of social commerce affiliate
management modules 120, the plurality of merchant/network
management modules 122, and the merchant online cart/checkout
system 124 from the service provider server 142. In another
embodiment, the social commerce marketplace system 118, the
plurality of social commerce affiliate management modules 120, the
plurality of merchant/network management modules 122, and the
merchant online cart/checkout system 124 is provided as a service
from the service provider server 142.
[0036] FIG. 2 is a simplified block diagram showing the
implementation of a social commerce marketing system in accordance
with an embodiment of the invention. In this embodiment, a social
commerce marketplace system 118 is implemented with a plurality of
social commerce affiliate management modules 120, a plurality of
merchant/network management modules 122, a merchant online
cart/checkout system 124. In these and other embodiments, the
plurality of social commerce affiliate management modules 120 are
accessed and used by a plurality of affiliates 214. Likewise, the
plurality of social commerce affiliate management modules 120
comprises a blog/site management module 218, a social network
management module 222, and a mobile delivery management module 222.
The plurality of social commerce affiliate management modules 120
likewise comprises a hosting management module 224, a social
commerce management module 226, and a marketing management module
228.
[0037] In one embodiment, the blog/site management module 214 is
used by the plurality of affiliates 214 to manage the posting and
linking of social commerce content from the affiliate's online blog
or website to the social commerce marketplace system 118. In
another embodiment, the social network management module 220 is
used by the plurality of affiliates 214 to manage the linkages
between one or more social media environments and the social
commerce marketplace system 118. In yet another embodiment, the
mobile delivery management module 222 is used by the plurality of
affiliates 214 to manage the delivery of social commerce content to
a mobile device. In still another embodiment, the hosting
management module 224 is used by the plurality of affiliates 214 to
manage the hosting environment(s) of a customized social commerce
storefront associated with the affiliate and the merchant. In one
embodiment, the social commerce management module 226 is used by
the plurality of affiliates 214 to perform social commerce
management operations as described in greater detail herein. In yet
another embodiment, the marketing management module 228 is used by
the plurality of affiliates 214 to perform social commerce
marketing operations, as likewise described in greater detail
herein.
[0038] In various embodiments, the plurality of merchant/network
management modules 122 are accessed and used by a plurality of
merchant administrators 230. In these and other embodiments, the
plurality of merchant/network management modules 122 comprises a
merchant/network management module 234, and a social commerce
moderation module 236. Likewise, the plurality of merchant/network
management modules 122 comprises a social commerce reporting module
238, a targeting module 240, and an incentives module 242.
[0039] In one embodiment, the merchant/network management module is
used by is used by the plurality of merchant administrators 230 to
manage a plurality of affiliate social commerce storefronts and a
plurality of affiliate networks 204. In another embodiment, the
moderation management module 236 is used by the plurality of
merchant administrators 230 to monitor and moderate social commerce
content and associated social media content related to the
plurality of affiliates 214. In yet another embodiment, the social
commerce reporting module 238 is used by the plurality of merchant
administrators 230 to administer and deliver a plurality of social
commerce reports as described in greater detail herein. In one
embodiment, the targeting module 240 is used by the plurality of
merchant administrators 230 to perform targeted advertising and
promotion operations familiar to those of skill in the art and
described in greater detail herein. In another embodiment, the
incentives module 242 is used by the plurality of merchant
administrators 230 to manage the accounting and payment of
incentives to the plurality of affiliates 214 as compensation for
referring customers to the merchant. As described in greater detail
herein, the plurality of social commerce affiliate management
modules 120 and the plurality of merchant/network management
modules 122 may include additional modules and the foregoing is not
intended to limit the spirit, scope or intent of the invention.
[0040] Referring now to FIG. 2, a plurality of users, such as
customers 202, are referred by a plurality of affiliate networks
204 to the social commerce marketplace system 118 as described in
greater detail. Once referred, the customers 202 are presented with
a customized social commerce storefront that is associated with an
individual affiliate of the plurality of affiliates 214 and the
merchant. In various embodiments, each of the customized social
commerce storefronts comprises a micro catalog 208 of purchasable
products, which is a subset of a master catalog 210 comprising a
set of available products. In these and other embodiments, and as
likewise described in greater detail herein, the customized social
commerce storefronts comprise social commerce content related to
the purchasable products. In these various embodiments, the
customers 202 review the social commerce content and select
individual purchasable products for purchase. Once selected, an
online purchase transaction familiar to skilled practitioners of
the art is completed with the merchant online cart/checkout system
124.
[0041] FIG. 3 is a simplified block diagram showing a high-level
architecture of a social commerce marketplace system as implemented
in accordance with an embodiment of the invention. In this
embodiment, the architecture a social commerce marketplace system
118 comprises infrastructure 302, data 304, application 306 and
presentation 308 layers. As shown in FIG. 3, the infrastructure 302
layer comprises feeds from affiliate networks 316, as described in
greater detail herein, and other networks 318, such as advertising
networks known to those of skill in the art. The infrastructure 302
layer likewise comprises a local application fabric 314, as
likewise known to those of skill in the art, a plurality of
application programming interfaces (APIs) 312, and a plurality of
databases 310, as described in greater detail herein. The data 304
layer likewise comprises repository classes 320, which are used for
the exchange of data between the data 304 and infrastructure 302
layers.
[0042] Likewise, the application 306 layer comprises host
environments 322, which in turn comprise a tenancy management
module 324, a product catalog management module 326, and a product
search module 328. The host environments 322 likewise comprise a
stores management module 330, a commission management module 332,
and a caching module 334. Likewise, the host environments 322
comprise an auditing module 336, a notifications module 338, a
search engine optimization (SEO) module 340, a security management
module 342, a moderation management module 344, and other modules
346 as described in greater detail herein.
[0043] In one embodiment, the tenancy management module 324 is used
by merchant administrators to manage a plurality of affiliate
tenancies in a virtual environment. In another embodiment, the
product catalog management module 326 is used to manage available
products in a master catalog and purchasable products, which are
subsets of the available products, in micro catalogs as described
in greater detail herein. In yet another embodiment, the product
search module 328 is used with various other modules in the
initiation, provisioning, and management of affiliate storefronts.
In still another embodiment, the commission management module 332
is used to track, account, and pay commissions to affiliates as
compensation for referring customers to the merchant. In one
embodiment, the caching module 334 is used to cache social commerce
content and other data related to conducting social commerce
operations.
[0044] In another embodiment, the auditing module 336 is used to
audit social commerce transactions that are performed within the
social commerce marketplace system. In yet another embodiment, the
notifications module 338 is use to manage notifications to
affiliates as well as users referred by the affiliates to the
social commerce marketplace system. In still another embodiment,
the SEO module 340 is used to perform SEO operations known to
skilled practitioners of the art. In this embodiment, the SEO
operations, as described in greater detail herein, are performed to
optimize the identification of a purchasable product according to
the search terms used by either an affiliate or a user of a social
media environment. In one embodiment, the security module is used
to maintain the security of the social commerce marketplace system.
In another embodiment, the moderation module 344 is used to monitor
and moderate social commerce content and associated social media
content related to a plurality of affiliates. In yet another
embodiment, the other modules 346 comprise additional modules, as
described in greater detail herein, that operate within the host
environments 322.
[0045] In various embodiments, the presentation 308 layer comprises
a Representational State Transfer (REST) application program
interface (API) 348 known to skilled practitioners of the art. In
these and other embodiments, the presentation 308 layer likewise
comprises a controller module 350 a presentation model 352, a
presentation view 354, and a plurality of administration 356 and
affiliate storefront 358 sites. In these various embodiments, the
controller module 350 interacts with the presentation model 354 and
presentation view 354, which likewise interact with each other, to
present different aspects of the plurality of administration 356
and affiliate storefront 358 sites. Likewise, the presentation view
354 module provides feedback to the controller module 350.
[0046] Referring now to FIG. 3, the presentation 308 layer
comprises manager classes 350 and the application 306 layer
comprises domain services. The manager classes 360 provide
presentation layer data to the service contracts module 362, which
is then used for the management of the domain service 364. In turn,
the domain services 364 provide application layer data to the
repository contracts module 366, where it is used for the
management of the repository classes 320. Likewise, the service
contracts module 362 and the repository contracts module 366 are
managed and bounded by a dependencies module 368. In turn, the
dependencies module 368 is managed with the logging 370, caching
372, and auditing 374 management modules.
