Method and a system for analysing traffic on a website including multiple visits by the visitors

• US 8,825,841 B2
• Filed: 03/25/2011
• Issued: 09/02/2014
• Est. Priority Date: 03/25/2011
• Status: Active Grant

• Current Assignee: SiteCore A/S
• Original Assignee: SiteCore A/S
• Inventors: Seifert, Michael, Person, Ralph Ronald
• Primary Examiner(s): Bengzon, Greg C
• Application Number:
  US13/072,342
• Publication Number:
  US 20120246296A1
• Time in Patent Office: 1,257 Days
• Field of Search: None
• US Class Current: 709/224
• CPC Class Codes: G06F 16/957 Browsing optimisation, e.g. caching or content distillation
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0246 Traffic
• CPC Class Codes: H04L 67/02 based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

A method and a system for analyzing traffic on a website are disclosed, the website being arranged on a server. The method comprises the steps of allowing a visitor to perform multiple visits on the website, and monitoring navigations and/or actions performed by the visitor during each visit while accumulating value points in accordance with content viewed by the visitor and actions performed by the visitor, and in accordance with predefined value point settings associated with content of the website, thereby obtaining a value point score for each visit. An origin of the first visit, leading the visitor to the website, is registered and categorized according to type of origin in accordance with two or more predefined categories of origin. An accumulated value point score for the visitor is obtained by adding the obtained value point scores of the first visit and each of the subsequent visit(s). Thereby the website owner obtains information regarding total value generated by the visitor during all visits and regarding what initially lead the visitor to the website. This allows the website owner to evaluate marketing campaigns and to focus and/or improve marketing efforts.

Claims

1. A method for analysing traffic on a website, the website being arranged on a server, the method comprising the steps of:

allowing a visitor to perform a first visit on the website,

monitoring, by a computer device, navigations and/or actions performed by the visitor during the first visit while accumulating value points in accordance with content viewed by the visitor and actions performed by the visitor, and in accordance with predefined value point settings associated with content of the website, thereby obtaining a value point score for the first visit,

registering an origin of the first visit, leading the visitor to the website,

storing the value point score for the first visit along with the registered origin of the first visit in a storage device,

categorising the stored value point score for the first visit and the origin of the first visit according to type of origin in accordance with two or more predefined categories of origin,

allowing the visitor to perform one or more subsequent visit(s) on the website,

for each subsequent visit, monitoring navigations and/or actions performed by the visitor during the visit while accumulating value points in accordance with content viewed by the visitor and actions performed by the visitor, and in accordance with predefined value point settings associated with content of the website, thereby obtaining a value point score for each subsequent visit,

obtaining an accumulated value point score for the visitor by adding the obtained value point scores of the first visit and each of the subsequent visit(s),

allowing a plurality of visitors to perform one or more visits on the website,

for each visitor, registering a sequence of visits on the website, registering and categorising origin of each visit, obtaining value point score of each visit, and obtaining an accumulated value point score for the visitor,

defining a set of visitors from the plurality of visitors, and

building visit patterns based on the categorized origins of each visit by the visitors of the set of visitors, where the registered sequences of visits form the visit patterns, the visit patterns including one or more full visit patterns, each full visit pattern corresponding to a complete registered sequence of visits of at least one visitor, wherein the visit patterns form an ordered tree data structure, where the categories of the origins of the visits form nodes of the ordered tree data structure,

wherein the ordered tree data structure is built such that a sequence of nodes in an order along a path extending downwardly and starting from a node at a first level of the ordered tree data structure and ending at a node from which no branches extend downwardly represents a sequence of visits to the website by at least one of visitors of the set of visitors, said visits respectively originating from the categorized origins corresponding to the sequence of nodes, and the sequence of visits to the website is in the same order of the sequence of nodes, wherein the sequence of visits to the website are originating from different categorized origins.

2. The method according to claim 1, further comprising the step of storing the accumulated value point score in the storage device along with the registered and categorised origin of the first visit.

3. The method according to claim 1, further comprising the steps of, for each subsequent visit:

registering an origin of the visit, leading the visitor to the website, and

storing the value point score of the visit along with the registered origin of the visit in the storage device.

4. The method according to claim 3, further comprising the step of categorising the origin of each subsequent visit according to type of origin in accordance with two or more predefined categories of origin.

5. The method according to claim 1, further comprising the steps of:

analysing accumulated value point scores and categorised origins of the first visits originating from a plurality of visitors on the website, and

generating a report providing information regarding accumulated value point scores originating from predefined categories of origin.

6. The method according to claim 5, further comprising the step of generating at least one sub-report providing information regarding accumulated value point scores originating from various origins of first visits within a predefined category of origin.

7. The method according to claim 5, wherein the step of generating a report comprises generating and displaying a visual representation of the accumulated value point scores and the predefined categories of origin.

8. The method according to claim 5, further comprising the step of registering time elapsed between visits of the visitor on the website, and wherein the generated report further provides information regarding time elapsed between visits of the visitor.

9. The method according to claim 5, further comprising the step of registering time duration of each visit performed by the visitor on the website, and wherein the generated report further provides information regarding time duration of the visits of the visitor.

