DYNAMIC INTERNET SHOPPING METHOD AND SYSTEM

• US 20090240555A1
• Filed: 12/08/2005
• Published: 09/24/2009
• Est. Priority Date: 12/10/2004
• Status: Abandoned Application

• Current Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Original Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Inventors: Panje, Krishna Prasad
• Application Number:
  US11/721,198
• Publication Number:
  US 20090240555A1
• Time in Patent Office: Days
• US Class Current: 705/10
• 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
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]
• CPC Class Codes: G06Q 30/0631 Item recommendations

Abstract

(57) Previous shopping sequences'"'"' (8) factors (9)—such as shopping site (10,11) or the item considered for purchase—are collected (50) and stored (52) at a shopping portal (16). When a potential customer engages (56) in a present shopping sequence (13), the factors (9) thereof are compared (58) at a facility (17) to the factors (9) of the previous shopping sequences (8). If the factors of the present shopping sequence match those of any previous shopping sequence, substantially the same information (18) furnished to the previous customers is furnished to the potential customer.

Claims

1. A method of presently recommending goods or services to a potential customer over a distributed network, comprising:

(a) detecting and storing selected factors of a previous shopping sequence of the potential customer and/or of one or more other customers, the previous shopping sequence(s) having occurred at a shopping site or sites and having resulted in the furnishing of selected information thereat;

(b) in response to the potential customer presently engaging in a shopping sequence at a present shopping site, comparing selected stored factors of the previous shopping sequence(s) to corresponding factors of the present shopping sequence; and

(c) furnishing to the potential customer only information that is substantially the same as that which was furnished during those previous shopping sequence(s) which had selected factors that are substantially matched by the corresponding factors of the present shopping sequence.

2. A method as in claim 1, which further comprises:

(d) weighting and differentiating the selected stored factors to selectively affect the content and amount of the furnished information.

3. A method as in claim 1, which further comprises:

in step (c), furnishing to the potential customer additional information that is generally similar to the furnished information.

4. A method as in claim 3, which further comprises:

weighting and differentiating the selected stored factors to selectively affect the content and amount of the furnished information and the additional information.

5. A method as in claim 1, wherein:

the selected stored factors include at least the identification of the goods or services that were the subject of the previous shopping sequence(s) and the identification of the previous shopping site.

6. A method as in claim 5, wherein:

the stored factors also include at least the location of the customer(s) during the previous shopping sequence(s).

7. A method as in claim 6, wherein:

the selected stored factors also include one or more of the following;

the time and/or day during which the previous shopping sequence(s) occurred;

whether or not the goods or services involved in the previous shopping sequence(s) were purchased;

the price or price range of the goods or services involved in the previous shopping sequence(s);

the brand(s) of the goods or services involved in the previous shopping sequence(s);

if the goods or services involved in the previous shopping sequence(s) were purchased, whether payment was in cash or by credit card;

the age and/or sex of the customer(s) involved in the previous shopping sequence.

8. A method as in claim 1, wherein:

the shopping sites are virtual or physical, and

at least some of the steps are carried out via the internet.

9. A method as in claim 8, wherein:

at least one of the steps is performed via a computer, a PDA, a mobile telephone or manual entry.

10. A method as in claim 1, wherein:

at least one of the steps is performed via a computer, a PDA, a mobile telephone or manual entry.

17. A system as in claim 5, wherein:

the selected stored factors also include one or more of the following;

the time and/or day during which the previous shopping sequence(s) occurred;

whether or not the goods or services involved in the previous shopping sequence(s) were purchased;

the price or price range of the goods or services involved in the previous shopping sequence(s);

the brand(s) of the goods or services involved in the previous shopping sequence(s);

if the goods or services involved in the previous shopping sequence(s) were purchased, whether payment was in cash or by credit card;

the age and/or sex of the customer(s) involved in the previous shopping sequence.

11. A system for presently recommending goods or services to a potential customer over a distributed network, comprising:

(a) facilities for detecting and storing selected factors of a previous shopping sequence of the potential customer and/or of one or more other customers, the previous shopping sequence(s) having occurred at a shopping site or sites and having resulted in the furnishing of selected information thereat;

(b) facilities responsive to the potential customer presently engaging in a shopping sequence at a present shopping site for comparing selected stored factors of the previous shopping sequence(s) to corresponding factors of the present shopping sequence; and

(c) facilities for furnishing to the potential customer only information that is substantially the same as that which was furnished during those previous shopping sequence(s) which had selected factors that are substantially matched by the corresponding factors of the present shopping sequence.

12. A system as in claim 11, which further comprises:

(d) facilities for weighting and differentiating the selected stored factors to selectively affect the content and amount of the furnished information.

13. A system as in claim 11, wherein:

the information-furnishing facilities include facilities for furnishing to the potential customer additional information that is generally similar to the furnished information.

14. A system as in claim 13, wherein:

the information-furnishing facilities include facilities for weighting and differentiating the selected stored factors to selectively affect the content and amount of the furnished information and the additional information.

15. A system as in claim 11, wherein:

the detecting and storing facilities detect and store at least the identification of the goods or services that were the subject of the previous shopping sequence(s) and the identification of the previous shopping site.

16. A system as in claim 15, wherein:

the detecting and storing facilities further detect and store at least the location of the customer(s) during the previous shopping sequence(s).

18. A system as in claim 11, wherein:

the shopping sites are virtual or physical, and

at least some of the facilities include or are connected to the internet.

19. A system as in claim 18, wherein:

at least one of the facilities includes or is connected to a computer, a PDA, a mobile telephone or manual entry apparatus.

20. A system as in claim 11, wherein:

at least one of the facilities includes or is connected to a computer, a PDA, a mobile telephone or manual entry apparatus.