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Bayesian Causal Analysis – an Effective Method For Measuring the Effectiveness of Marketing Campaigns
We use various criteria for qualifying consumers for mailings. Usually different campaigns compete for the same “best” customers. We can’t always use control groups. Sometimes, by mistake, a control group gets syndicated. In the end, we ask ourselves: which of these actions had a real positive effect and translated into important indicators for us. Doesn’t this sound like an everyday occurrence in many companies?
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Profit immediately or loyalty for years? Machine learning in short- and long-term customer value managementProfit immediately or loyalty for years?
One of the key challenges for marketers is striking a balance between short-term gains and building long-term customer value. Is it worth betting on quick sales campaigns, or is it better to invest in building lasting relationships? The future of marketing lies in advanced predictive models and automation that will allow companies to maximize the potential of each customer.
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Why am I not getting the expected benefits from using AI in marketing?
Interest in the subject of artificial intelligence (AI) is not waning. The public is most excited about the achievements of so-called generative AI. However, it is worth remembering that AI is also more mundane models that, play a role in many business processes. However, it happens that they do not bring the expected benefits and their performance is sometimes disappointing. What mistakes can contribute to such situations and what can be done to avoid them?
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How to get out of the RFM trap
(R)ecency, (F)requenct, (M)onetary value is a classic of marketing analysis. We all know it. Many of us use it. Each of us understands it. But do we really? RFM analysis undoubtedly has many advantages, which is why it has been in use for many years. However, it is also worth learning about its disadvantages and limitations. In order to use it properly and not try to solve problems with it that it cannot solve.
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