Great Guidance on Pricing from Zoosk CEO

December 29, 2011
There is a way to think about that. The model that I have in mind is a graph where the X-axis is the price and the Y-axis is the revenue. At a price point of zero, you make zero money. A ridiculous price or a very high price point, again you make zero money because no one buys your product. This curve starts from zero and then goes up and then comes down. There is a peak, the revenue maximizing price point. Theoretically it is there whether you know it or not. It depends on your product and your demographics, etc., but if everything else is fixed, there is a revenue-maximizing price point. If you actually know the revenue-maximizing price point, you can do say, okay, that’s the top of the peak. However, I prefer to make 10 percent less money but have 20 percent more customers. You want to stay a little bit to the left side of the peak. It is around 90 percent of the revenue maximization point. The way I think about it is a little bit different. I don’t look at it as a continuous thing. I would try to pinpoint the revenue-maximizing price point and then find the nearest round number right before. If my revenue maximizing price point is somewhere between $20 and $30, I would shoot for $19.95. I can tell you that there is at least 20 to 30 percent additional profit you can get by optimizing your product packaging and your product pricing. If you can figure it out, you can go from a company
Shah,Tarang; Shah,Sheetal (2011-11-16). Venture Capitalists at Work: How VCs Identify and Build Billion-Dollar Successes (p. 64). Apress. Kindle Edition.

A lot of people have asked me about how to determine optimal pricing for a product or service.  This morning I read the following statement from Alex Mehr, the founder/CEO of Zoosk, and thought it was the best explanation I’d ever seen.  It’s a great articulation of the theory behind the process I’ve used for years.

Alex Mehr, the founder/CEO of Zoosk on pricing: “There is a way to think about that. The model that I have in mind is a graph where the X-axis is the price and the Y-axis is the revenue. At a price point of zero, you make zero money. A ridiculous price or a very high price point, again you make zero money because no one buys your product. This curve starts from zero and then goes up and then comes down. There is a peak, the revenue maximizing price point. Theoretically it is there whether you know it or not. It depends on your product and your demographics, etc., but if everything else is fixed, there is a revenue-maximizing price point. If you actually know the revenue-maximizing price point, you can do say, okay, that’s the top of the peak.

However, I prefer to make 10 percent less money but have 20 percent more customers. You want to stay a little bit to the left side of the peak. It is around 90 percent of the revenue maximization point. The way I think about it is a little bit different. I don’t look at it as a continuous thing.

I would try to pinpoint the revenue-maximizing price point and then find the nearest round number right before. If my revenue maximizing price point is somewhere between $20 and $30, I would shoot for $19.95. I can tell you that there is at least 20 to 30 percent additional profit you can get by optimizing your product packaging and your product pricing. If you can figure it out, you can go from a company.”

Shah,Tarang; Shah,Sheetal (2011-11-16). Venture Capitalists at Work: How VCs Identify and Build Billion-Dollar Successes (p. 64). Apress. Kindle Edition.

4 thoughts on “Great Guidance on Pricing from Zoosk CEO”

  1. I love the explanation but it hides customer lifetime value.

    Assuming you factually know the “peak revenue maximizing point” there are only two reasons you might want to be to the left of it.

    1) You’re battling against a competitor and you think stealing some of their customers with a lower price point will impact their unit economics *more* than your unit economics.

    2) You are expecting repeat business. If you have any sort of retention rate, then you don’t want to optimize against revenue, but rather customer lifetime value.

    I’d be really interested in understanding how best to determine the demand curve to begin with. (If you’re a startup, you might not have a lot of data to go on, especially if it’s B2B.)

    I’d also be really interested in a better way to conceptualize and maximize the equation with lifetime customer value. The math is straightforward, but optimizing it is tricky without going excel mad.

    A lot of startups seem to just opt for freemium (way too far to the left of the peak revenue point) in the vain hope that CLV will pay off. A cleaner way to approach this might save a lot of people some pain.

  2. This exercise assumes we have visibility on the impact of price changes on revenue. While we can observe churn as prices are increased (assuming you have a user base already) there is much more to pricing strategy. If you sell a SaaS product at $100/month everything you do from positioning to acquisition channels to customer service is completely different than if you were selling the same product for $10.

    This exercise just does not cut it for me

  3. This exercise assumes we have visibility on the impact of price changes on revenue. While we can observe churn as prices are increased (assuming you have a user base already) there is much more to pricing strategy. If you sell a SaaS product at $100/month everything you do from positioning to acquisition channels to customer service is completely different than if you were selling the same product for $10.

    This exercise just does not cut it for me

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