Comparing pricing strategies at Thinkific and Kajabi
Steven Forth is a Managing Partner at Ibbaka. See his Skill Profile on Ibbaka Talent.
Learning, supporting learning, supporting people who learn, and supporting people who help others learn … these are all part of my passion. I am constantly working to improve my understanding and skills in these areas. As a result, I do the odd Google search and someone has noticed. Over the past few months I have been getting a lot of ads for Thinkific and Kajabi across various feeds. Note that Ibbaka does not do work with either of these companies, though we know some of the people at Thinkific.
As I am always curious about pricing, I went to each companies pricing page to compare them. This seemed fair as (i) they seem to be advertising in response to the same triggers and (ii) Kajabi is quite explicit about comparing itself to Thinkific. Thinkific also plays this game.
(Setting up alternatives is good tactic in category creation - see Pricing and value for category creation.)
Kajabi compares itself to Thinkific
Thinkific compares itself to Kajabi
What can we learn by comparing these pricing pages?
Comparing pricing curves in tiered pricing
One of the first things I do when looking at tiered pricing (or Good Better Best pricing) is to look at the pricing metric and the pricing curve.
Kajabi has a simple three tier architecture and fences its offer on five different metrics:
Products (I believe these are courses)
Pipelines
Contacts
Active Members
Admin Users
That is a lot of fences. Too many perhaps.
Thinkific has a four tier architecture, but one of these is the free trial, so for our purposes this also a three-tier architecture. The fences are
Number of admins
Advanced functionality
These are already very different packaging strategies. But many buyers are going to start by looking at the prices, so that is what I am going to focus on here.
Let’s compare the tiered pricing curves for these two companies.
Thinkific is cheaper than Kajabi at the two lower tiers, and then higher at the top tier. Both companies have convex pricing curves (there are lots of companies with concave pricing curves, a subject for a different post). Thinkific’s curve is more convex than Kajabi’s.
What does this mean about each company’s beliefs about the market structure? (These are often implicit beliefs inside the company rather than formal hypotheses open to testing.)
Let’s explore this by looking at some different assumptions and the implications for revenue and market share. I am going to make lots of simplifying solutions here. To begin, let’s assume that there are 200 buyers and that Thinkific and Kajabi split the market (each aims at some market distribution). What will each companies revenues be? That depends on the distribution of buyers in the market. Here are four distributions to test. (Tier III is the entry tier, Tier I is the top tier.)
You may think that the first distribution is the most likely, that there will be more buyers for the cheapest offer. This is probably not true, at least not if these companies have done a good job on package design. The lowest tier is generally designed as an entry point and not where the majority of customers will end up. You should have a hypothesis about the distribution across tiers for your own company, and then be testing to see if your hypothesis is true.
Taking these different distributions, what are the comparative revenues for Thinkific and Kajabi?
Hmm, Kajabi comes out ahead of Thinkific in three of the distributions, but the distribution where Thinkific wins is the one that maximizes the category size by revenue (holding volume constant). On the other hand, I suspect that Distribution D is closer to the truth for both companies. And it is probable that the distribution is different for each company, so this is all a thought experiment, but one that shows how pricing curves and cross tier distributions interact to determine revenues.
Cross price elasticity and market share
Of course this is way too simplistic. One thing we could layer in is cross price elasticity.
Cross price elasticity: Cross price elasticity of demand refers to the percentage change in the quantity demanded of a given product due to the percentage change in the price of another "related" product.
Let’s drop in a simple cross-price elasticity assumption. More people will buy the cheaper offer. I am keeping this really simple, and a bit extreme, so I simply gave 3/4 of the market to the company with the lower price. In actual work, we have tools to explore different levels of cross price elasticity and do discreet choice modelling to test the actual levels in the market.
Adding in cross price elasticity has a big impact.
The danger in this approach though. It is to see pricing as a purely zero sum game. It is not. Changes in price elasticity and cross price elasticity can end up growing the market. Let’s look at the revenue impact on each company rather than the comparative impact. As the number of customers can also be important I have included that as well.
This is a very simplistic analysis. Cross price elasticity is generally not constant at different price levels. Hopefully this is enough of a taste to get you to start analyzing these questions for your own company.
Cross price elasticity is only one type of price elasticity though. When they hear ‘price elasticity’ most people are more likely to think of ‘price elasticity of demand. This is the idea that changes in price will lead to changes in overall demand.
Price elasticity of demand: Price elasticity of demand is the ratio of the percentage change in quantity demanded of a product to the percentage change in price.
It is possible that Thinkific’s lower entry points are bringing people into the market and helping to grow the overall category. By making it cheap to put learning online the companies in this category (which includes companies like Leanworlds, Teachable, Mightynetworks, etc.) these companies have created a new category that is helping millions of people share their knowledge. Eventually this will evolve into a multi-sided marketplace and community led growth models will come to compete with the current product led growth models. That will lead to another change in pricing strategy and market dynamics.
Of course this is just the beginning of the explorations one would make in serious pricing work. To begin one would test a much wider range of assumptions. One would also look at interactions. The interactions between price elasticity of demand and cross price elasticity are especially interesting to explore, but this quickly becomes a chaotic system. In this case one is generally looking for attractors and basins of stability to guide overall strategy rather than insight into precise price setting.
There are two main ways to get data to evaluate all these hypotheses. One can comb through existing transactional data looking for patterns generated by price changes and price variability or one can conduct a discrete choice study (these are sometimes referred to a conjoint analysis).
The other problem with this approach is that it assumes packaging is a constant. In most cases, when you begin to look at pricing you also look at packaging. Are there functionality clusters that one might want to add or subtract from each of these packages to explore different outcomes? This is where discrete choice studies can give important insights.
The real lesson here is that pricing is based on assumptions, sometimes explicit, more often implicit. These assumptions say a lot about what a company believes about its customers and markets. Calling out these assumptions and beginning to test them is the path to better pricing.
So, if you use a tiered pricing architecture, take five minutes to sketch the price curve for your tiers. Compare this to a few competitors. Look at the distribution of customers and revenues between tiers, your success with upsell from tier to tier, and the churn at each tier. This will give you some insight into the actual customer lifetime value (LTV) for a customer in each tier.
Then ask …
What has to be true for the current pricing curve to be a sensible curve? Do this for your own company and for competitors that have different price curves like Thinkific and Kajabi.
What would a change in cross price elasticity imply for your current strategy?
What would a change in price elasticity of demand imply for your current strategy?
