The secret to start-up pricing: A playbook for writing your Pricing Discovery Survey
Stop guessing and start formulating a real pricing strategy with these four steps.
Earlier this year I had my eyes opened to the power of pricing strategies. In a workshop with Patrick Campbell (from Price Intelligently) I learnt that we were part of the ~80% of SaaS start-ups that blindly chose per-user pricing because… well just because that’s what everyone else was doing.
Pricing strategy always seemed like a daunting black hole to dive into and I never knew where to start. We’d feebly attempted to iterate on our pricing at Everproof in the past, but in hindsight we were just putting our finger in the air and doing what felt right.
The Price Intelligently workshop made me realize that there was a process that could be followed here, and I’m a process geek. I set about putting together our first Pricing Discovery Survey and took it out to current and prospective customers. I was shocked by how well it worked. People were open to telling me exactly the information I needed to take the guess work out of pricing.
Since then, I’ve been sharing these steps with a number of other founders in a shitty Word Doc, so I thought it was time to put it into an article so others could benefit from this to.
Four Steps to Formulating Your Pricing Discovery Survey
Start with a text editor open
Step 1: Establishing Your Key Value Metric
Your key value metric is what defines and separates the packages in your pricing model. When a customer arrives on your pricing page, this is what they look at to go “ah-huh, I’m in the Growth package”. It could be users, transactions, storage size, teams, emails, projects etc.
A key value metric must be three things:
- Easy to understand and calculate
- Align with your customer’s needs
- Grow with your customer
To establish your key metric, first consider what value your product is creating for customers. Then think about all the various metrics you could shape pricing around.
Your key metric should satisfy one fundamental question: Does your customer know how many [your metric] they need? If they don’t know this, or have to defer to someone internally to find more information, then it’s not the right metric.
So, let’s jot down the first three questions in your Pricing Discovery Survey:
1. Which of these metrics do you have most clarity on?
[list your various metrics here]
2. How many [key value metric selected] do you [have/undertake] each [month/year]?
3. Which of the other metrics I outlined in the first question do you know the number for at your organization?
The third question is useful to accrue data on in the event that you want to change your key metric down the track or experiment with dual value metric strategies.
Note: You can also ask the first question through relative preference tests which could assist with dual value metric pricing strategies (where you drive the customers up pricing packages through one of two metrics) but we’ll keep it simple for this first article. Let me know in the comments if you want me to write a more advanced version on this step.
Step 2: Establishing Quantified Buyer Personas
Next, you’ll want to establish your Quantified Buyer Personas so that you know:
- How to identify your highest-value customers so that you can position your offering effectively;
- What the most valued features for the different subsets of customers;
- What is each type of customer willing to pay; and
- If the unit economics of these customers are viable.
The goal is to come out with 3–5 identifiable personas. Establishing buyer personas could be its own entire article, but here’s a simple way to work it into your Pricing Discovery Survey.
First, ask the following questions to gather key demographic information:
4. What industry are you in?
5. What is the size of your company?
6. What is your role within the company? What titles are given to your equivalents in on other organizations?
Take note of how they answer the question about the size of their company — do they go to headcount, revenue or some other descriptor that could give an indication of how that industry breaks down their own segments.
Then you want to map their most and least preferred feature using a relative preference test.
List all your key features in a table with a description under each feature title. Then have a column for Least Preferred and Most Preferred. Ask your customer to select one (and only one) in each column. Don’t ask them to rank them or accept multiple Most Preferred, this will make sense when we aggregate the data.
Then look for commonalities in the answers you’ve received in this section, and your buyer personas will start to emerge.
Do your larger sized customers consistently prefer integration? Do your medium-sized customers really want SSO? These insights can also be used to strategically drive customers up a pricing package by putting a highly desired feature one package higher than where their key value metric puts them. See extract below for an example from Price Intelligently on synthesizing this data:
Step 3: Establishing Willingness to Pay
This section is where it gets really interesting. You will start to uncover what your customers would actually pay for your product. To do this, we ask for four different numbers, as people aren’t good at thinking about specific price points. This is called the Van Westendorp’s Price Sensitivity Meter.
Write down the following questions:
7. At what price would you consider the product to be so expensive that you would not consider buying it? (Too expensive)
8. At what price would you consider the product to be priced so low that you would feel the quality couldn’t be very good? (Too cheap)
9. At what price would you consider the product starting to get expensive, so that it is not out of the question, but would have to give some thought to buying it? (Expensive/High Side)
10. At what price would you consider the product to be a bargain — a great buy for the money? (Cheap/Good value)
By aggregating this data relative to the buyer personas identified above, you can start to understand the willingness to pay for each subset of customers. You can see what price point will capture the largest subset of customers — see Price Intelligently extracts below:
You can also determine if a higher price point may lose you a bit of the market, but return greater revenues for your company. In the above graph, sliding from $200 to $400 per month resulted in a greater net outcome despite having less market share:
Note: Some customers may feel uncomfortable giving you this information in person. Feel free to send them the four questions above in an email straight after the meeting. Ask that they complete it that day so that you don’t have an incomplete data set as these figures are critical to your outcome.
Step 4: Calculating Customer Acquisition Costs
Finally, use this interview as an opportunity to try and glean as much data as you can about your customer’s buying habits so that you can start to calculate an indicative customer acquisition costs and learn how to engage with similar customers. Here are a few questions you might find helpful to ask:
11. What is a similar product you’ve purchased recently?
12. How did you find or come across that product? (email, google search, cold call, word of mouth, conference etc.)
13. How many touch points did you have with a representative of that company before you became a customer?
14. Roughly how much time did you spend speaking with them through this process?
First, I suggest formulating a Pricing Committee and get a meeting in the calendar once a month to ensure that this becomes ingrained in your company’s behavior. This should involve the founders and ideally someone from sales and product to ensure any decisions that are made can be reflected quickly across the whole company.
Then, get out there and start getting your answers! I would encourage you to start with in-person meetings as it will help refine your questions further. You’ll quickly see if your customers are struggling with understanding some of the languages and they’ll often have little gems which they speak out aloud which you could miss if you’re not in the room with them.
Don’t be afraid to iterate on the order of questions or add/remove some. If you find a better structure, please let me know as we are always looking to improve our processes at Everproof.
Ensure all responses are documented and once you have your first 10–20 responses, have your first Pricing Committee meeting to analyse the results.
I’m the CEO and Co-founder of Everproof. I’m a process geek and have been documenting plenty of our processes like this in Word Docs. If you found this article valuable, have suggested improvements, or would like to see other processes we have established at Everproof, please leave a clap or a comment below letting me know what you want me to share with you next. Also check out my co-founder’s articles on customer discovery if you want to dive deeper into product and UX:
Think your startup idea will work? Run a premortem for the best chance at success
Challenge your assumptions before you build anything, otherwise you’ll burn money fast.
Lastly, a big thank you to PC and the team at Price Intelligently for opening my eyes to the world of pricing! Head to their website for more info on their services and workshops.