Lessons about Pricing For Growth in B2B SaaS
In our last post, we spoke about maximizing the customer experience as a north-star for B2B Growth. If you didn't read that one, I strongly encourage you to take a look here, because pricing builds on top of that.
Now let's talk about pricing and how we can maximize the customer experience, and as a result, maximize our own value capture in that area.
The main thing we try to achieve with pricing is to find the "Fair Exchange Rate" of value between the product we've created and the value that customers derive from it.
This is important for two reasons:
1) We don't want to undercharge. This is a pain because we don't want to lose out on valuable revenue. This may surprise you, but some segments of customers actually churn before purchase simply because they're skeptical about product quality because of what they believe it should cost.
2) On the other hand, overcharging may also turn customers off if they don't feel like they're getting their value's worth. We could close some deals by overcharging and earning a higher margin, but those customers won't last and we eventually we pay for it with our reputation.
Consequently, most founders are hesitant to touch pricing once they've established something and the question is why would they?
Well, pricing is actually our strongest growth lever.
Multiple research studies have shown that a 1% increase in pricing yields a higher ROI in revenue and profit compared to sales and retention. So optimizing our pricing actually gives us the highest bang for our buck.
This doesn't mean that the sky's the limit. Many categories in B2B SaaS actually have well-established budgets so we don't want to price ourselves out of that budget, but we can try to maximize our value capture as long as the customer is willing to pay for it and it's part of their expectation, which we'll expand on later.
Another reason, and this one is especially important for startups… is that it's good to keep some optionality with regards to pricing. When we start out in an established SaaS category, the best bet is usually to go for early adopters and innovators and these people are usually willing to pay a higher price as they prioritize outcomes & benefits over price competitiveness.
Lastly, pricing is one of those things that allows us to somewhat control and play with our growth rate. When we create a product, it has a certain cost to build. We set a price for that product and whatever is the difference between the price and cost-to-build is our margin. Our margin is our incentive to sell.
On the other hand, when the customer buys our product, they obtain a certain value from the product. The margin between the value they receive and the price they pay, becomes their incentive to buy our product.
The higher the incentive to buy – the more people typically buy and the higher our growth rate will be (in customer numbers). Conversely, the more we increase our price and our incentive to sell, the less people typically buy, but the higher our revenue per customer.
This phenomenon allows us to manipulate our growth or revenue. Depending on our stage and strategy, most founders will settle on some mixture of these, usually by mechanism of a demand yield curve, to find their optimal pricing point.
Nonetheless, it's important to be aware of these dynamics and that they exist. Typically, we recommend, especially early on to maximize the customer experience where a good benchmark is to offer far more value to the customer (for example 10x) than what they pay.
Talking with Customers
As the company grows up, we can use our process/system:
1) talk with users
2) collect data/insights
3) apply our data insights
Keep in mind, this will be a continuous process. There is no "right" result that will stay right forever.
We want to establish a practice of talking with customers continuously. And our goal here is to collect data across two dimensions specifically: what do customers value and how much are they willing to pay for that value.
Before we do that; we must first establish who our customers are exactly so that we know that we're talking to the right people and can bucket our insights accordingly.
Here are the rough steps to create such personas:
First, we want to create some segment our audience into alliterative buyer groups that are easily recognized by our teams. We then create a short description that includes demographic and behavioral data.
One could go much further into developing personas, but that's not the purpose of this post.
For SkaleUp, the result would look as follows:
"Startup Sarah" = She's 32, one of the founders and her company is between 11-50 employees, she's not sophisticated with her marketing yet and is looking to validate new channels, set up a tracking foundation and find sustainable growth to prepare for her Series A. She's the final decision maker.
"Growth George" = 29, He's the VP of marketing and the company is between 50-200 employees. He wants to scale growth (usually 2 or 3x) as fast as possible and wants experts to guide his team along the way. He's usually the decision maker, typically has a large allocated budget, but needs the founder to sign off.
We can now start collecting data from these customers. They don't need to have a specific status such as "those who are already using the product" or those who have been with the company for x years. You could talk with customers and learn about pricing during sales conversations, customer development interviews, customer success calls or whichever allows you to gather data at that time. The most important thing is that you are able to bucket them according to a validated persona group.
Collecting data & insights
When collecting data, it's important to go in with a single goal. We follow the framework introduced by Patrick Campbell from Profitwell (now part of Paddle) who specifically tries to understand the following questions:
- What features do customers specifically place the highest value on? And how do they derive value?
- What is the customer's willingness to pay for features/products?
We follow this method because the questions Patrick prioritizes are strongly aligned with our goal of maximizing the customer experience. Patrick's main recommendation is to use surveys that use a relative preference methodology. This is simply a way to determine which options or features are liked the most by comparing and ranking them against each other.The reason why Patrick uses them is because they're simple and easy to understand for customers, but still provide the depth and insight of data needed to make good decisions.
For the first part, his survey looks like this:
If you want to learn from Patrick directly: we recommend reading this blog post.
– Keep in mind, we're collecting data from the different personas we've established. We segment this data and the insights because not everything is valued equally by each persona. A security feature might be worth $100 to a startup, but the same feature might be worth $10,000 to an enterprise.
For the second part of the survey, he assesses overall price sensitivity to gauge how much customers are willing to pay and he uses the following questions:
- What price is so high you'd never buy it?
- What price is getting expensive, but you might still buy it?
- What price makes you think it's a great deal?
- What price is so low you'd worry about the quality?
Here you get super valuable insights that you can align directly with your customer experience.
Again, we strongly recommend giving your customers a "great deal" early on as soon as you've discovered this data from talking with customers.
What the result should look like
Applying our data & insights
It's a good practice to keep on talking with customers continuously and Campbell recommends sending short surveys with 3-5 questions every 3-5 weeks to maximize the amount of data you can collect.
He says you'll often be surprised by the results, because you might assume that the features that are used most often are also the ones that they find most important, but that's not always the case.
Now that we have gathered significant data and have much more certainty about what people want and need; we can use our insights to update our pricing.
Our recommendation is to first test your pricing with new cohorts and to validate your learnings. After that has been done, you can update your pricing page and establish it company wide.
And don't forget the larger objective: we want to maximize the customer experience as this is what leads to organic referrals, retention and expansion.
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SkaleUp is a boutique agency that works with fast-growing B2B SaaS startups to manage and implement growth. Subscribe to get our most recent posts in your inbox.
