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One thing business analysts
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sometimes rip up on are the assumptions they make about the data.
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Let's go back to our WeCart company.
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Say you're the business analysts,
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calculating the LTV across the years,
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and you're counting the number of transactions by converted customers during each year.
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For example, you want to know the LTV for a customer acquired in 2016.
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You want to include all the transactions the customer had even those in 2017.
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LTV takes into account future uncertainty.
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It is a good estimate about the future actions of the customer.
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Another thing to keep in mind is the actual value of the product.
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Most high value products,
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such as a car or a house,
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won't have customers coming back and buying it again and again.
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For example, it's very likely you have bought cars from different dealerships.
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So, for the dealership,
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it is more important to focus on
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the individual customer value rather than the lifetime value.
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The value you provide each dealership is restricted to
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that single purchase you made because you never visit them again.
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Compare that to smaller orders at Amazon.
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There, the lifetime value will make sense as
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you're likely to come back and make orders several times.
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Calculating lifetime value matters in this case.
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