Understanding and predicting your customers

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For any business it is important to identify who the customers are that generate the most revenue, understand why they continue to buy and what their behavior is when it comes to transacting with the brand.

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In this way, we can communicate with them to offer them loyalty benefits, continue working on their retention and create strategies to acquire customers with similar characteristics.

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This metric provides insight into business health and customer behavior, as it indicates how valuable a customer is to a business, based on their historical relationship with the brand. We can think of it as how much money a customer will bring in throughout their future relationship with a brand.

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To calculate this data, you need the transaction history of your customers, including the unique customer ID, date and amount of each transaction.

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Using this data, it will be possible to predict, with an acceptable level of accuracy (especially for frequent buyers), the following information:

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• Probability that the customer will make a new transaction within the defined period.
• Number of new transactions within this period
• Present value of these transactions.

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The long-term value of a company is strongly related to the CLV of its customer base (current and future).

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At Data4Sales we predict future customer value with more than 90% accuracy.

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By predicting the individual CLV of their customers, companies can:

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• Segment your customers based on how much value they will generate in the future.
• Forecast this value for a given period, including new customers to be acquired in the future.
• Define the ideal customer profile and prioritize the acquisition of new customers with this profile.
• Set maximum values for customer acquisition and retention costs according to their profile/segment.
• Prioritize products that generate higher CLV.
• Identify and prioritize the solution of customer experience issues that most affect CLV.

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A CLV-based segmentation model helps a company know which customers make sense to focus efforts and resources on based on what they are (or can be) worth to its business.

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With this segmentation model, marketers will be able to communicate with customers effectively, based on expected future results. The applicability of CLV goes beyond marketing and customer services.

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Story mode

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Paula is a fan of Arcor chocolates.

She stocks her candy fridge weekly so that she always has one on hand.

He places orders through Arcor's website every Sunday and receives them at home the next day.

Paula, given her number of orders, the amount she spends and the relationship she has had with the brand for the past year, has a high CLV.

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