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  2. Customer analytics - Wikipedia

    en.wikipedia.org/wiki/Customer_analytics

    Customer analytics is a process by which data from customer behavior is used to help make key business decisions via market segmentation and predictive analytics. This information is used by businesses for direct marketing, site selection, and customer relationship management. Marketing provides services to satisfy customers.

  3. AIDA (marketing) - Wikipedia

    en.wikipedia.org/wiki/AIDA_(marketing)

    Action – The consumer forms a purchase intention, shops around, engages in trial or makes a purchase Some of the contemporary variants of the model replace attention with awareness . The common thread among all hierarchical models is that advertising operates as a stimulus (S) and the purchase decision is a response (R).

  4. RFM (market research) - Wikipedia

    en.wikipedia.org/wiki/RFM_(market_research)

    The maximum score represents the preferred behavior and a formula could be used to calculate the three scores for each customer. For example, a service-based business could use these calculations: Recency = 10 – the number of months that have passed since the customer last purchased [ 2 ]

  5. Behavioral analytics - Wikipedia

    en.wikipedia.org/wiki/Behavioral_analytics

    Behavioral analysis focuses on understanding how consumers act and why, enabling predictions about how they are likely to act in the future. It enables marketers to make the right offers to consumer segments at the right time. Behavioral analytics can be useful for authentication as for security purposes. [1]

  6. Customer insight - Wikipedia

    en.wikipedia.org/wiki/Customer_insight

    A customer insight, or consumer insight (CI), is an interpretation of trends in human behaviors which aims to increase the effectiveness of a product or service for the consumer, as well as increase sales for the financial benefit of those provisioning the product or service. [1] There is an overlap between market research and

  7. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    Predictive analytics can help underwrite these quantities by predicting the chances of illness, default, bankruptcy, etc. Predictive analytics can streamline the process of customer acquisition by predicting the future risk behavior of a customer using application level data. Predictive analytics in the form of credit scores have reduced the ...