Impact Pricing Blog

Pricing Metrics and Market Segments … or Not

AAAACHH!  Twice this week I ran into the same situation. Two different companies are creating subscription products and are trying to figure out how to price them. They correctly started looking for a pricing metric, but because they wouldn’t segment their market, the pricing metric they were leaning toward was ineffective at capturing value. It was essentially a cost plus metric.

Market Segment

Let’s just use one of them, and anonymize it of course. This company, call them company X, makes analytical engine that crunches massive amounts of a specific data type and returns results that are often incredibly valuable to their customers. They served several different market segments, each trying to solve a different problem. The value of company X’s results depend on the market segment, of course.

Now the painful part. Company X was pricing their subscription based on the amount of storage used by the customer. Really?


Strategies (Value)

The one good thing I can think of about this strategy is that data storage is somewhat correlated with the amount of value customers receive.  Customers with huge databases are doing more analytics, receiving more value and paying higher prices. That works. Many things are wrong with this strategy. It doesn’t capture the value from the different market segments, it doesn’t incentivize usage, it doesn’t feel to the buyer that just because they store more data they should pay more. It isn’t really correlated with outcomes.  If you think about it, this is essentially a cost plus strategy. They were thinking, “Since we have to pay for the storage, let’s make sure we get paid for it.”

The company and I started talking about the value to the customers.  How the different segments receive dramatically different amounts of value. How the information each segment needed was different. I suggested creating packages around the types of analytics they perform so they could capture the right amount of value from each segment. They said something like, “That’s a lot of work. Amazon AWS doesn’t do it that way.”

AHA!  That’s it.  This company (and the other one) was looking to huge companies serving horizontal markets as their examples.
Here’s the difference. When Amazon AWS sets prices, it does so for everybody, probably thousands of different market segments.  Some of those companies receive a ton more value than others, but because of their horizontal market, they have to choose a relatively generic attribute that every segment uses, and charge based on that.  They do not capture as much value from each segment as they could.



Amazon Case

If you’re not Amazon and you can identify 3 or 4 market segments, you can create different packages and prices for each segment.  You can capture more value.  Sure, it’s a little bit more work, but boy is it worth it.Let’s say you serve many segments.  Here’s a thought.  Find your generic “charge by the storage” equivalent that works across segments.  Then, identify your best segment.  This is probably the one with the highest willingness to pay or the largest one.  Create a set of packages and prices specifically for that segment.LinkedIn is a great example of this.  LinkedIn serves many different market segments, but they have identified 4: recruiters, job seekers, salespeople and everyone else.  The everyone else category, they call it Premium, is the generic group.  Some day they may split another segment out.  Some day they may have a segment for Pricers.  (Not likely).The point is, your pricing metrics should be based around the value your customers receive.  If you can identify vertical markets and package and price for each vertical, you will capture a ton more of that value.  Of course that means a ton more profit.
Tags: pricing data

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