[0047] FIGS. 4a-b show a simplified block diagram of a plurality of
social commerce modules implemented within a plurality of host
environments in accordance with an embodiment of the invention. In
this embodiment, the host environments 322 comprise social media
store 401, affiliate storefront 402, blog 403, templates 404,
content 406, notifications 410, uniform resource locator (URL) 411,
reputation 412, and search engine optimization (SEO) 417 management
modules. Likewise, the host environments 322 comprise catalog 426,
links 435, web analytics 438, fraud 442, payment 448,
administration 454, reports 463, and widget 470 management
modules.
[0048] In one embodiment, the social media store 401 management
module is used to manage a social commerce storefront that is
associated with an affiliate's presence and activities within a
social media environment. In another embodiment, the affiliate
storefront 402 management module is used to manage a social
commerce storefront that is associated with an affiliate's web site
or online blog. In yet another embodiment, the blog 403 management
module is used to manage an affiliates blog activities as it
relates to social commerce activities, processes and operations as
described in greater detail herein. In still another embodiment, as
likewise described in greater detail herein, the templates 404
management module is used for the automated configuration of social
commerce storefront pages. In one embodiment, the notifications 410
management module is used for the management of notifications to
affiliates and users associated with affiliates, such as users of
an affiliate's online social commerce presence. In various
embodiments, the affiliate's online presence may comprise a blog, a
website, or a community of interest or conversation thread in a
social media environment. In another embodiment, the URL 411
management module is used to manage URL links between the host
environments 322 and the affiliate's various online social commerce
presences.
[0049] In yet another embodiment, the content 405 management module
further comprises articles 406, podcast 407, pictures 408, and
video 409 management sub-modules. In this and other embodiments,
the articles 406, podcast 407, pictures 408, and video 409
management sub-modules are used by affiliates to manage their
respective, associated content as it relates to social commerce
operations. In still another embodiment, the reputation 412
management module comprises points 413, badges 414, activity 415,
and score 416 management sub-modules. In this and other
embodiments, the reputation 412 management module comprises points
413, badges 414, activity 415, and score 416 management sub-modules
are used by the merchant to manage reputation data associated with
affiliates. As used herein, reputation data refers to data
associated with social commerce activities performed by an
affiliate. As an example, an affiliate may receive points from a
merchant for each item of social commerce content they product.
Likewise, badges may be awarded upon achievement of various point
tiers or frequency of activity. Likewise, each social commerce
content item may receive a score that is associated with the
achievement of the points and badges. It will be appreciated that
many such examples are possible and the foregoing is not intended
to limit the spirit, scope, or intent of the invention.
[0050] In one embodiment, the SEO management 417 module comprises
backlinks 418, rank 419, competition 420, search application
program interface (API) 421, keyword density 422, keyword placement
423, keyword insertion 424, and content comparison 425 management
sub-modules. In this and other embodiments the various sub-modules
of the SEO management 417 module are used by affiliates and the
merchants to perform SEO operations familiar to those of skill in
the art. As an example, the backlinks 418 management sub-module may
be used to determine prior web site locations that a user has
visited prior to being referred to an affiliate's social commerce
storefront. Likewise, the rank 419 management sub-module may be
used to determine the search engine rank assigned to the
affiliate's social commerce storefront as well as the individual
search engine ranking of the search terms that resulted in the
referral. As another example, the competition 420 management
sub-module may be used by the merchant to rank the search engine
popularity of their competitors, or alternatively, the frequency
that a competitor's web site is returned as a result of a search by
a user of a social media environment. Likewise, the search API 421
management sub-module may be used by the merchant and affiliates
alike to gain access to various search engines in order to receive
search metadata. As yet another example, the keyword density 422,
placement 423, and insertion 424 management sub-modules may
likewise be used by the merchant and the affiliates to optimize
searches through the use of predetermined keywords within related
social commerce content. As still another example, the content
comparison 425 sub-module may be used to compare various items of
social commerce content to determine which items perform better
than others during SEO operations.
[0051] In another embodiment, the catalog 426 management module
comprises filter 427, search 428, price 429, taxonomy 430, import
431, differential 432, categories 433, and deals 434 management
sub-modules. In this and other embodiments, the filter 427, search
428, price 429, taxonomy 430, import 431, differential 432,
categories 433, and deals 434 management sub-modules are used by
the affiliate for managing their social commerce storefronts. For
example, the filter 427, search 428, price 429, differential 432,
deals 434, and import 431 management sub-modules may be used
individually, or in combination, to identify and populate a set of
purchasable products within a micro catalog from a set of available
products contained in a master catalog. Likewise, the taxonomy 430
and categories 433 management sub-modules may be used to understand
the interrelationship of various purchasable products and how they
are categorized within the affiliate's social commerce storefront.
It will be appreciated that many such examples are possible and the
foregoing is not intended to limit the spirit, scope, or intent of
the invention.
[0052] In yet another embodiment, the links 435 management module
comprises network 436 and system 437 management sub-modules, which
are used to manage the linkages between the various systems,
modules, and sub-modules of the social commerce marketplace system
and various affiliate and advertising networks. In still another
embodiment, the web analytics 438 module comprises web crawling
439, listening 440, and analytics 441 management sub-modules. In
this and other embodiments the web crawling 439, listening 440, and
analytics 441 management sub-modules are used by the merchant to
perform web analytics operations familiar to skilled practitioners
of the art. As an example, the merchant may use the web crawling
439 management sub-module to perform web crawling operations to
discover conversation threads associated with its products. Once
discovered, the listening 440 management sub-module may be used to
monitor the conversations threads, which are then analyzed with the
analytics 441 management sub-module to determine their relevance
and possible effect on social commerce operations. Those of skill
in the art will be knowledgeable of many such examples.
Accordingly, the foregoing is not intended to limit the spirit,
scope, or intent of the invention.
[0053] In one embodiment, the fraud 442 management module comprises
an abuse reporting 443, traffic 444, links 445, Internet Protocol
(IP) 446, and dashboard 447 management sub-modules. In this and
other embodiments, the abuse reporting 443, traffic 444, links 445,
Internet Protocol (IP) 446, and dashboard 447 management
sub-modules are used by the merchant to identify, mitigate, and
prevent fraudulent behavior within the social commerce market place
system. As an example, the traffic 444, links 445, and IP 446
management sub-modules may be used to identify the source of
fraudulent behavior. Once identified, it may be reported by the
abuse reporting 443 management sub-module and then displayed for
review within a user interface by the dashboard 447 sub-module.
[0054] In another embodiment, the payment 448 module comprises a
traffic 449, payment 450, 1099 Form 451, buyers 452, and payment
processor 453, management sub-modules. In this and other
embodiments, the traffic 449, payment 450, 1099 451, buyers 452,
and payment processor 453, management sub-modules are used by the
merchant for the management of payment to affiliates. As an
example, the buyers 452 and traffic 449 management sub-modules may
be used to identify individual buyers and the traffic they generate
at an affiliate's social commerce storefront. In turn, the payment
450 and payment processor 453 sub-modules may be used to track the
payments made by the buyers, which are then processed by various
payment processors. Likewise, the same sub-modules may be used to
track commission payments made by the merchant to individual
affiliates. The output of those sub-modules may then be processed
by the 1099 Form 451 sub-module for managing reporting of the
commission payments to the affiliate to the Internal Revenue
Service (IRS).
[0055] In yet another embodiment, the administration 454 module
comprises companies 455, target 456, users 457, roles 458, deals
459, moderation 460, profile 461, and email 462 management
sub-modules. In this embodiment, the companies 455, target 456,
users 457, roles 458, deals 459, moderation 460, profile 461, and
email 462 management sub-modules are used by the merchant to
administer the various users of the social commerce marketplace
system. As an example, the target 456 management sub-module may be
used, individually or in conjunction with, the target 456, users
457, profile 461, and roles 458 management sub-modules to identify
specific users of a social media environment. Once identified,
their social media interactions may be monitored by the moderation
460 management sub-module, and in turn the email 462 and deals 459
management sub-modules may be used individually, or in combination,
to target predetermined users.
[0056] In still another embodiment, the reports module 463
comprises traffic abuse 463, traffic 465, search engines 466, users
467, content status 468, and competitors 469 reporting sub-modules.
