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Pragmatic Data Science

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Armin

RFM Analysis as an Important Revenue Growth Analytics Capability – Part 2

RFM Analysis is a powerful tool for businesses seeking insights into customer behavior and segmenting them based on purchasing habits. By calculating RFM scores and creating segments, companies can identify valuable customer groups and target them with personalized sales and marketing campaigns. RFM Analysis is not limited to the retail industry or the marketing domain. It can be applied to most industries and functional domains that touch the customer, including pricing, supply chain, A/R, product management, and customer service. Additionally, RFM Analysis can benefit nonprofit organizations by understanding donor behavior to optimize fundraising initiatives.

In part 2 of our RFM Analysis article, we’ll dive deeper into how we can calculate RFM scores, visualize customer performance by RFM segment and discuss sales and marketing implications.

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Articles
Armin

An executive’s advice for data scientists (and leadership) – Part II.

In a previous article, I wrote about the three main structural challenges that data scientists and their organizations face when maximizing their career satisfaction and business impact (data ROI).

This edition of Revology Analytics Insider will dive deeper into the first impediment (“mismatch between data scientist aspirations and corporate reality”). We’ll decompose why it exists and make concrete recommendations to the data science community and company leaders on how to best address it.

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Have a Revenue Growth Analytics pain point, a question, or a content suggestion?

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