The Essential Guide to Growing Your Early-Stage SaaS Startup

A decade or so ago, starting a company was harder—but with fewer competitors, it made sense to go all-out on acquisition. Today, growing competition and market saturation have made switching products easier, and led to a decline in relative value of features and an increase in Customer Acquisition Cost (CAC). The scenarios couldn’t be more different, yet a lot of existing advice is still based on acquisition models from the past.

When you put too much focus on acquiring customers, you neglect two other strategic pillars: making more money per each (monetization) and keeping your customers around for a long time (retention). But to grow your business, improving monetization and retention has two to four times the impact of just sticking with acquisition:

Businesses that are primarily acquisition-focused invest their time, energy, and resources into bringing people on board, but later miss out on the opportunity to find out important data points such as what value proposition drove people to their product, and what kept them there.

The same logic applies to your startup: if you don’t have a clear sense of which customers you are getting, how can you know what to build, or how to price it?

Gathering customer data helps you understand the general makeup of your customers and quantify the value people derive from your product, so you can drive your pricing strategy accordingly.  

Surveys are a very effective and relatively fast way to obtain information, but you need to be smart and intentional about the questions you ask. Standard survey templates include demographic data points such as age, gender, location, etc., but behavioral insights are more useful for pricing purposes. You should be asking things such as:

• how do you use our product/service?
• what problem is our product/service solving for you?
• what feature(s) do you find most important?
• what would persuade you to use our product more often?
• what’s the one thing our product is missing?
  
  

If you need some additional inspiration, you can get started by taking a look at the questions we love asking our Hotjar users. After you send out a survey and collect all the answers, you can always follow-up with a few customers using the in-person interview formats we covered in the chapters on positioning and product-market fit.

If no-one has paid for your product yet, pricing it is hard: when we launched Hotjar, we simply picked a number that looked like a no-brainer and put little extra thought into it—which is why now, two years later and with over 180,000 websites using us (and all the customer data that comes with it), we are in the middle of refining and updating our pricing structure.

To come up with an initial price:

• start by looking around and checking your competitors to see if any useful patterns can be detected. Never replicate or copy their model: just try to get some information about what is going on in the space around your product, and use this input to start determining your own pricing.  
  
  
• Use the data you gathered from your customers (existing or potential) to quantify the amount of value they would get from your product, and pick a number that is around 10% of that.
  
  
• Build a landing page with different pricing options, and test to find out what happens when you have three pricing plans vs. five, when you double vs. triple your initial price, etc.

You can also get customers involved more explicitly by asking ranged survey questions to discover their ‘price sensitivity’. This model is known as the Price Sensitivity Meter (PSM) and is based on four questions that let you derive the different thresholds of your customers’ willingness to pay for your product/service.

1. At what price would you consider the product to be so expensive that you would not consider buying it? (Too expensive)
2. 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)
3. At what price would you consider the product starting to get expensive, so that it is not out of the question, but you would have to give some thought to buying it? (Expensive/High Side)
4. At what price would you consider the product to be a bargain—a great buy for the money? (Cheap/Good Value)
   
   

Once you have a sample of data in place that is highly representative of your whole customer population, plotting the answers onto a graph will help you visualize an optimal price band. This is a more advanced process, which Patrick Campbell explains in the video below (starts at 39:50):