METHOD FOR VISUALIZING CUSTOMER INSIGHTS

• US 20110106581A1
• Filed: 10/30/2009
• Published: 05/05/2011
• Est. Priority Date: 10/30/2009
• Status: Abandoned Application

• Current Assignee: emnos GmbH (ROBUR Industry Service Group GmbH)
• Original Assignee: emnos GmbH (ROBUR Industry Service Group GmbH)
• Inventors: Rohrbasser, Patrick, Götz, Sandro
• Application Number:
  US12/609,241
• Publication Number:
  US 20110106581A1
• Time in Patent Office: Days
• US Class Current: 705/7.29
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data

Abstract

A method for visualizing customer insights, comprising the steps of: receiving information data including at least one of transaction, product, shop and customer-related information data; generating a predefined analysis report by associating respective information included in the received information data with each other; parameterizing the generated analysis report with at least one user defined parameter; and outputting the parameterized predefined analysis report.

Claims

1. A method for visualizing customer insights, comprising the steps of:

receiving information data including at least one of transaction, product, shop and customer-related information data;

generating a predefined analysis report by associating respective information included in the received information data with each other;

parameterizing the generated analysis report with at least one user defined parameter; and

outputting the parameterized predefined analysis report.

2. The method of claim 1, wherein the predefined analysis report includes at least one of key measure report, assortment analysis report, cross purchase report, repeat purchase report, switching report, and customer profile report.

3. The method of claim 1, wherein the user defined parameter is based on at least one of time interval, branch, store, brand, product, group of products and user defined data sets.

4. The method of claim 1, wherein the information data includes information data relating to at least one of unique identifier, customer birthday, employee status, customer gender, nation description, town, postal code, identifier of customer, identifier of the household, customer start date, product, item quantity, price of position, identifier of shop, identifier of transaction, and date of transaction.

5. The method of claim 2, wherein the step of generating the predefined analysis report is based on associating respective information on at least one of store level, category level, brand level, product level and user defined data set.

6. The method of claim 3, wherein the user defined data set can be defined based on a product hierarchy, pre-defined product groups, import of stock keeping unit data, user defined time intervals.

7. The method of claim 1, wherein the information data is based on at least one of point-of-sale data, retailer data, transaction data, household data, shopping card data, consumer data being based on at least one of demographic data, shopping preference data and financial data.

8. The method of claim 2, wherein the key measure report is based on associating information related to a specific product or product group and a specific time period, thereby visualizing the performance of the specified product.

9. The method of claim 8, wherein the performance of the specific product is visualized for at least one of customer segment, time period, product category.

10. The method of claim 2, wherein the assortment analysis report is based on associating information related to attributes of customers who have purchased a first group of products with attributes of customers who have purchased a second group of products.

11. The method of claim 10, wherein the assortment analysis report is visualized for weekly sales and repeat purchase rate.

12. The method of claim 2, wherein the cross purchase report is based on associating information related to a vendor of a product and a specified product.

13. The method of claim 12, wherein the cross purchase report is visualized for at least one of loyal customers and repertoire customers.

14. The method of claim 2, wherein the repeat purchase report is based on associating information related to a specific product with attributes of customers.

15. The method of claim 14, wherein the repeat purchase report is visualized for at least one of time period, customer segments, competition, comparable product launch.

16. The method of claim 2, wherein the switching report is based on associating information related to customers with at least two specific products.

17. The method of claim 16, wherein the switching report is visualized for at least two time periods.

18. The method of claim 2, wherein the customer profile report is based on building customer profiles by grouping customers with similar attributes and associating the resulting customer profilers with at least one specific product.

19. A computerized system for visualizing customer insights, comprising:

at least one database having information data including at least one of transaction, product, shop and customer-related information data;

a first computer-based system having access to the database and being configured to perform the steps of;

receiving a request for generating a predefined analysis report;

receiving a user defined parameter;

generating the requested predefined analysis report by associating respective information included in the information data with each other and parameterizing the generated predefined analysis report with at least one user defined parameter;

outputting the parameterized requested predefined analysis report.

20. The computerized system of claim 19, further comprising a second computer-based system coupled to the first computer-based system via a network configured to send the request for generating the predefined analysis report and the user defined parameter and to receive and display the outputted analysis report.

21. The computerized system of claim 19, wherein the first computer-based system is further configured to generate the predefined analysis report as at least one of key measure report, assortment analysis report, cross purchase report, repeat purchase report, switching report, and customer profile report.

22. The computerized system of claim 19, wherein the user defined parameter is based on at least one of time interval, branch, store, brand, product, group of products and user defined data sets.

23. The computerized system of claim 19, wherein the information data includes information data relating to at least one of unique identifier, customer birthday, employee status, customer gender, nation description, town, postal code, identifier of customer, identifier of the household, customer start date, product, item quantity, price of position, identifier of shop, identifier of transaction, and date of transaction.

24. The computerized system of claim 19, wherein the step of generating the predefined analysis report is based on associating respective information on at least one of store level, category level, brand level, product level and user defined data set.

25. The computerized system of claim 19, wherein the user defined data set can be defined based on a product hierarchy, pre-defined product groups, import of stock keeping unit data, user defined time intervals.

26. The computerized system of claim 19, wherein the information data is based on at least one of point-of-sale data, retailer data, transaction data, household data, shopping card data, consumer data being based on at least one of demographic data, shopping preference data and financial data.

27. The computerized system of claim 26, further comprising a third computer-based system having access to the database and providing the information data.

28. A computer-readable medium including instructions which cause a computer-based system to perform the steps of:

receiving information data including at least one of transaction, product, shop and customer-related information data;

generating a predefined analysis report by associating respective information included in the received information data with each other;

parameterizing the generated analysis report with at least one user defined parameter; and

outputting the parameterized predefined analysis report.