Method for performing a market analysis

• US 20090144127A1
• Filed: 11/30/2007
• Published: 06/04/2009
• Est. Priority Date: 11/30/2007
• Status: Active Grant

• Current Assignee: Caterpillar Incorporated
• Original Assignee: Caterpillar Incorporated
• Inventors: Smith, Nigel G.
• Granted Patent: US 8,086,481 B2
• 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 30/0203 Market surveys; Market polls

Abstract

A method for performing a market analysis may include collecting survey data, which may include evaluation data for desired outcomes, the desired outcomes consisting of attributes of one or more products or services. The desired outcome evaluation data may include importance and satisfaction data. Further, the survey data may include evaluation data for potential features. The potential features evaluation data may include desirability data indicative of the affinity survey participants have for potential features. The method may further include processing the collected survey data using a computer processor. The processing may include calculating, based on the importance and satisfaction data, opportunity scores for the individual desired outcomes. The processing may also include correlating potential features with desired outcomes. In addition, the processing may include ranking the potential features based on the collected desirability data and the calculated opportunity score.

Claims

1. A method for performing a market analysis, comprising:

collecting survey data from survey participants, the survey data including;

evaluation data for desired outcomes, the desired outcomes consisting of attributes of one or more products or services, wherein the desired outcome evaluation data includes;

importance data indicative of the level of importance survey participants respectively attribute to the individual desired outcomes; and

satisfaction data indicative of the present level of satisfaction survey participants have with the ability of current products or services to achieve the individual desired outcomes; and

evaluation data for potential features that could be implemented to provide the desired outcomes, wherein the potential features evaluation data includes;

desirability data indicative of the affinity survey participants have for the individual potential features;

processing the collected survey data using a computer processor, including;

calculating, based on the importance data and the satisfaction data, opportunity scores for the individual desired outcomes, wherein the opportunity scores are indicative of the extent to which the desired outcomes are valued by the survey participants and presently unmet by current products or services; and

correlating potential features with desired outcomes that the potential features could provide; and

ranking the potential features based on the collected desirability data for the individual potential features and the calculated opportunity score for the individual desired outcomes.

2. The method of claim 1, wherein the potential features evaluation data includes:

inclusion data indicative of how survey participants would feel if the individual potential features were included in a product; and

exclusion data indicative of how survey participants would feel if the individual potential features Were excluded from a product.

3. The method of claim 2, further including using the processor to perform, for each potential feature, the following:

calculating a satisfaction coefficient indicative of the inclusion data for the respective potential feature;

calculating a dissatisfaction coefficient indicative of the exclusion data for the respective potential feature; and

calculating a desirability coefficient based on the satisfaction coefficient and dissatisfaction coefficient.

4. The method of claim 3, wherein, for each potential feature, the satisfaction coefficient is indicative of the number of survey participants that rated the respective potential feature as attractive or one-dimensional;

wherein a rating of attractive means that the survey participant would like it if the respective potential feature were included on a product and would feel indifferent or feel that it would be expected if the potential feature were not included on the product; and

wherein a rating of one-dimensional means that the survey participant would like it if the respective potential feature were included on the product and would dislike it if the potential feature were omitted from the product.

5. The method of claim 3, wherein the dissatisfaction coefficient is indicative of the number of survey participants that rated the respective potential feature as one-dimensional or expected;

wherein a rating of one-dimensional means that the survey participant would like it if a potential feature were included on the product and would dislike it if the potential feature were omitted from the product; and

wherein a rating of expected means that the survey participants expect that the product would normally include the potential feature.

6. The method of claim 3, wherein calculating the desirability coefficient includes subtracting the dissatisfaction coefficient from the satisfaction coefficient.

7. The method of claim 3, wherein calculating desirability coefficients involves weighting some responses of survey participants differently from others.

8. The method of claim 3, wherein ranking the potential features based on the collected desirability data and the calculated opportunity scores includes determining a desirability ranking for each of the potential features according to the calculated desirability coefficients and determining an opportunity ranking for each of the desired outcomes according to the calculated opportunity scores.

9. The method of claim 1, wherein, for each desired outcome, calculating opportunity scores includes calculating an importance score, which includes:

determining a top box score representative of the number of survey participants that rated the importance of the desired outcome with at least a predetermined rating;

calculating an average importance rating for the desired outcome; and

calculating a composite importance score by multiplying the top box score by the average importance rating.

