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What is the ultimate size of your total addressable market?

Your CRM is always a fraction of the entire population. That’s rather obvious.

When you look at the size of your CRM relative to the population of discrete areas you will find a wide degree and large standard deviation.  It’s better explained by example.  I’ve seen one brand that had 10% market share within a small radius of its stores, which is a rather footprint. But once outside of that radius the number drops to near zero. That implies no e-commerce. 

When Executives attempted to put stores in different locations to fill in the gaps, marginal sales did not support the growth.  When they looked at those populations, demographics looked right on. But something was rather odd about where they placed the stores. The stores were born in the Midwest, moved towards the Northeast and then they started to move west.

Turns out for this well-known retailer, that was a very bad decision. As they expanded the trusted data that worked really well on the East coast, woefully failed with the company expanding West.

Why is that the case?

Simply put the density of traditional demographic base data and traditional digital data failed them.  It’s a classic case of significant differences in traits where are the drivers of nonconsumption in the West.

The image indicates there’s some limit to the size of the list which is less than the entire population. That limit should include not just likely buyers but approximate itself to actual buyers.  To compound the problem, Publishers are incentivized in the wrong direction.

The solution is/was to reconfigure what you’re selling and how you’re selling to match the underserved needs of a different market. it’s a hard lesson to learn. You have to think of your market like an onion. In the very center is a sphere of customers that are going to understand you.  As you grow and expand you’re further away from the core. At some point, you might morph into something completely different like an outer shell.

Ultimately no matter what technology you’re using, you’re managing cost volume and profit for each layer or segment of customer types. You have trade-offs. Balancing volume with profitability is key and the way to do this best is by creating segments based on traits aligned with other data sets. An example: if you’re reaching the techie and early adopters, the volume is very small, cost is small and profits are large on a per-customer basis. As you reach out further into different segments based on traits you have to change the message to bring in different customers for different reasons. If you ignore this, you start to average customer lifetime value in a very dangerous way.  Your marginal cost of sales using the same message skyrockets as you try to force-feed something that’s not working for people with very different traits that don’t care. When you do this successfully you can increase volume successfully while controlling cost and managing profit. it’s going to take some discipline to understand the changes in traits by segment. creating false segments creates muted measurement and get you into trouble every time.

If you focus on the unmet needs of the customers through the lens of the customer, their traits and desires, you have a Fighting Chance to keep growing with a core product adjusting along the way.

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