Purchase sequence browser

1. A method for browsing a purchase sequence, the method being implemented by one or more data processors and comprising the steps of:

generating, by at least one data processor, a purchase sequence analysis of a retailer's transaction data relating to purchases by a plurality of consumers;

providing, by at least one data processor, a graphical user interface that uses said purchase sequence analysis to facilitate insight discovery and exploration of product affinities across time;

providing a purchase sequence browser, said purchase sequence browser, in conjunction with said graphical user interface, further performing at least one any of the steps of:

allowing a user to browse most significant product phrases discovered by an exhaustive search of product affinities across time;

exploring a retail grammar to create both forward and backward phrase trees or alternate purchase paths starting from, or ending in, a product;

generating consistent purchase sequences given constraints on products and their order; and

profiling a value of a product across time with regard to other products fixed in time.

2. The method as in claim 1 , wherein the graphical user interface renders

a tree diagram showing an active product at all but a terminal time stamp;

wherein, by default, top products are active in first and second columns;

wherein, when a user selects any of the displayed products to be active, a list of products is populated in a next column based on all active products in the past; and

wherein default active products are kept as a first product in a new list.

3. The method as in claim 1 , wherein the graphical user interface enables backward exploration of an active product.

4. The method as in claim 1 , wherein the graphical user interface enables keeping of a time lag or not for an active product;

wherein, by default, a time-lag is one time-unit; and

wherein said user can ignore a particular time-slot.

5. The method as in claim 1 , further comprising:

using consistencies to grow forward using a forward aggregate scoring function.

6. The method as in claim 1 , further comprising:

using consistencies to grow backward using a backward aggregate scoring function according to the invention.

7. The method of claim 1 , wherein the providing comprises:

providing one or more panels, the panels comprising at least one of:

a product panel;

a sequence panel; and

a property panel.

8. The method of claim 1 further comprising:

providing a browser panel for allowing a user to browse pre-created high consistency product phrases;

providing an explorer panel for allowing a user to grow/shrink purchase sequences manually;

providing a generator panel for automatically generating phrases from a product set;

providing a profiler panel for showing time profiles of products for a given sequence; and

providing a favorites panel for collecting sequences that a user adds to favorites.

9. The method as in claim 8 , wherein the browser panel comprises:

a drop down list from which a user selects a product;

wherein all pre-created phrases that contain the selected product are listed in a table.

10. The method as in claim 9 , wherein the table comprises the following properties:

Phrase ID=row number in the PHRASE file;

Trigger Product (first product) name;

Length of the phrase; Duration of the phrase;

Phraseness measure (min/max); and

Ability to add other product properties as in bundles/bridges.

11. The method as in claim 8 , wherein the explorer panel comprises:

a drop-down menu that provides options to:

Display Phrase tree;

Explore Phrase FORWARD; and

Explore Phrase BACKWARD.

12. The method as in claim 11 , wherein a product is placed either in a top LEFT or top RIGHT corner of said explorer panel, depending on whether the user selected (FORWARD) or (BACKWARD) respectively.

13. The method as in claim 8 , wherein the The purchase sequence explorer panel comprises:

a forward phase tree and a backward phase tree, each said phase tree further comprising the following parameters:

Time Scale;

Maximum Length; and

Maximum Branch.

14. The method as in claim 8 , wherein the generator panel comprises at least one any of:

a product constraint, wherein a user may select two or more products either from the product panel or from the property panel, or from a sub-graph, neighbor, bundle, or bridge structure, wherein said generator generates product phrases using only these products; and

a set of order constraints, wherein a user specifies an order of certain products, wherein each product is anchored or non-anchored in a particular position, wherein an anchored product cannot change its position and all products above/below it must remain there in their ordering;

wherein a sorted list of product phrases that satisfy either or both constraints is generated.

15. The method as in claim 8 , wherein the profiler panel enables:

profiling any of consistency and phraseness of one or more products, wherein said profile is generated against at least one any of:

a given phrase with an entire phrase blanket, wherein all products in a phrase affect the profile;

a given phrase with a subset phrase blanket, wherein a chosen few products in a phrase affect the profile; and

a given phrase with a maximal phrase blanket, wherein each profile value is maximized across available phrase blankets.

16. The method as in claim 8 , wherein the profiler panel enables:

choosing measure to plot in a graph to show consistency of phraseness.

17. The method as in claim 16 , wherein the profiler panel enables: choosing a phrase blanket to use.

18. A method for browsing a purchase sequence, the method being implemented by one or more data processors and comprising:

generating, by at least one data processor, a purchase sequence analysis of a retailer's transaction data relating to purchases by a plurality of consumers;

providing, by at least one data processor, a graphical user interface that uses the purchase sequence analysis to facilitate insight discovery and exploration of product affinities across time;

wherein the graphical user interface enables:

allowing a user to browse most significant product phrases discovered by an search of product affinities across time;

exploring a retail grammar to create both forward and backward phrase trees or alternate purchase paths starting from, or ending in, a product;

generating consistent purchase sequences given constraints on products and their order; and

profiling a value of a product across time with regard to other products fixed in time.