In this embodiment, the traffic abuse 463, traffic 465, search
engines 466, users 467, content status 468, and competitors 469
reporting sub-modules are used by the merchant to generate various
reports related to social commerce operations, which in turn may be
provided to an affiliate. As an example, the content status 468
reporting sub-module may report on the status of various items of
social commerce content and the search engines 466 reporting
sub-module may report on the search results it generates. In turn,
the traffic reporting 465 sub-module may be used to report on the
social commerce traffic resulting from the search results and the
users 467 reporting sub-module may provide reports related to the
various users referred to the social commerce site. Likewise, the
traffic abuse reporting sub-module 464 may be used to report on
various traffic abuses related to the social commerce marketplace
system, while the competitors 469 reporting sub-module may provide
reports related to competitive activity from competitors.
[0057] In various embodiments, the widgets module 470 may comprise
web crawling 471, keyword analysis 472, analytics 473, widget
manager 474, data 475, semantic analysis 476, catalog management
477, scoring 478, hot spots manager 479, sentiment analysis 480,
keyword widget 481, social keyword widget 482, API 483,
recommendations engine 484, social score widget 485 and in-line
links widget 486 sub-modules. In one embodiment, the web-crawling
471 sub-module is implemented to perform web crawling operations to
discover keywords within web pages. In another embodiment, the
keyword analysis 472 sub-module is implemented to determine related
keywords, competition of keywords, search frequency of keywords,
and locality of keywords. In yet another embodiment, the analytics
473 sub-module is implemented to provide the utilization of widgets
by visitors. In still another embodiment, the widget manager 474
sub-module is implemented to provide a set of user interfaces to
configure and publish a widget. In various embodiments, the widget
manager 474 sub-module is implemented to provide templates that
comprise user interface (UI) themes and interactions that determine
the end-user experience. In these and other embodiments, the widget
manager 474 sub-module comprises a wizard that provides a
multi-step process to configure the widget. In one embodiment, the
widget manager 474 sub-module comprises a dashboard providing a UI
to access the wizard, embed associated programming code, and
generate related reports.
[0058] In one embodiment, the data 475 sub-module is implemented to
process social graph, user, and catalog data. In another
embodiment, the semantic analysis 476 sub-module is implemented to
semantically extract keywords, topics, people and places from
strings of text. In another embodiment, the catalog 476 sub-module
is implemented with a widget to process catalog data. In yet
another embodiment, the hot spots manager 477 sub-module comprises
a set of user interfaces to configure and publish images and videos
that contain hot spots. In still another embodiment, the sentiment
analysis 478 sub-module is implemented to extract positive, neutral
and negative tone from strings of text. In one embodiment, the page
keyword widget 479 sub-module is implemented to provide a widget
that automatically matches catalog products to the context of
keywords extracted from a web page. In another embodiment, the
social keyword widget 480 sub-module is implemented to provide a
widget that automatically matches catalog products to a user's
context by matching keywords and themes from their social graph. In
yet another embodiment, the API 481 sub-module is implemented to
provide an API between a widget and various operating environments.
In still another embodiment, the recommendation engine 482
sub-module is implemented to automatically select or recommend
objects that best match the user's context based on a set of
algorithms. In one embodiment, the social score widget 783
sub-module is implemented to provide a widget that dynamically
presents catalog products and discounts according to a user's
social score. In yet another embodiment, the in-line links widget
784 sub-module is implemented to provide a widget that
automatically creates in-line hyperlinks within text strings based
on keywords that match objects from a catalog. It will be
appreciated that many such embodiments are possible and the
foregoing is not intended to limit the spirit, scope or intent of
the invention.
[0059] FIG. 5 is a generalized flow chart of social commerce
initiation operations performed on behalf of an affiliate in
accordance with an embodiment of the invention. In this embodiment,
affiliate social commerce operations are begun in step 502,
followed by a candidate affiliate providing information to a
merchant in step 504 to register as an affiliate. The merchant then
uses the provided information to create a social commerce
storefront for the affiliate in step 506. The affiliate then
proceeds to select a product to add to their social commerce
storefront in step 508. In various embodiments, the product is
selected from a plurality of available products contained in a
master catalog. The selected product is then added to the
affiliate's social commerce storefront in step 510. In various
embodiments, a selected product becomes a purchasable product once
it is added to the affiliate's social commerce storefront.
[0060] The affiliate then views their social commerce storefront in
step 512, followed by a determination being made in step 514
whether to add an additional product. If so, then the process is
continued, proceeding with step 508. Otherwise, an article related
to one or more of the purchasable products is written in step 516
and then posted to the affiliate's social commerce storefront. The
ongoing sales results of the affiliate's social commerce storefront
is then tracked in step 518, as well as the ongoing ranking of its
performance relative to other affiliate social commerce storefronts
in step 520. Ongoing conversion of organic searches resulting in
sale is likewise tracked in step 522, followed by affiliate social
commerce initiation operations being ended in step 524.
[0061] FIGS. 6a-d are generalized depictions of social commerce
initiation operations performed on behalf of an affiliate within a
plurality of user interface windows in accordance with an
embodiment of the invention. In this embodiment, a social commerce
storefront management module, as described in greater detail
herein, is implemented within a window 604 of a user interface (UI)
602. As shown in FIG. 6a, the UI window 604 comprises data entry
fields 606 for a candidate affiliate to provide information to
initiate the creation of a social commerce storefront. Referring
now to FIG. 6b, the affiliate then provides additional information
610 associated with their social commerce storefront. As shown in
FIG. 6c, the affiliate selects the category 614 of their social
commerce storefront, and as likewise shown in FIG. 6d, selects
products 614 to be displayed for purchase within their social
commerce storefront.
[0062] FIG. 7 is a generalized flow chart of the performance of
social commerce operations as implemented in accordance with an
embodiment of the invention. In this embodiment, social commerce
operations are begun in step 702, followed by the affiliate
managing the integration of the social commerce storefront in step
704 with a social media environment, such as a social network. In
various embodiments, the integration may be with an affiliate web
site or blog. The affiliate then launches the social commerce
storefront in step 706, followed by the importation of friends,
family, and associates from one or more social media environments
(e.g., a social network) in step 708. The friends, family and
associates are then matched with products that are appropriate to
their interests in step 710, followed by a determination in step
712 whether to create a promotional offer for them. If so, then a
promotional offer is created in step 714 and the process is
continued, proceeding with step 712. Otherwise, a determination is
made in step 716 whether the affiliate will offer to provide an
offer to pay a commission to the friends, family or associates in
return for referrals. If so, then a commission offer is prepared in
step 718 and the process is continued, proceeding with step 716.
Otherwise the promotion offers(s), the commission offer(s), or
both, are displayed to the friends, family and associates in-line
within the social media environment in step 720. Ongoing activity
at the affiliate's social commerce storefront, and the
corresponding success of the offer(s), is tracked in step 722 and
social commerce operations are then ended in step 724.
[0063] FIG. 8 is a generalized flow chart of the performance of
social commerce advertising network management operations as
implemented in accordance with an embodiment of the invention. In
this embodiment, advertising network operations are begun in step
802, followed by ongoing operations in step 804 for affiliate and
enterprise channels to manage their online advertisements. In step
806 the affiliate and enterprise channels perform ongoing
operations to select online advertisements for purchase, followed
by corresponding ongoing operations in step 808 to place the
purchased online advertisements in predetermined online locations.
In steps 810, 812, 814, 816, and 818, the affiliate and enterprise
channels perform ongoing operations respectively display the online
advertisements in social commerce storefronts, online newsletters,
social media channels, online billboards, and enterprise sites.
Ongoing operations are then performed in step 820 to correlate
sales to the placement of the online advertisements, followed by
advertising network operations being ended in step 822.
[0064] FIGS. 9a-b show the creation of an affiliate offer within a
user interface window in accordance with an embodiment of the
invention. In this embodiment, a social commerce storefront deals
management module, as described in greater detail herein, is
implemented within a window 904 of a user interface (UI) 902. As
shown in FIG. 9a, the UI window 904 comprises an `Offers` tab 906,
a data entry field 908 for information related to the merchant and
the affiliate making the offer, and associated data entry fields
910 corresponding to details of the purchasable product. Likewise,
the UI window 904 comprises data entry fields 912 corresponding to
details of the offer, as well as an offer display window 914 that
provides a preview of the offer as it will appear when presented
within a social media environment. As likewise shown in FIG. 9a,
data display field 916 displays summary information corresponding
to a related offer, and as shown in FIG. 9b, a corresponding offer
display window 918 providing a preview of the related offer, as
well as data display fields 920 displaying summary information
corresponding to other offers.
