METHODS AND SYTEMS FOR COMPILING MARKETING INFORMATION FOR A CLIENT

• US 20140365275A1
• Filed: 08/26/2014
• Published: 12/11/2014
• Est. Priority Date: 06/21/2010
• Status: Active Grant

• Current Assignee: Salesforce.com, Inc.
• Original Assignee: Salesforce.com, Inc.
• Inventors: Newton, Christopher Daniel
• Granted Patent: US 9,070,137 B2
• Time in Patent Office: Days
• US Class Current: 705/7.29
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 43/04 Processing captured monitoring data, e.g. for logfile generation
• CPC Class Codes: H04L 43/045 for graphical visualisation of monitoring data
• CPC Class Codes: H04L 67/02 based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

Methods and systems for compiling marketing information for a client are provided. Data can be obtained from a plurality of social media websites, where each of the social media websites includes a universal resource identifier that points to a client website. A plurality of insights can be extracted from the obtained data, resulting in extracted insights. Each of the extracted insights comprises text elements that denote product approval for at least one product available for sale at the client website. Measurements of traffic to the client website can be collected, the traffic being referred to the client website by the plurality of social media websites. A referred traffic dynamics summary table can then be generated based on the extracted insights and the measurements of traffic. The referred traffic dynamics summary table aggregates the extracted insights across the plurality of social media websites to rank the extracted insights.

Claims

1. A method of compiling marketing information for a client, the method comprising:

obtaining data from a plurality of social media websites, wherein each of the social media websites includes a universal resource identifier that points to a client website;

extracting a plurality of insights from the obtained data, resulting in extracted insights, wherein each of the extracted insights comprises text elements that denote product approval for at least one product available for sale at the client website;

collecting measurements of traffic to the client website, the traffic being referred to the client website by the plurality of social media websites; and

generating a referred traffic dynamics summary table based on the extracted insights and the measurements of traffic, wherein the referred traffic dynamics summary table aggregates the extracted insights across the plurality of social media websites to rank the extracted insights.

2. The method of claim 1, wherein the referred traffic dynamics summary table ranks the extracted insights in accordance with their value in bringing business to the client.

3. The method of claim 1, wherein the referred traffic dynamics summary table ranks the extracted insights in accordance with an assumption that the extracted insights have contributed to a decision to buy the at least one product available for sale at the client website.

4. The method of claim 1, wherein the obtaining data from the plurality of social media websites, comprises:

crawling blog posts that appear on the plurality of social media websites to obtain crawled blog posts.

5. The method of claim 4, wherein the crawling comprises:

crawling blog posts that contain at least one link to the client website.

6. The method of claim 4, wherein the extracting the plurality of insights from the obtained data, resulting in extracted insights, comprises:

extracting the plurality of insights from the crawled blog posts.

7. The method of claim 6, wherein collecting the measurements of traffic to the client website, comprises:

collecting the measurements of traffic to the client website, the traffic being referred to the client website by referring blog posts on the plurality of social media websites.

8. The method of claim 7, wherein the collecting comprises:

collecting one or more events recorded in the client website.

9. The method of claim 8, wherein the collecting comprises recording one or more of the following events:

visits to the client website;

number of orders of products from the client website;

number of orders of products from the client website divided into a category; and

number of downloads from the client website.

10. The method of claim 6, wherein generating comprises:

generating a referred traffic dynamics summary table based on the extracted insights and the measurements of traffic, wherein the referred traffic dynamics summary table aggregates the measurements of traffic associated with the extracted insights across the crawled blog posts to rank the extracted insights.

11. A non-transitory computer readable medium having computer readable instructions stored thereon for execution by a processor, the computer readable instructions capable of performing a method for compiling marketing information for a client, the method comprising:

obtaining data from a plurality of social media websites, wherein each of the social media websites includes a universal resource identifier that points to a client website;

extracting a plurality of insights from the obtained data, resulting in extracted insights, wherein each of the extracted insights comprises text elements that denote product approval for at least one product available for sale at the client website;

collecting measurements of traffic to the client website, the traffic being referred to the client website by the plurality of social media websites; and

generating a referred traffic dynamics summary table based on the extracted insights and the measurements of traffic, wherein the referred traffic dynamics summary table aggregates the extracted insights across the plurality of social media websites to rank the extracted insights.

12. The non-transitory computer readable medium of claim 11, wherein the referred traffic dynamics summary table ranks the extracted insights in accordance with their value in bringing business to the client.

13. The non-transitory computer readable medium of claim 11, wherein the referred traffic dynamics summary table ranks the extracted insights in accordance with an assumption that the extracted insights have contributed to a decision to buy the at least one product available for sale at the client website.

14. The non-transitory computer readable medium of claim 11, wherein the obtaining data from the plurality of social media websites, comprises:

crawling blog posts that contain at least one link to the client website and that appear on the plurality of social media websites to obtain crawled blog posts.

15. The non-transitory computer readable medium of claim 14, wherein the extracting the plurality of insights from the obtained data, resulting in extracted insights, comprises:

extracting the plurality of insights from the crawled blog posts.

16. The non-transitory computer readable medium of claim 15, wherein collecting the measurements of traffic to the client website, comprises:

collecting the measurements of traffic to the client website, the traffic being referred to the client website by referring blog posts on the plurality of social media websites.

17. The non-transitory computer readable medium of claim 16, wherein the collecting comprises:

collecting one or more events recorded in the client website.

18. The non-transitory computer readable medium of claim 17, wherein the collecting comprises recording one or more of the following events:

visits to the client website;

number of orders of products from the client website;

number of orders of products from the client website divided into a category; and

number of downloads from the client website.

19. The non-transitory computer readable medium of claim 15, wherein generating comprises:

generating a referred traffic dynamics summary table based on the extracted insights and the measurements of traffic, wherein the referred traffic dynamics summary table aggregates the measurements of traffic associated with the extracted insights across the crawled blog posts to rank the extracted insights.

20. A referred traffic analysis system for compiling marketing information for a client, the referred traffic analysis system comprising:

a processor; and

a plurality of modules comprising computer readable instructions stored on a non-transitory computer readable medium for execution by the processor, the modules comprising;

a collector module comprising computer instructions capable of obtaining data from a plurality of social media websites, wherein each of the social media websites includes a universal resource identifier that points to a client website, and extracting a plurality of insights from the obtained data, resulting in extracted insights, wherein each of the extracted insights comprises text elements that denote product approval for at least one product available for sale at the client website;

a web analytics module comprising computer instructions capable of collecting measurements of traffic to the client website, the traffic being referred to the client website by the plurality of social media websites; and

an aggregator module comprising computer instructions capable of generating a referred traffic dynamics summary table based on the extracted insights and the measurements of traffic, wherein the referred traffic dynamics summary table aggregates the extracted insights across the plurality of social media websites to rank the extracted insights.