Methods and apparatus to incorporate saturation effects into marketing mix models
First Claim
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1. A method comprising:
- calculating, by a processor, adstocked gross rating points associated with an advertising campaign during segments of a period of time, the adstocked gross rating points based on raw gross rating points corresponding to the advertising campaign, the raw gross rating points delivered during the segments of the period of time, the raw gross rating points defined by marketing mix input data stored in a marketing mix inputs database, the marketing mix input data including historical marketing data and historical sales data;
transforming, by the processor, the adstocked gross rating points into an effective reach realized during the segments of the period of time for the advertising campaign, the transformation based on determining a relationship indicative of a saturation effect on a reach of the advertising campaign that best fits the marketing mix input data, the effective reach realized indicative of a percentage of target audience members effectively exposed, during each segment, to an advertisement of the advertising campaign an average number of times sufficient to elicit a response to the advertisement, the effective exposure to the advertisement including actual exposure to the advertisement during each segment and a time lagged effect of exposure to the advertisement during previous segments;
generating, by the processor, a marketing mix model that automatically accounts for the saturation effect without manual adjustment, by one or more users, of a response curve associated with the advertising campaign, the accounting for the saturation effect based on a regression analysis of the effective reach realized during the segments of the period of time for the advertising campaign and the marketing mix input data retrieved from the marketing mix inputs database; and
reducing a computational burden on the processor by eliminating tuning of response curves after the generation of the marketing mix model and determining a best fitting saturation curve corresponding to the relationship to increase an accuracy of predictions of future sales associated with the advertising campaign and increase a confidence in plans for future marketing endeavors.
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Abstract
Methods and apparatus to incorporate saturation effects into marketing mix models are disclosed. A disclosed method includes calculating adstocked gross rating points associated with an advertising campaign during segments of a period of time. The adstocked gross rating points are based on raw gross rating points corresponding to the advertising campaign. The raw gross rating points are delivered during the segments of the period of time. The example method further includes calculating an effective reach realized during the segments of the period of time for the advertising campaign. The effective reach realized is based on the adstocked gross rating points.
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Citations
16 Claims
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1. A method comprising:
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calculating, by a processor, adstocked gross rating points associated with an advertising campaign during segments of a period of time, the adstocked gross rating points based on raw gross rating points corresponding to the advertising campaign, the raw gross rating points delivered during the segments of the period of time, the raw gross rating points defined by marketing mix input data stored in a marketing mix inputs database, the marketing mix input data including historical marketing data and historical sales data; transforming, by the processor, the adstocked gross rating points into an effective reach realized during the segments of the period of time for the advertising campaign, the transformation based on determining a relationship indicative of a saturation effect on a reach of the advertising campaign that best fits the marketing mix input data, the effective reach realized indicative of a percentage of target audience members effectively exposed, during each segment, to an advertisement of the advertising campaign an average number of times sufficient to elicit a response to the advertisement, the effective exposure to the advertisement including actual exposure to the advertisement during each segment and a time lagged effect of exposure to the advertisement during previous segments; generating, by the processor, a marketing mix model that automatically accounts for the saturation effect without manual adjustment, by one or more users, of a response curve associated with the advertising campaign, the accounting for the saturation effect based on a regression analysis of the effective reach realized during the segments of the period of time for the advertising campaign and the marketing mix input data retrieved from the marketing mix inputs database; and reducing a computational burden on the processor by eliminating tuning of response curves after the generation of the marketing mix model and determining a best fitting saturation curve corresponding to the relationship to increase an accuracy of predictions of future sales associated with the advertising campaign and increase a confidence in plans for future marketing endeavors. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 16)
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9. A tangible machine readable storage medium comprising instructions, which when executed by a processor, cause a machine to at least:
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calculate adstocked gross rating points associated with an advertising campaign during segments of a period of time, the adstocked gross rating points based on raw gross rating points corresponding to the advertising campaign, the raw gross rating points delivered during the segments of the period of time, the raw gross rating points defined by marketing mix input data stored in a marketing mix inputs database, the marketing mix input data including historical marketing data and historical sales data; transform the adstocked gross rating points into an effective reach realized during the segments of the period of time for the advertising campaign, the transformation based on determining a relationship indicative of a saturation effect on a reach of the advertising campaign that best fits the marketing mix input data, the effective reach realized indicative of a percentage of target audience members effectively exposed, during each segment, to an advertisement of the advertising campaign an average number of times sufficient to elicit a response to the advertisement, the effective exposure to the advertisement including actual exposure to the advertisement during each segment and a time lagged effect of exposure to the advertisement during previous segments; generate a marketing mix model that automatically accounts for the saturation effect without manual adjustment, by one or more users, of a response curve associated with the marketing mix model, the accounting for the saturation effect based on a regression analysis of the effective reach realized during the segments of the period of time for the advertising campaign and the marketing mix input data retrieved from the marketing mix inputs database; and reduce a computational burden on the machine by eliminating tuning of response curves after the generation of the marketing mix model and determining a best fitting saturation curve corresponding to the relationship to be saved for use as an initial estimate in determining a second best fitting saturation curve for a second advertising campaign thereby increasing a computational efficiency for the determination of the second best fitting saturation curve. - View Dependent Claims (10, 11, 12, 13, 14, 15)
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Specification