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Increasing Customer Revenue: Assumptions vs. Reality

Intuition is a great marketing tool, as long as it’s balanced with a good data-based reality check. Here are two examples of counter-intuitive data insights that can impact your marketing strategy

As marketers, we rely heavily on our intuition. We usually have a pretty good gut feeling regarding the decisions we make daily: which segments to target, what offers to make, where our low hanging fruit is and where we should drill down to unlock value. But, as in every other walk of life, there are times when our assumptions and intuition trick us into making wrong decisions. When it comes to matters of the heart there’s not much we can do (except perhaps heed the advice of our friends), but when it comes to matters of marketing, data is the reality check we need. This is the story of how we used data to refute two common marketing assumptions, helping our clients hone their marketing strategy to increase their retention marketing ROI.

More is Better – But More of What?

As marketers, our goal is to increase revenue. We want our customers to buy more and spend more. And we all share the assumption that the higher our customers’ order value, the more revenue we will generate. We are naturally inclined to push our customers to increase their order value. For example, if we segment our customers according to order value, we’ll strive to push customers from the under-$50 segment to the $50-$100 segment.

But is that the right strategy for every customer segment? Could pushing all customers in the same direction actually hurt the total revenue that we are seeing from our customers? Should we always up-sell or cross-sell, or perhaps there are other, more subtle, but also more powerful, tactics we should use? The answer lies in the predicted future value of the different customer segments, which can help to determine the driving force behind that segment.

Let’s look at this example from a large online retailer: Customers who make purchases of less than $100 per order have double the future value of customers who make purchases of only under $50 or only $50-$100 (specifically, $79 average net revenue per customer over the next year, compared to $37 and $48, respectively).

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This is a striking and unexpected result, which is due to the increased frequency of purchases for customers who have an all-around purchase values up to $100. The data reveals that the deciding factor for future value is a combination of average order value and order frequency.

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According to this data, it’s clear that those customers who only make purchases of less than $50 should be incentivized to increase their purchase amount. Those customers with purchases of only $50-$100 should actually – and counter-intuitively – be encouraged to make purchases of $50 or less, thus encouraging them to follow the purchasing behavior of customers with similar behavioral patterns. The expected result will be an increase in purchasing frequency, and thus an increase in future value.

If we jump to the next level, those customers who are purchasing from both buckets – $0-$50 and $50-$100 – should be pushed to the next cluster in terms of future value. This cluster – “All Around Mid Order Value” – is made up of customers with purchases of $0-$50, $50-$100 and also $100-$200. This cluster represents the group with the highest future value, at $100 average net revenue per customer over the next year. This is even higher than customers who mainly purchase at over $200 per order! Again, this apparent inconsistency is due to order frequency.

The Return of the Return

Another enlightening data revelation comes from the area of item returns and order cancellations. We intuitively assume that customers who make a lot of returns and/or cancellations are unsatisfied with the brand and therefore have a low lifetime value.

The data, however, reveals a completely different story. Below are two examples from two different retailers of customer segments with the highest rate of returns/cancellations – and they actually have the highest future value! Counter to common assumptions, the data here shows that these customers are not unsatisfied with the brand, but rather are deeply involved with it and have had enough satisfying experiences of returns or cancellations to trust the brand with their business.

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This is an indication that companies should strive to offer a very easy and efficient return policy that strengthens customer loyalty to the brand. For marketers, this is a great campaign that doesn’t require any promotions or offers but only brings awareness to how much the brand cares about customer satisfaction.

Conclusion

When in doubt, check the data. On second thought, let me rephrase that: check the data, even when not in doubt. At times, there are things we don’t know that we don’t know and the data has the power to tell us. If you get into the habit of setting aside time to explore your data, you’re sure to find insights that will influence your best practices and enhance your performance. It’s right there at the tip of your fingers.

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