This is Kristen O'Brien, Managing Editor at NFX, and this is the founder list. Audible versions of essays from technology's most important leaders selected by the founder community. This is how to determine the optimal price for your web service. Written by Sean Ellis, co founder of Go Practice And Growth Hackers. Red by NFX. For the startups I Beller take to market, one of our most important projects is determining their optimal price.
Unlike companies in established categories with high unit costs, optimal pricing for a software startup mostly relates to maximizing revenue. An optimal price allows the startup to grow at the fastest possible rate by maximizing profitable investments in customer acquisition programs and or offering a free version to drive broad user adoption. Considering most software startups simply guess a price, determining your optimal price can become an enormous competitive advantage.
There are 3 key factors to consider when determining your optimal pricing. 1, price sensitivity. You wanna find the price that generates the highest yield per 1000 trials or visitors, DLs, etcetera. You can find this number by determining how many units you would sell at each price. For example, if you have a 10% conversion rate at both $8 a unit $10 a unit, then $10 is obviously the better price for you. But let's say at $20 a unit, demand drops to 8%.
Pete lower demand, yield is higher at $20, so it would be a better price than $10. I estimate max yield pricing first through surveys and then through experimentation at several price points. Around launch, your volume will be too low for a meaningful sample size, so be sure to launch with introductory pricing which should be at the low end of your expectations. Adjust the price when volume allows you to hone in on the optimal pricing. 2, marginal cost.
For web services, it's important to understand your cost per unit to avoid pricing at a loss. This marginal cost is essentially a floor on your pricing. If you have bandwidth and storage costs that are $5 a user per year, then your business would not be sustainable if you priced your service at $4 a user per year. For most downloadable software, there's no marginal cost per user beyond marketing costs. 3, growth strategy.
I generally prefer 1 of the following pricing strategies for innovative products. One is a market builder pricing strategy where the majority of your users are coming through your demand generation initiatives. Demand generation is expensive unless driven through vital tactics and therefore requires premium pricing to create a high allowable user acquisition cost.
An example of a company that took a market builder approach to grow the personal remote PC access category is go to my Pete, which combined premium pricing with aggressive radio demand generation. An alternative strategy is a market drafter pricing strategy. Freemium pricing is ideal for a market drafter. Essentially, As the market builder creates awareness for the category, the market rafter swoops in and offers a much better deal. SEM is a good place to focus for a market rafter.
This strategy only works when a market builder is aggressively investing to grow the category. I prefer the market draft or position when possible. In the long term, the market builder must focus on differentiation to justify its higher prices or reduced prices. Once the optimal price has been established there are many tactics that can be used to boost response rates.
These include setting the price a bit higher than the optimal level and then frequently discounting it, or using a decoy super premium version to make the version with the real price seem cheaper. My favorite pricing model for driving demand is freemium, combined with carefully research max yield pricing on the premium version of the product, then applying the response boosting tactics listed above. An insightful read on freemium pricing is Josh Kopelman's post the penny gap.
It is an exploration of the power of free in driving customer adoption and suggests that elasticity of demand is not linear. At the price of 0, demand sores. Dan Arilli also makes this point in his book predictably irrational. He concludes 0 is not just another discount. 0 is a different place. The difference between 2¢ and 1¢ is small, but the difference between 1¢ and 0 is huge. He supports this point through the following experiment.
He first offered a lint truffle for 15¢ and a Hershey kiss for 1¢. Participants who could only select 1 purchase the Flint truffle 73% of the time and the Hershey kiss only 27% of the time. When they were both discounted an additional penny making the Hershey kiss free, demand for the Hershey kiss shot up to 69% and demand for the Flint truffle dropped to 31%. There several other great pricing psychology nuggets and predictably irrational, I highly recommend reading it.
It goes well beyond the 3 basic pricing factors previously presented. Some useful points include a higher price not only positions your product as superior, people may actually have a better experience using the product, He presents a fascinating experiment that shows people got more relief from a $2.50 painkiller than a $0.10 painkiller. Even though they were both just vitamin C, He concludes the perception of value in medicine, soft drinks, drugstore cosmetics, or cars can become real value.
When we encounter from then on. He uses the example of black pearls. Initially, there was no demand for them, but when they were anchored to the finest gems in the world with premium pricing, demand shot up. Differentiation gives more flexibility to increase price. His example here was that Starbucks differentiated the coffee shop experience allowing them to more than double the price of a cup of coffee compared to Dunkin' Donuts. Finally, remember that technology prices tend to drop over time.
Keep this in mind when determining allowable acquisition cost based on a user's lifetime value. Lifetime value will probably be lower when considering future pricing pressure. It's better requires innovation that allows you to profitably offer the service at a lower cost than competitors.
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