10. The method of claim 1, wherein, for each desired outcome, calculating opportunity scores includes calculating an importance score, which includes:

determining a top box score representative of the number of survey participants that rated the importance of the desired outcome with at least a predetermined minimum rating;

calculating an average importance rating for the desired outcome; and

calculating a composite importance score by adding the top box score and the average importance rating.

11. A system for performing a market analysis, comprising:

a processor configured to;

collect survey data from survey participants, the survey data including;

evaluation data for desired outcomes, the desired outcomes consisting of attributes of one or more products or services, wherein the desired outcome evaluation data includes;

importance data indicative of the level of importance survey participants respectively attribute to the individual desired outcomes; and

satisfaction data indicative of the present level of satisfaction survey participants have with the ability of current products or services to achieve the individual desired outcomes; and

evaluation data for potential features that could be implemented to provide the desired outcomes, wherein the potential features evaluation data includes;

desirability data indicative of the affinity of survey participants for the individual potential features; and

process the collected survey data, by;

calculating, based on the importance data and the satisfaction data, opportunity scores for the individual desired outcomes, wherein the opportunity scores are indicative of the extent to which the desired outcomes are valued by the survey participants and presently unmet by current products or services; and

ranking the potential features based on the collected desirability data for the individual potential features and the calculated opportunity score for the individual desired outcomes.

12. The system of claim 11, wherein the potential features evaluation data includes:

inclusion data indicative of how survey participants would feel if the individual potential features were included in a product; and

exclusion data indicative of how survey participants would feel if the individual potential features were excluded from a product.

13. The system of claim 12, wherein, for each individual potential feature, the processor is further configured to:

calculate a satisfaction coefficient indicative of the inclusion data for the individual potential feature;

calculate a dissatisfaction coefficient indicative of the exclusion data for the individual potential feature; and

calculate a desirability coefficient based on the satisfaction coefficient and dissatisfaction coefficient for each respective potential feature.

14. The system of claim 13, wherein, for each potential feature, the satisfaction coefficient is indicative of the number of survey participants that rated the respective potential feature as attractive or one-dimensional;

wherein a rating of attractive means that a survey participant would like it if the respective potential feature were included on the product and would feel indifferent or feel that it was normal if the respective potential feature were not included on the product; and

wherein a rating of one-dimensional means that a survey participant would like it if the respective potential feature were included on the product and would dislike it if the respective potential feature were omitted from the product.

15. The system of claim 13, wherein, for each potential feature, the dissatisfaction coefficient is indicative of the number of survey participants that rated the respective potential feature as one-dimensional or expected;

wherein a rating of one-dimensional means that a survey participant would like it if the respective potential feature were included on the product and would dislike it if the respective potential feature were omitted from the product; and

wherein a rating of expected means that a survey participant expects that the product would normally include the respective potential feature.

16. The system of claim 13, wherein, for each potential feature, the desirability coefficient is calculated by subtracting the dissatisfaction coefficient from the satisfaction coefficient.

17. The system of claim 13, wherein, for each potential feature, the calculation used to calculate desirability coefficient weighs some responses of survey participants differently from others.

18. The system of claim 13, wherein the processor is configured to rank the potential features based on the collected desirability data and the calculated opportunity scores by determining a desirability ranking for each of the potential features according to the calculated desirability coefficients and determining an opportunity ranking for each of the desired outcomes according to the calculated opportunity scores.

19. The system of claim 11, wherein, for each desired outcome, calculating opportunity scores includes calculating an importance score, which includes:

determining a top box score representative of the number of survey participants that rated the importance of the respective desired outcome with at least a predetermined rating;

calculating an average importance rating for the respective desired outcome; and

calculating a composite score for the respective desired outcome by multiplying the top box score by the average importance rating.

20. The system of claim 11, wherein, for each desired outcome, calculating opportunity scores includes calculating an importance score, which includes:

determining a top box score representative of the number of survey participants that rated the importance of the respective desired outcome with at least a predetermined minimum rating;

calculating an average importance rating for the respective desired outcome; and

calculating a composite score for the respective desired outcome by adding the top box score and the average importance rating.