[0065] FIG. 10 shows the display of affiliate offers within a user
interface window implemented in accordance with an embodiment of
the invention. In this embodiment, a social commerce storefront
deals management module, as described in greater detail herein, is
implemented within a window 1004 of a user interface (UI) 1002. As
shown in FIG. 10, the UI window 1004 comprises an `Offers` tab
1006, as well a listing 1008 of a plurality of offers and related
information 1010.
[0066] FIG. 11 shows the display of affiliate network feeds and
associated offers within a user interface window implemented in
accordance with an embodiment of the invention. In this embodiment,
a social commerce storefront deals management module, as described
in greater detail herein, is implemented within a window 1104 of a
user interface (UI) 1102. As shown in FIG. 11, the UI window 1104
comprises an `Offers` tab 906, as well a listing 1108 of a
plurality of advertising network feeds corresponding to referrals
resulting from associated offers, and related information 1110.
[0067] FIG. 12 is a generalized flow chart of the performance of
content syndication operations as implemented in accordance with an
embodiment of the invention. In this embodiment, content
syndication operations are begun in step 1202, followed by the
ongoing generation of search engine optimization (SEO) content by
an affiliate, a professional author, or both, in step 1204. Ongoing
syndication operations are then performed in step 1206 to syndicate
the SEO content other sites and establish corresponding links.
Then, in step 1208, ongoing operations are performed to post the
SEO content to other content marketplaces known to skilled
practitioners of the art. A determination is then made in step 1210
whether enterprises (e.g., corporations) elect to accept the SEO
content. If so, then ongoing operations are performed by the
enterprises in step 1212 to accept the SEO content for online
publication. As an example, a corporation may elect to post
predetermined SEO content on their internal web site for review by
employees.
[0068] However, if it is determined in step 1210 that enterprises
do not elect to accept the SEO content, or if they do so in step
1212, then a determination is made in step 1214 whether other
affiliates elect to accept the SEO content for online publication.
If so, then ongoing operations are performed by affiliates in step
1216 to accept the SEO content for publication in step 1217. For
example, another affiliate may elect to publish SEO content that is
complementary to content they generate themselves. However, if it
is determined in step 1214 that other affiliates do not elect to
accept the SEO content, or if they do so in step 1216, then ongoing
operations are performed in step 1218 for enterprises, affiliates,
or both, to post a "bounty" (i.e., an offer for compensation) for
content creation. Thereafter, ongoing operation are performed in
step 1220 to track authors, the content they generate, their
corresponding reputation ratings, and the monetary value they
receive as compensation for providing the content. Content
syndication operations are then ended in step 1222.
[0069] FIG. 13 is a generalized flow chart of the performance of
billboard management operations as implemented in accordance with
an embodiment of the invention. In this embodiment, online
billboard management operations familiar to those of skill in the
art are begun in step 1320, followed by the ongoing aggregation of
the most popular product content in step 1304. A micro site, such
as a small, specialized web site, is then created in step 1306,
followed by ongoing operations in step 1309 to determine high
rankings for challenging key words used in searches for product
information. Ongoing operations are then performed in step 1310 to
drive traffic to affiliate social commerce storefronts, such as
using the high ranking challenging key words in search engine
optimization (SEO) operations known to skilled practitioners of the
art. Thereafter, ongoing operations are performed in step 1312 to
determine high ranking niche focus key words, followed by ongoing
operations being performed by affiliates in step 1314 to drive
traffic to their storefronts, and accordingly, receive compensation
from a merchant for doing so. In step 1316, ongoing operations are
performed by the merchant to challenge small affiliates to
challenge the sales performance of larger affiliates. Online
billboard management operations are then ended in step 1318.
[0070] FIG. 14 is a generalized flow chart of the performance of
product categorization operations as implemented in accordance with
an embodiment of the invention. In this embodiment, product
categorization operations are begun in step 1402, followed by the
receipt of recurring data feeds of catalog data from a vendor,
merchant or other product source in step 1404. The catalog data is
then processed in step 1406 to acquire stock keeping units (SKUs)
related to an individual vendor, merchant or other product source,
their corresponding merchant category pairs, Global Trade Item
Numbers (GTINs), and manufacturer part numbers (MPNs). As used
herein, a merchant category pair refers to a pairing of an
individual vendor, merchant or other product source and a
predetermined product category.
[0071] A SKU categorization file is then generated in step 1408,
followed by the addition of a SKU category column to the SKU
categorization file in step 1410. Then, in step 1412, target
product catalog data feeds are consolidated into batches for
processing. The consolidated product catalog data is processed to
identify products that have neither a MTN nor a GTIN (MPN|GTIN).
Catalog product data is then selected for processing in step 1412,
followed by a determination being made in step 1414 whether the
selected catalog product data comprises MPN|GTIN data. If so, then
a products crawler system, such as a web crawler system familiar to
those of skill in the art, is accessed and the selected catalog
product data is inputted in step 1418. The products crawler then
performs a search in step 1420 for the MPN|GTIN associated with the
selected product data. It will be appreciated by those of skill in
the art that in various embodiments the product crawler may be
implemented to crawl web pages, sites, and other data repositories
residing on the Internet at-large, private and proprietary data
repositories, or both.
[0072] A determination is then made in step 1422 whether the
product crawler has identified additional product data
corresponding to the MPN|GTIN associated with the selected product
data. If so, then a determination is made in step 1424 whether only
one product category is listed for the MPN|GTIN. If not, then a
determination is made in step 1426 whether the product category is
listed within the master product catalog. If so, then the product
crawler selects the first product category out of a set of listed
categories in step 1428. Thereafter, or if it was determined in
step 1424 that only one product category was listed, the product
crawler selects the first search result. Then, in step 1432, the
product crawler captures all required details from product content
associated with the link to the first search result. The product
crawler then matches the captured MPN|GTIN to the MPN|GTIN returned
in the product crawler search in step 1434, followed by making a
determination in step 1436 whether the product details between the
two MPN|GTIN are similar. If not, or if it was determined in step
1416 that the MPN|GTIN was not available, or in step 1422 that the
product crawler did not find a MPN|GTIN, or in step 1426 that a
product category was not listed, then the product data is sorted on
the basis of merchant category and product brand. Then, in step
1440, a merchant category is selected, followed by selecting the
first product brand in the selected merchant category.
[0073] A determination is then made in step 1442 whether the
product brand in the selected merchant category is "blank," (e.g.,
"generic," not specified, etc.). If so, then a check is performed
in step 1444 with the associated product image specifications and
product details to ascertain a product brand for each SKU with a
"blank" product brand. A determination is then made in step 1446
whether the product brand can be verified. If not, then the SKU
category within the SKU categorization file is assigned a value of
"uncategorized" and the process is continued, proceeding with step
1440. Otherwise, or if it was determined in step 1442 that the
product brand was not "blank," then for each product brand under
the merchant category, a category assigned by an automated process
is used as a benchmark and to initialize manual categorization for
unmapped products in step 1450. The benchmark category for the
product brand is then assigned in step 1452 as the category for
SKUs in the SKU categorization file.
[0074] However, if it was determined in step 1436 that the product
details between the two MPN|GTIN are not similar, then the product
crawler sets the first category as the category for the GTIN in the
SKU categorization file. Thereafter, or after the benchmark
category for the product brand has been assigned in step 1452, then
the product data is sorted, based on merchant category, in step
1454. Then, in step 1456, one merchant category at a time is
selected, with a final merchant category being assigned within the
master catalog, based on the least common category applicable for
all SKUs within that merchant and merchant category pair. The
product data is then populated in the master catalog, followed by a
determination in step 1460 whether to end product categorization
operations. If not, then the process is continued, proceeding with
step 1412. Otherwise, product categorization operations are ended
in step 1462.
[0075] FIG. 15 is a generalized flow chart of the performance of
product moderation operations in accordance with an embodiment of
the invention. In this embodiment, product moderation operations
are begun in step 1502, followed by the receipt of a recurring data
feed of "product offers" in step 1504. As used herein, "product
offers" refer to product data associated with a product being
offered for sale, or resale, by a merchant, vendor, manufacturer or
other product source. The product offer data feeds are then
processed by various systems associated with the product moderation
process in step 1506 and an automated product crawler system, such
as a web crawler system familiar to those of skill in the art, is
run on the URL of a selected product offer in step 1508.
