Article | Release

What’s next: A re-energized interface, purpose-designed to enhance user experience

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To ensure that we stay one step ahead of your future needs, the Contactlab Marketing Cloud will soon be available through a new user interface. A tailor-made workplace that both complements the integration of a wealth of features and enables you to move from one module to another while using the same view. ...

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Article

Why is it important to calculate the CLV for each of your customers?

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“Will my existing customers keep on buying my brand in the future? How much will my best customers buy in the next 2 weeks? Which customers are at risk of churning? Who will be my top spender in the next six months?”  These are questions that many companies often ask themselves, to be able to forecast the future purchasing potential of their customers, understand the value they can generate, and plan marketing activities that will enhance the success of their business. ...

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Article

Contactlab’s Top 10 Product Developments of 2018

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2018 was an important year for Contactlab’s customer engagement platform. Here, we’ve tried to select 10 news articles that recall a year of compelling releases and considerable excitement, although they are not necessarily shown in order of importance. ...

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Article | Tutorial

Not all customers who stop buying are lost: Create a re-engagement campaign and bring them back on board!

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Brands regularly experience customers who, over time, become inactive and stop buying, often without a tangible reason. This can mean a significant loss of business for a company, especially if it applies to a substantial number of customers. People who came into contact with the brand, and might have bought regularly in the past, but have recently and gradually moved away ...

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Article

How does the RFM model work with real data?

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Here, we will apply the RFM model. An acronym for Recency, Frequency and Monetary, it is one of the easiest and most effective clustering models that can be applied to transactional data. We will apply the model to two different datasets to see how its behaviour chances ...

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