Setting Prices That Sell
Setting Prices That Sell
It’s not enough to have a great product, you also need the right price.
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This is a guest post by Alex Shartsis. Alex advises founders and CEOs on everything GTM–strategy, tactics, and not infrequently, pricing. He started an AI pricing startup in 2013, Perfect Price, and has interesting insights on how to get pricing right at a startup. He also ran corp dev for a public company–so brings a holistic view to growing your company with an eye towards what that means for your outcome. You can find him on LinkedIn here, or get his newsletter on early stage GTM (which is fantastic) here. Enjoy!
Product and price are critical to achieving product market fit. Without a product that solves customers' problems at a price they're willing to pay–that you can build a business around–no go to market strategy can succeed. While product market fit is well documented, the pricing component is often overlooked.
There are two dimensions where pricing fails. Pricing can be too high or low, or too simple or too complex. Most pricing mistakes trace back to these areas. Pricing is also stage specific, not static, and should evolve (generally becoming even higher and more complex) as you break markets into submarkets and move into new markets.
Articulating a pricing philosophy is crucial. You can easily recall Walmart, Amazon, Costco, or Apple’s pricing strategy. What is yours? Everyday low prices? Premium for premium products? Clearly defining your strategy, at least internally, is important.
Setting your price
Almost all early stage companies price too low. Low prices project inferior quality and create less margin to deliver your product/service or recycle into customer acquisition. As you raise later rounds, a low margin profile scares off investors. Customers are often less price sensitive than you think.
Beyond, the dynamic pricing tool for Airbnb hosts, initially charged a seemingly high 1% of all revenue where their dynamic pricing was used. But customers paid it, enabling extraordinarily high margins and growth without more capital. The company had a successful exit after raising less than $2 million in funding because it charged a high price.
Later stage companies tend to price too high, leaving room for new entrants undercutting them for price sensitive segments, like Harry's did to Gillette. Harry’s ended up with over 30% of Gillette’s volume thanks to a focus on affordability–still with great margins. Offering versions for all viable segments prevents new competitors from gaining a foothold as your market evolves. By trying to force everyone into buying more and more expensive products, without leaving some lower-priced options, Gillette left themselves open to competition.
Simplify for pricing–then make it complex
Early on, simple pricing enables learning and rapid growth. As you learn, added complexity can capture more value and generate leverage in enterprise sales negotiations, capturing more value where more value is created by your product. Many companies mistakenly invent sophisticated early pricing, overcomplicating the process before having data. This complexity makes selling slower, harder, and adds variables that make learning with few customers impossible.
Stay customer focused early. Build pricing for your ideal customer's use cases and budgets. Let other segments buy too if they wish. Observe why non-ideal customers purchase–would different packaging/pricing suit them better? Then evolve a sophisticated model based on how different segments find value.
Seat-based pricing is generally inadvisable as it doesn't align payment with value unless seats precisely reflect usage. It also gives customers control over what they pay. Rippling sells based on seats, which makes sense because as a platform for HR it generates value for each employee or contractor a company has. Hubspot primarily charges based on modules and the number of marketing contacts a company has–a better approximation of the value it creates.
As your dataset grows, you can make decisions about pricing based on customer behavior. With tens of millions in revenue, it can make sense to bring in pricing expertise–either consultants or a full time pricing team. Always avoid company-centric pricing that comes from your own needs and thinking, and fails to maintain the focus on the customer. Group features into packages matching how customers identify their needs.
Here are 3 questions you can ask your prospects in the product development stage:
What price seems reasonable?
What price is so inexpensive it would make you question if it works?
What price is so high, you would never consider paying it?
The too high or too low pitfall
The above questions help get at the key questions of what price is too high or too low? Many companies fail to ask these questions and instead make their own assumptions about their clients’ willingness to pay.
Products that appear to generate a lot of theoretical economic value are frequently overpriced. Thinking such as: our AI pricing tool will make you 20% more revenue. So, you should be fine paying me $1 million, because you have $50 million in revenue, and I’ll make you $5 million more. This fails on many areas. First, its likely there are other costs beyond the $1 million–training, behavior change, integrations, etc. – that reduce the benefit. Second, the benefit of more revenue is not actually profit. At a 20% margin, $1 million would actually capture all of the incremental value created by this project–maybe making it negative if the full cost was included. And finally there is risk to the client if it doesn’t work as promised.
There is less of a pattern to products that are underpriced–because almost all startups underprice their products at the beginning. The best way to avoid this is to ask the questions above early in the development process and not steer your prospects to an answer. Be genuinely curious. You might be surprised how valuable solving certain, specific problems is to customers.
For more on pricing and GTM strategy, see Alex’s newsletter Seed to Sequoia which is a great resource.