[0076] A determination is then made in step 1510 whether the URL
associated with the selected product offer is broken. If so, then
the product offer is automatically or manually rejected in step
1516 and the process is continued, proceeding with step 1506.
Otherwise, a determination is made in step 1514 whether all
MPN|GTIN fields in the product offer are blank. If so, then the
product offer is automatically or manually rejected in step 1516
and the process is continued, proceeding with step 1506. Otherwise,
in step 1518, the product offer is entered into a work scheduler, a
master catalog URL is created, the product offer is assigned to a
moderator for auditing, and a moderation page is opened in a
separate browser window for the assigned moderator.
[0077] The assigned moderator then initiates the audit of an
assigned product offer in step 1520, followed by a determination
being made in step 1522 whether the title, brand, manufacturer, or
MPN|GTIN fields contain profanity. If so, then the product offer is
automatically or manually rejected in step 1516 and the process is
continued, proceeding with step 1506. Otherwise, a determination is
made in step 1524 whether the brand in the product offer title is
different than the brand referenced within the product offer
itself. If so, then the product offer is automatically or manually
rejected in step 1516 and the process is continued, proceeding with
step 1506. Otherwise, a determination is made in step 1526 whether
the manufacturer in the product offer title is different than the
brand referenced within the product offer itself. If so, then the
product offer is automatically or manually rejected in step 1516
and the process is continued, proceeding with step 1506.
[0078] Otherwise, a determination is made in step 1528 whether the
product image associated with the product offer passes image
checks. As an example, the product image may not pass the image
check if it contains pornography, nudity or profanity. As another
example, the product image may not pass the image check if shows a
product that is different than a product described within the title
of the product offer or within the product offer itself. If it is
determined in step 1528 that the product offer image does not pass
the image checks, then the product offer image is marked as "not
passed" in step 1530. Thereafter, or if it was determined in step
1528 that the product offer image passed the image checks, then a
determination is made in step 1532 whether the GTIN of the product
offer is different than the GTIN of the product itself. If so, then
a search is performed in step 1534, using GTIN, MPN, and
manufacturer name as search criteria to perform the search in the
master catalog.
[0079] A determination is then made in step 1536 whether the search
yielded an applicable product. If so, then the product data
associated with the applicable product is used in step 1538 to
replace (i.e., "switch") the product data associated with the
product offer. The process is then continued, proceeding with step
1532. However, if it was determined in step 1538 that the search
did not yield an applicable product, then a search is performed in
step 1540 using the MPN, GTIN, manufacturer name, and the title of
the product offer as search criteria. A determination is then made
in step 1542 whether the search yielded an applicable product. If
not, the product offer data feed is queried in step 1544 to
determine the Global Unique Identifier (GUID) associated with the
product offer. The GUID is then used to perform a search of the
master product catalog and the process is then continued,
proceeding with step 1536.
[0080] However, if it is determined in step 1542 that the search
yields an applicable product, then a new product is created in the
master catalog in step 1548 and populated with the details
associated with the product offer. Any information specific to the
merchant, vendor or other source of the product offer is then
removed from the new product listing in step 1550. A determination
is then made in step 152 whether the product image associated with
the new product listing is specific to the merchant, vendor or
other source of the product offer. If so, then the product image
associated with the product offer is marked as "unavailable" in
step 1554. Thereafter, or if the product image associated with the
new product listing is not specific to the merchant, vendor or
other source of the product offer, the process is continued,
proceeding with step 1532.
[0081] However, if it is determined in step 1532 that the GTIN of
the product offer is not different from the GTIN of the product
itself, then a determination is made in step 1556 whether the
product GTIN contains profanity. If so, then the process is
continued, proceeding with step 1534. Otherwise, a determination is
made in step 1558 whether the MPN, manufacturer name, or product
brand in the product offer is the same as the product itself. If
not, then a determination is made in step 1560 whether any related
product offers are mapped to the product itself. If so, then a
determination is made in step 1562 whether the MPN, manufacturer
name, or product brand in the product offer contains profanity. If
so, then the process is continued, proceeding with step 1534.
Otherwise, an edit function is implemented in step 1564 to manually
or automatically delete the profanity from MPN, manufacturer name,
or product brand in the product offer and the process is continued,
proceeding with step 1534. However, if it is determined in step
1560 that no other product offers are mapped to the product itself,
then the product detail is manually or automatically edited in step
1566 to have the same MPN, manufacturer name, or product brand as
the other product offer.
[0082] Thereafter, or if it is determined in step 1558 that the
MPN, manufacturer name, or product brand in the product offer is
the same as the product itself, a determination is made in step
1568 whether the manufacturer name or product brand contains
profanity. If so, then the product offer is either manually or
automatically edited in step 1570 to have the same product brand
and manufacturer name as in the related product offer or any
identified profanity is deleted. Thereafter, or if is determined in
step 1568 that there is no profanity in the manufacturer name or
product brand, then a determination is made in step 1572 whether
the product image associated with the product offer is marked "not
passed." If so, then an "unavailable image" is selected in step
1574 as the product image. Otherwise, a determination is made in
step 1576 whether the product image passes image checks. If not,
then a product offer image is selected in step 1578 as the product
image in the master catalog, or alternatively, an "unavailable
image" is selected if the product offer image has merchant-related
text. Otherwise, or once the product offer images have respectively
selected in steps 1574 or 1578, the product offer is approved in
step 1580. A determination is then made in step 1582 whether to end
product moderation operations. If not, then the process is
continued, proceeding with step 1506. Otherwise, product moderation
operations are ended in step 1584.
[0083] FIGS. 16a-b are a generalized flow chart of the performance
of search engine optimization (SEO) goal attainment operations as
implemented in accordance with an embodiment of the invention. In
various embodiments, a SEO algorithm is implemented in a syndicated
commerce environment to predict the amount of financial
compensation an individual or social commerce marketplace entity
can receive from the sale of a predetermined product. In certain
embodiments, the SEO algorithm is further implemented to optimize
their web pages to increase site traffic, and as a result, the
likelihood of reaching their financial goals.
[0084] In these and other embodiments, the SEO algorithm determines
keyword options for a predetermined product based upon the
product's description, its web page content, and other related
information. The social commerce marketplace system then uses the
SEO algorithm to determine the product's associated search traffic
and rank-per-keyword from various search engines. This information,
in addition to sales conversion rate information, is used to
estimate the likelihood of monetization for a single keyword or a
group of keywords. In certain embodiments, the SEO algorithm
refines its estimates by tracking and analyzing historical purchase
records for a given path and visitor segment. The system then
automatically modifies the website pages with optimal combinations
of keywords. Once optimized, various search engines are
automatically notified of the changes to the web pages to improve
organic search rankings.
[0085] In various embodiments, the SEO algorithm determines the
competitiveness for a predetermined keyword and then assigns it a
"level of difficulty" for a user to succeed in organic search
optimization. Likewise, the "level of difficulty" is used by the
SEO algorithm to determine how much money the user could
potentially earn selling products that correspond to a given level
of difficulty. In these and other embodiments, the "level of
difficulty" is further refined according to analysis of the user's
generated content and any additional data the social commerce
marketplace system can capture from a visitor to the user's
website. The SEO algorithm then determines the likelihood of a
relationship or visitor associated with the user's social graph to
purchase a predetermined product. Once the likelihood is
determined, the social commerce marketplace system creates tasks
for the user, monitors the progress of their completion, and makes
ongoing recommendations to assist the user in reaching their
revenue goals. In one embodiment, a crawler sub-module is
implemented with the SEO algorithm to crawl a predetermined domain
or website to analyze the market opportunity or financial value of
the site. In this embodiment, the output of the analysis is a list
of markets to target, and a list of recommendations and tasks to
complete, to capitalize on each opportunity.
[0086] Referring now to FIG. 16, SEO goal operations are begun in
step 1602 to predict the estimated revenue of a predetermined
product, followed by addition of the predetermined product from a
store's catalog to a social commerce storefront in step 1604. In
various embodiments, the social commerce marketplace system
automatically creates an associated product details page within the
store when the product is added. In these and other embodiments,
the product details page comprises merchant, manufacturer, or store
owner-defined content such as a product title and descriptions. In
various embodiments, the store owner can optionally create
additional product content and metadata, such as:
[0087] Title
[0088] Short Description
[0089] Long Description
[0090] Friendly (vanity) URLs
[0091] Keywords
[0092] Specifications
[0093] Ratings
[0094] Reviews
[0095] Product Blog
[0096] Posts to third party social sites about the product
[0097] Then, in step 1606, manufacturer links, such as Uniform
Resource Locators (URLs), provided in the catalog feeds described
in greater detail herein are used by the social commerce
marketplace system as primary sources to crawl for product content.