10. The method according to claim 5, wherein the step of obtaining an accumulated value point score is performed immediately prior to or as a part of the step of analysing.

11. The method according to claim 1, further comprising the steps of:

defining a set of visitors having been exposed to a predefined campaign, and

for each visitor of the set of visitors, defining a visit originating from the predefined campaign as the first visit on the website by the visitor.

12. The method according to claim 1, further comprising the step of:

for each full visit pattern, calculating a total visit value being the sum of accumulated value point scores for all visitors with registered sequences forming said full visit pattern.

13. The method according to claim 12, further comprising the step of identifying a most efficient full visit pattern being the full visit pattern with the highest total visit value per visitor in the full visit pattern.

14. The method according to claim 1, wherein the visit patterns further include at least one partial visit pattern, each partial visit pattern corresponding to a part of registered sequence of at least one visitor.

15. The method according to claim 14, further comprising the steps of:

analysing each partial visit pattern, and

for each partial visit pattern, identifying a value point loss for said partial visit pattern, based on the analysis step.

16. The method according to claim 1, further comprising the steps of:

for each visitor, assigning a node value to each node corresponding to a visit of the sequence of visits, the node value being the accumulated value point score for the visitor, and

for each node, calculating a total node value being the sum of all node values assigned to the node.

17. The method according to claim 16, further comprising the step of assigning a node count to each node, the node count being the number of visitors having a sequence of visits including a visit corresponding to said node.

18. The method according to claim 17, further comprising the step of, for each node, calculating a total node efficiency per visitor being the total node value divided by the node count.

19. The method according to claim 16, further comprising the step of analysing the ordered tree data structure and the node values.

20. The method according to claim 19, further comprising the step of identifying a most valuable full visit pattern of the ordered tree data structure, based on the analysis step.

21. The method according to claim 19, further comprising the step of identifying a most efficient full visit pattern of the ordered tree data structure, based on the analysis step.

22. The method according to claim 19, further comprising the step of identifying a most valuable node of the ordered tree data structure, based on the analysis step.

23. The method according to claim 19, further comprising the step of identifying a most efficient node of the ordered tree data structure, based on the analysis step.

24. The method according to claim 1, wherein the origin of the first visit includes a referral which referred the visitor to the website.

28. The method according to claim 1, wherein the ordered tree data structure is built such that a node at a first level of the ordered tree data structure represents that a first visit to the website by at least one of the visitors of the set of visitors originates from the categorized origin corresponding to the node at the first level of the ordered tree data structure.

29. The method according to claim 1, wherein the ordered tree data structure is built such that the number of nodes of a sequence of nodes along a path extending downwardly and starting from a node at a first level of the ordered tree data structure and ending at a node from which no branches extend downwardly represents the number of visits to the website for at least one of the visitors of the set of the visitors.

25. A system for analysing traffic on a website arranged on a server, the system comprising:

a monitoring module adapted to monitor navigations and/or actions performed by a visitor during a sequence of visits on the website by said visitor, said monitoring module further being adapted to accumulate value points in accordance with content viewed by the visitor and actions performed by the visitor, and in accordance with predefined value point settings associated with the content of the website, thereby obtaining a value point score for each visit of the sequence of visits, said monitoring module further being adapted to register an origin of a first visit of said sequence of visits, leading the visitor to the website at said first visit, and said monitoring module further being adapted to add obtained value point scores of each of the visits of the sequence of visits, thereby obtaining an accumulated value point score for the visitor,

a storage device for storing value point scores and/or accumulated value point scores along with registered origins of first visits, for each visitor visiting the website,

a categorising module adapted to categorise stored accumulated value point scores and origins of first visits according to type of origin in accordance with two or more predefined categories of origin, and

an analysis module adapted to analyse stored and categorised accumulated value point scores and origins of first visits originating from a plurality of visitors, wherein the analysis module is adapted to build visit patterns based on sequences of visits by visitors of a defined set of visitors, where the sequences of visits form the visit patterns, and wherein the visit patterns form an ordered tree data structure, where the categories of the origins of the visits form nodes of the ordered tree data structure,

wherein the ordered tree data structure is built by the analysis module such that a sequence of nodes in an order along a path extending downwardly and starting from a node at a first level of the ordered tree data structure and ending at a node from which no branches extend downwardly represents a sequence of visits to the website by at least one of visitors of the set of visitors, said visits respectively originating from the categorized origins corresponding to the sequence of nodes, and the sequence of visits to the website is in the same order of the sequence of nodes, wherein the sequence of visits to the website are originating from different categorized origins.

26. The system according to claim 25, wherein the categorising module forms part of the monitoring module.

27. The system according to claim 25, said system residing on the server having the website arranged thereon.

30. The system according to claim 25, wherein the ordered tree data structure is built by the analysis module such that a node at a first level of the ordered tree data structure represents that a first visit to the website by at least one of the visitors of the set of visitors originates from the categorized origin corresponding to the node at the first level of the ordered tree data structure.

31. The system according to claim 25, wherein the ordered tree data structure is built by the analysis module such that the number of nodes of a sequence of nodes along a path extending downwardly and starting from a node at a first level of the ordered tree data structure and ending at a node from which no branches extend downwardly represents the number of visits to the website for at least one of visitors of the set of the visitors.