In one embodiment, the social commerce marketplace system submits a
search request to a search engine to obtain links to crawl if the
manufacturer links are not included in the feed. In various
embodiments, the crawled content is indexed and used by other
process steps described in greater detail herein to identify
keywords and high value content.
[0098] The social commerce marketplace system then acquires the
domains included in the merchant's catalog feed(s) as well as the
highest ranked pages within predetermined search engines in step
1608. Then, in step 1610, the acquired domains and website URLs
(i.e., backlinks) are submitted to predetermined search engines, as
well as other data service providers, to retrieve the number,
quality, trust, and other information about the inbound links to
each domain. In various embodiments, this information is stored
within the social commerce marketplace system and is subsequently
used to determine the relative competitiveness of other vendors in
the market as well as sources to crawl for recommended content and
keywords for use in various SEO operations.
[0099] Then, in step 1612, social graph information and social site
history from predetermined social network sites for the store's
social accounts (e.g., store entity, store owner users, etc.) is
retrieved. The retrieved information is then analyzed by the SEO
algorithm in step 1614 to identify high-value keywords, content,
backlinks and influencers for the product within the social
graph(s). In various embodiments, the retrieved product information
may be contained in social objects such as "wall posts," comments,
"tweets," profiles, stores, events, etc. In various embodiments,
the retrieved content is semantically analyzed to determine the
sentiment (i.e., the "tone" of the content) for each extracted
element. In certain of these various embodiments, the social
commerce marketplace system scores the retrieved keywords and
content according to the source's authoritative value and the
content creator's social influence (e.g., their digital worth
score).
[0100] As used herein, authoritative value broadly refers to the
contextual relationship of a keyword to the overall theme of its
associated content source. As an example, the search term "Lincoln
automobile" may return the phrase "the Lincoln automobile is named
after President Abraham Lincoln," where the content source is a
first web page primarily oriented to the history of President
Lincoln. In this example, authoritative value is low. As another
example, the same search term may return the same phrase, but from
a second web page primarily oriented to the history of the Lincoln
automobile. In this example, the authoritative value is high.
[0101] As likewise used herein, social influence broadly refers to
the level of influence a user of a social networking environment is
capable of exerting upon a predetermined market segment. In various
embodiments, a digital worth score is derived from a user's social
influence. As used herein, a digital worth score refers to a
numeric value, or set of values, associated with a predetermined
user's social influence. As an example, a user may write a blog
extolling the virtues of a product, with the result that a high
percentage of the readers of the blog purchase the product. In this
example, the writer of the blog would have a high digital worth
score. In these and other embodiments, the financial value of the
associated purchase(s) of the referenced product is used to
determine the digital worth score.
[0102] In various embodiments, the SEO algorithm uses additional
information associated with the content authors and influencers
that is stored within the social commerce marketplace system,
including their:
[0103] name
[0104] email addresses
[0105] IP Address
[0106] geographic location
[0107] preferences
[0108] The social commerce marketplace system then retrieves
available historical clickstream web analytics information in step
1616. In various embodiments, the analytics information is
retrieved from corporate web sites associated with the store owner
that contain product or product related information. The analytics
information is then processed to generate inputs for the SEO
algorithm in step 1618. In various embodiments, the retrieved
analytics information includes:
[0109] Web Analytics Data [0110] Visitor personal information
(e.g., name, demographics, prior purchase history, etc.) [0111]
Referring keywords (e.g., associated with source, visitor,
geo-location, temporal information, etc.) [0112] Conversion
Data
[0113] Listening Platform Data [0114] Content [0115] Source (e.g.,
person or entity) [0116] Sentiment [0117] Media (e.g., web,
television, radio, etc.) [0118] Location
[0119] One or more authoritative sites are then crawled in step
1620 to determine keywords and content related to the product,
which may include:
[0120] titles
[0121] product name
[0122] descriptions
[0123] ratings
[0124] reviews
[0125] pricing
[0126] discounts
[0127] offers
[0128] location(s)
[0129] As used herein, an authoritative site broadly refers to the
contextual relationship of individual content elements within a
content source.
[0130] To extend the previously-used example, the phrase "the
Lincoln automobile is named after President Abraham Lincoln," in a
first web page primarily oriented to the history of President
Lincoln may not be considered to be an authoritative site on the
Lincoln automobile. Conversely, the same phrase in a second web
page primarily oriented to the history of the Lincoln automobile
may be considered to be an authoritative site on the Lincoln
automobile.
[0131] Once the product has been added to the on-line store, the
social commerce marketplace system semantically extracts topics,
themes and keywords from the product's content and associated
metadata in step 1622. In various embodiments, such content and
associated metadata comprises: [0132] merchant or
manufacturer-defined content (e.g., titles, descriptions,
promotion, pricing, etc.) [0133] store owner-defined content [0134]
content defined by other store owners [0135] visitor-generated
content [0136] third party content and data sources (e.g.,
backlinks)
[0137] In various embodiments, additional third party data related
to the product is extracted and stored within the social commerce
marketplace system, including:
[0138] sales information, such as: [0139] number of units
manufactured and sold [0140] average sales price [0141] sales
location
[0142] ratings and reviews
[0143] demographics related to owners of the product
[0144] A list of keywords, themes and topics from the previous
process steps, along with any additional keywords that were
extracted for the same catalog product when it was last added or
analyzed for other stores is then generated in step 1624. The
resulting list is then submitted to various search engines as well
as other data service providers to retrieve additional information
in step 1626. Search results corresponding to each element of the
submitted list is then received in step 1628. In various
embodiments, the search results include: [0145] keyword ideas,
referring to additional sets of keywords that are related to the
submitted keyword [0146] local search traffic, referring to the
number of searches submitted to the search engine for a
predetermined geographic region [0147] global search traffic,
referring to the number of searches submitted to the search engine
by all Internet users [0148] mobile search traffic, referring to
the number of searches submitted to the search engine via mobile
devices [0149] frequency, referring to the frequency that the
keyword is searched [0150] competition, referring to the relative
frequency of bids combined with the value and associated ad price
of each keyword within various advertising networks [0151] traffic
estimation, referring to the estimated traffic, the estimated
number of paid visits, the estimated paid search rank, and the
estimated paid search cost per day [0152] category, referring to
various businesses, industries, genera's, etc. that the search
engine has determined that the keyword is most closely associated
with [0153] domains and websites, referring to a list of the
highest-ranked domain or website for a predetermined keyword [0154]
demographics, referring to the demographics corresponding to a set
of users that used the keyword [0155] purchase conversion
information, referring to a list of products and prices that a user
purchased after searching with a keyword combined with the
corresponding site where the purchase was made [0156] ad
competition, referring to the relative market competitiveness of
the keyword for a paid search within a commercial search engine
service or within an advertising network [0157] vendors competitive
pricing information, referring to a list of top-performing vendors
selling a product associated with a predetermined product, combined
with its current price
[0158] The keyword search results received in step 1628 are then
analyzed by the SEO algorithm in step 1630 to generate a keyword
score corresponding to each keyword's estimated effect on inbound
traffic, conversion rate, competiveness, competitive pricing, and
other factors. Then, in step 1632, the SEO algorithm uses a variety
of SEO formulas and optimization best practices to process the
keyword scores generated in step 1630 to generate a ranked list of
keywords predicted to result in the highest amount of traffic and
conversion rates.
[0159] In step 1634, the user (e.g., an online store owner) uses
various financial goal information to set financial goals for the
product before it is published to the online store. In various
embodiments, the financial goal information may include: [0160]
commissions, referring to the amount of monthly commission revenue
the store owner would like to generate for the product [0161] ad
revenue, referring to the amount of monthly ad revenue the store
owner would like to generate for the product's associated product
detail page [0162] quantity, referring to the number of product
units the store owner would like to sell on a monthly basis
[0163] A series of market opportunity (i.e., market penetration)
scores are then generated in step 1636 from the data collected and
analyzed in the previous process steps to identify areas that the
product may perform well in (e.g., low competition, high demand,
etc.). In various opportunities, these areas may include [0164]
local market, referring to one or more local geographic areas
[0165] social network, referring to one or more social networks or
populations (i.e., segments) of users [0166] geo-location/region,
referring to a state, country, or other geographic region [0167]
search marketing, referring to a paid search market for a
predetermined commercial search engine [0168] market segment,
referring to a group of individuals with similar
characteristics
[0169] The social commerce marketplace system then uses the
preceding goals, selected list of keywords, and opportunity scores
in step 1638 to determine the estimated traffic and related SEO
elements (e.g., the number of backlinks links, etc.) required to
reach the financial goals of the online store. Then, in step 1640,
the social commerce marketplace system calculates the estimated
difficulty of achieving the financial goals, which provides the
store owner the information required to make a decision if they
should include the product within their online store. In one
embodiment, the financial goal information provided in step 1634 is
presented to the online store owner to show the potential financial
opportunity by market segment. It will be appreciated that such
information would assist the online store owner in focusing and
aligning their marketing efforts to those market segments that
represent the greatest financial opportunities.
[0170] The product is then saved to the online store and its
corresponding product details page is published to the online
store's website in step 1642, followed by a determination being
made in step 1644 whether to continue SEO goal attainment
operations. If so, then the process is continued, proceeding with
step 1604. Otherwise, SEO goal attainment operations are ended in
step 1644.
[0171] FIG. 17 shows a ranked list of keywords within a user
interface window that are predicted to result in the highest amount
of traffic and corresponding conversion rates. In this embodiment,
a user interface (UI) 1702, such as a web browser, is implemented
to comprise a UI window 1704, which in turn comprises a plurality
of search phrases 1706 that are ranked according to their predicted
ability to result in the highest amount of traffic and
corresponding conversions rates.
[0172] FIG. 18 shows estimated traffic and SEO elements within a
user interface window that are anticipated to affect an online
store's ability to reach its financial goals. In this embodiment, a
user interface (UI) 1702, such as a web browser, is implemented to
comprise a UI window 1804, which in turn comprises a financial goal
window 1806 and a requirements window 1812 comprising a plurality
of estimated traffic and SEO elements are anticipated to affect an
online store's ability to reach its financial goals.
[0173] In one embodiment, the financial goal window 1806 comprises
a financial goal amount data entry field 1808 and a `Calculate`
command button 1810. In this embodiment, a user enters a financial
goal amount in the financial goal amount data entry field 1808 and
then selects the `Calculate` command button 1810. The estimated
traffic and SEO elements required to reach the financial goal are
calculated and then displayed in the requirements window 1812.
[0174] FIG. 19 is a generalized flow chart of the performance of
keyword submission optimization operations implemented in
accordance with an embodiment of the invention. Those of skill in
the art will recognize that the effectiveness of a keyword used
within a site, such as an online storefront, is dependent upon
whether it is used in the context of an authoritative content
source, such as a web page containing product details. In various
embodiments, the SEO algorithm is implemented to suggest keywords
and predict their respective monetary SEO value when used to
promote the sale of a product. In these and other embodiments, the
SEO algorithm is likewise implemented to automate HTML code updates
with associated keywords to make the target page authoritative. It
will be appreciated that such automation can provide novice users
with SEO optimizations that are typically only available from an
SEO expert.
[0175] In this embodiment, keyword submission optimization
operations are begun in step 1902 to automatically insert the
keywords generated in step 1624 and selected in step 1632 of the
process described in the descriptive text of FIG. 16. The social
commerce marketplace system then automatically inserts the
aforementioned keywords into the target webpage's keywords meta tag
within its associated HTML code in step 1904. In one embodiment, a
user (e.g., the online store owner) can manually update the
keywords within the keywords meta tag at any time through a user
interface (UI).
[0176] Then, in step 1906, the social commerce marketplace system
automatically inserts the product title provided by the merchant or
a manufacturer into the webpage's HTML title tag. In one
embodiment, a user (e.g. the online store owner) can manually
update the title tag at any time through a UI. The social commerce
marketplace system then automatically inserts the product title
provided by the merchant or a manufacturer into the alt image tag
for the product image's URL in step 1908. In one embodiment, a user
(e.g. the online store owner) can manually update the alt image tag
at any time through a UI.
[0177] A friendly URL that contains text elements from the
product's title is then automatically created by the social
commerce marketplace system in step 1910. As used herein, a
friendly URL refers to a URL pointing to a location that references
a topic or subject that is indicated in the name of the URL. As an
example, the URL may contain the name of a product that is promoted
within the URL's associated page or site. Then, in step 1912, the
social commerce marketplace system automatically inserts the
product title from the merchant/manufacture into the webpage's HTML
H1 heading tag. In various embodiments, a user (e.g., the online
store owner) can manually update any of the H1 through H6 HTML
heading tags at any time through a UI. In various embodiments, the
social commerce marketplace system also automatically updates other
HTML elements expected by commercial search engines such as:
[0178] meta content language
[0179] meta content type
[0180] meta language
[0181] meta author
[0182] meta copyright
[0183] robots meta tag
[0184] The target web page is then published to a production
instance of the online store in step 1914. Once the target web page
is published, the social commerce marketplace system automatically
creates an HTML site map for the online store in step 1916 and
keeps it updated thereafter. In various embodiments, the web page's
index within the site map is updated whenever a material change
(e.g., in its page name, title, URL, etc.) occurs.
[0185] Skilled practitioners of the art will be aware that it is
common for search engine crawlers to use sitemap.xml files to help
them index a target website. To assist such search engine crawlers
the sitemap.xml file for the online store is automatically updated
by the social commerce marketplace system in step 1918 whenever
there is a material change (e.g., new page, URL name change, etc.).
Those of skill in the art will likewise be aware that it is also
common for search engine crawlers to use robots.txt files to help
them understand which areas of the site to index. To assist such
search engine crawlers the robots.txt file for the online store is
automatically updated by the social commerce marketplace system in
step 1920 whenever there is a material change (e.g., new page, URL
name change, etc.).
[0186] Then, in step 1922, the social commerce marketplace system
automatically submits the page to various search engines to notify
them if there was a change to the online store, such as in the
page's HTML elements, its URL, or if the page was newly created or
deleted. The social commerce marketplace system then automatically
identifies potential issues and creates tasks for the user to
remedy them in step 1924. In various embodiments, such issues may
include:
[0187] not enough keywords
[0188] too many keywords
[0189] recommended product description text
[0190] add keywords to URLs
[0191] A determination is then made is step 1926 whether to end
keyword submission optimization operations. If not, then the
process is continued, proceeding with step 1904. Otherwise, keyword
submission optimization operations are ended in step 1928.
[0192] FIG. 20 shows information that is proactively submitted to a
commercial search engine and its associated SEO effect within a
user interface window. In this embodiment, a user interface (UI)
1702, such as a web browser, is implemented to comprise a UI window
1704, which in turn comprises a target keywords sub-window 2006,
recommendations window 2010, and a product description window 2016.
As shown in FIG. 20, the target keywords sub-window 2006 comprises
a plurality of target keywords 2008 and the product description
window 2016 comprises a plurality of product description data 2018.
In various embodiments, the target keywords 2008 and the plurality
of product description data 2018 is processed to generate an SEO
optimization prediction 2012 and a list of tasks 2014 to increase
the likelihood of an online storefront to achieve their financial
goals.
[0193] FIGS. 21a-b are a generalized flow chart of the performance
of product and store performance optimization operations
implemented in accordance with an embodiment of the invention.
Skilled practitioners of the art will recognize that two online
stores promoting the same product, and using the same content and
underlying SEO algorithm, can anticipate receiving approximately
the same traffic and recognizing the same sales volume for the
product. As a result, each online store will only recognize
approximately half of the available revenue generated by the
product.
[0194] In various embodiments, an SEO algorithm is implemented to
mitigate the potential deterioration of the earning value of a
product promoted by similar online stores by: [0195] generating
recommendations for changes to online store of product content,
including the generation of content ideas for a user [0196]
generating recommendations regarding where their marketing messages
should be syndicated, including automated processed to efficiently
perform the syndication [0197] analyzing the online store and store
users' social network to determine its value and then making
recommendations to capitalize on the network's potential [0198]
generating recommendations and associated tasks to capitalize on
market opportunities
[0199] In these and other embodiments, the social commerce
marketplace system evaluates the online store's SEO status,
individual product detail page SEO status, and other factors to
generate tasks for a user (e.g., the store owner) to complete to
improve the likelihood of achieving their revenue goals.
[0200] In this embodiment, product and store performance
optimization operations are begun in step 2102. Then, in step 2104,
the social commerce marketplace system retrieves social graph
information associated with a user (e.g., an online store owner),
which is then used to determine their relationships, influence,
reach within their network, and the corresponding influence and
reach of each of those relationships for the online store and each
store user. Based upon each store owner's digital worth and social
graph, the social commerce marketplace system then generates
recommended tasks in step 2106 to improve the likelihood of the
online store reaching its financial goals. In various embodiments,
these tasks include: [0201] comment and posting tasks, including a
list of content sources within each social network that should have
a comment or response posted by the user [0202] syndication tasks,
including a list of people and the creation of backlinks to the
online store [0203] friend request tasks, including a list of users
within each social network the user should build a relationship
with due to the user's influence and digital worth score [0204]
store creation, including recommendations on the type of online
store to create within each social network and any maintenance the
user should complete to keep the store interesting and current
[0205] ads, including recommendations on the type of ads to place
within a specific social network
[0206] Then, in step 2108 the social commerce marketplace system
recommends social networking tasks for the user (e.g., the online
store owner), including the creation of new types of blog posts and
changes to make to existing blog posts. In one embodiment, the
social commerce marketplace system identifies other online store
blogs within a social network site that the user should consider
building backlinks with to mutually benefit each party. In another
embodiment, the social commerce marketplace systems recommends
specific blog sites that have the highest market opportunity to
attract powerful influencers, who in turn will create backlinks to
the on line store. In this and other embodiments, the backlinks are
created directly through page links, or indirectly through
re-tweets, wall posts, etc. to drive organic traffic to the online
store. In yet another embodiment, the social commerce marketplace
system recommends the frequency of updates, content to post, and
the types of offers to make within the blogs.
[0207] In step 2110, the social commerce marketplace system
identifies third party influencers and creates recommended tasks
that provide both ideas and instructions to obtain backlinks from
each target. In one embodiment, in addition to existing targets
based on their individual value, the social commerce marketplace
system also recommends targets based upon the aggregate long-term
value of the market opportunity associated with the target. In this
embodiment, a determination is made regarding how valuable the
target's social graph and influence are within a market segment and
the likelihood that they will generate additional relationships
that the online store can capitalize upon in the future.
[0208] The social commerce marketplace system then automatically
generates recommended tasks in step 2112 to make changes to product
detail pages, widgets, store blogs, or the online store's home page
to improve the online store's SEO performance and subsequent
traffic. In various embodiments, these recommendations are based
upon visitor activity within a social network environment, their
associated purchase activity, online store content changes, and
other information. Then, in step 2114, the social commerce
marketplace system generates recommend lead generation tasks,
including: [0209] list of contacts to target [0210] type of
communication to use (e.g., tweets, email, posts, etc.) [0211] type
and structure of offers to make (e.g., packaging, bundling,
pricing, etc.) [0212] time and date to send communications [0213]
frequency of re-marketing activities [0214] recommended campaigns,
including outlines of markets to target, the type of campaign to
run, and the duration of the campaign.
[0215] The social commerce marketplace system then generates
recommended search engine tasks in step 2116. In one embodiment,
the social commerce marketplace system analyzes the competition and
then recommends search engine keyword bidding activities for each
identified marketing opportunity. In another embodiment, a
recommendation is generated to determine marketing spend allocation
to optimize various Search Engine Marketing (SEM) programs. Then,
in step 2118, the social commerce marketplace system generates
recommended pricing and offers that should be created and presented
to each market segment or individual visitor. In various
embodiments, the social commerce marketplace system analyzes
competitive factors for each market opportunity segment and
recommends optimized pricing and discount structures to optimize
conversion rates, revenue and margins for each segment.
[0216] In step 2120, the social commerce marketplace system
analyzes competitive factors (e.g., lower competition, more demand,
etc.) for each market opportunity segment and then recommends
specific ratings and reviews to associate with each product to
optimize conversation and revenue uplift. Then, in step 2122, the
social commerce marketplace system identifies markets and market
segments that have arbitrage opportunity, which are then used to
generate a list of recommended market tasks that capitalize on the
arbitrage opportunities. Examples of market arbitrage opportunities
include:
[0217] high demand|low adoption rates
[0218] high demand|low sales penetration rates
[0219] high demand|lack of competitive vendor pricing
[0220] shifts in buying patterns
[0221] high demand|low inventory availability
[0222] time-of-product in a market
[0223] In one embodiment, the social commerce marketplace system
performs an analysis to determine if there is an opportunity (e.g.,
based upon projected revenue or margin) to liquidate products to a
specific market. In another embodiment, the social commerce
marketplace system performs an analysis to recommend the type of
marketing campaigns to execute within a specific market. In yet
another embodiment, the social commerce marketplace system performs
an analysis to recommend whether or not the online store should
create a micro-site store for a specific market opportunity. In
still another embodiment, the social commerce marketplace system
performs an analysis to recommend `local` physical locations to
open a Flash `pop-up` store based upon a local market
opportunity.
[0224] Then, in step 2124, the social commerce marketplace system
tracks ad spend and response rates across radio, television, and
web media to generate recommendations for the optimal allocation of
ad spend. In one embodiment, the social commerce marketplace system
monitors ad spends for a specific product or product category to
determine on-line marketing and merchandising tasks to capitalize
on the ad influence to determine which products to sell, where
(e.g., region, location, etc.) to sell them, and at what pricing
point. In step 2126, the social commerce marketplace system then
generated recommendations regarding what types of product to stock
according to their anticipated sales rate such that various online
stores can optimize their inventory levels to achieve higher net
margins for a given market segment or opportunity.
[0225] The social commerce marketplace system then generates
recommendations in step 2128 regarding which products to sell,
which products to bundle, the price of a product, and the discount
to apply, based upon the visitor's context or intent and the market
opportunity analysis. In one embodiment, the social commerce
marketplace system recommends which products to market to a
specific market segment. In another embodiment, the social commerce
marketplace system recommends which related products to offer or
present to visitors based on the current product they are viewing
and their market opportunity context. For example, a particular
type of hair product may be presented, according to the user's
local market trends and demand.
[0226] Then, in step 2130, the social commerce marketplace system
analyzes procurement demand within predetermined markets and market
segments to determine areas of opportunity. Based upon each
opportunity, the social commerce marketplace system generates
recommendations regarding which products to bid, pricing and
packaging. After the recommended tasks have been completed, the
social commerce marketplace system re-executes the SEO algorithm in
step 2132 to update financial prediction as well as recommended
store tasks. A determination is then made in step 2134 whether to
end product and store performance optimization operations. If not,
then the process is continued, proceeding with step 2104.
Otherwise, product and store performance optimization operations
are ended in step 2136.
[0227] The present invention is well adapted to attain the
advantages mentioned as well as others inherent therein. While the
present invention has been depicted, described, and is defined by
reference to particular embodiments of the invention, such
references do not imply a limitation on the invention, and no such
limitation is to be inferred. The invention is capable of
considerable modification, alteration, and equivalents in form and
function, as will occur to those ordinarily skilled in the
pertinent arts. The depicted and described embodiments are examples
only, and are not exhaustive of the scope of the invention.
[0228] For example, the above-discussed embodiments include
software modules that perform certain tasks. The software modules
discussed herein may include script, batch, or other executable
files. The software modules may be stored on a machine-readable or
computer-readable storage medium such as a disk drive. Storage
devices used for storing software modules in accordance with an
embodiment of the invention may be magnetic floppy disks, hard
disks, or optical discs such as CD-ROMs or CD-Rs, for example. A
storage device used for storing firmware or hardware modules in
accordance with an embodiment of the invention may also include a
semiconductor-based memory, which may be permanently, removably or
remotely coupled to a microprocessor/memory system. Thus, the
modules may be stored within a computer system memory to configure
the computer system to perform the functions of the module. Other
new and various types of computer-readable storage media may be
used to store the modules discussed herein. Additionally, those
skilled in the art will recognize that the separation of
functionality into modules is for illustrative purposes.
Alternative embodiments may merge the functionality of multiple
modules into a single module or may impose an alternate
decomposition of functionality of modules. For example, a software
module for calling sub-modules may be decomposed so that each
sub-module performs its function and passes control directly to
another sub-module.
[0229] Consequently, the invention is intended to be limited only
by the spirit and scope of the appended claims, giving full
cognizance to equivalents in all respects.
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