Business Model Environment & The most critical hypotheses of a business model
This article is part of a case study “From zero to profitable business within 3 months”
In the last post, I described how I was working out my initial idea of an intelligent time tracking solution. Then I created a first business model with the Business Model Canvas.
Some of you might wonder why I haven’t taken care of the competition in the business model. Well, competition is not part of your business model. As Alexander Osterwalder describes, the competition is part of the business model environment. A business model itself can’t be seen isolated. But there are external factors such as trends, market forces, macroeconomic forces and industry forces (like competitors) that are influencing the business model.
🤜 Business Model Environment
For my case study, I have done research about the market in general, possible trends affecting my business model and also the industry forces or in particular the competitors.
Market
There were two factors that I wanted to find out: The market size and the market type.
There are three important key metrics that should be estimated for the market size:
- TAM: Total addressable market — How big is the universe?
- SAM: Serviceable available market — How many people of the TAM can I possibly reach with my products or services?
- SOM: Serviceable obtainable market — Who will be the most likely buyers?
As my solution probably will be an app, I estimated the TAM to all smartphone users worldwide which is around 2 billion. But this would only be the case if I could serve every smartphone user in every country and there would be no competition at all.
Consequently, the SAM will be much smaller. This was one more difficult to estimate since there are some factors affecting this size and I couldn’t find always good sources. First of all, I analysed the competition in this market. In 2015, Toggl had 1 million users. However, Toggl is not the only competitor. There are several more time-tracking apps such as RescueTime which also has hundreds of thousands of users. Now basically time tracking serves several uses cases, whether professional time tracking (in companies, agencies, freelancers, …) or personal time tracking. Regarding the personal time tracking, we should also consider neighbouring markets. For example, TodoIst is one of the most famous todo management apps and has around 10 million users. Some of them might be interested in adding the additional dimension of time to their todo management.
So all in all, I estimated the SAM to 10 million users or more worldwide. Obviously, already a couple of millions of users are already using time tracking applications, and the amount seems to grow.
Now, how many of those will be the most likely buyers for our product? 10%? 1%? 0,1%? If we have a look at the direct competitors such as RescueTime, SaveMyTime or Flip, they have mostly something between 100.000–500.000 users. So I would estimate our SOM also something between 100.000–500.000 users.
These estimations might be wrong or correct. However, they give us a very first really rough overview of the market size.
Additionally to the market size, I wanted to identify the market type. Basically, there are four market types:
- Existing market
- New market
- Re-segmentation of an existing market with a low-cost strategy
- Re-segmentation of existing market with a niche strategy
Clearly, there is already an existing market for time tracking/productivity apps. With our value propositions, I think we can distinguish from competitors, e. g. with new features, better UI & UX and so on. Ideally, we can even create a small niche within in the existing market with a focus on personal, visual time tracking.
Trends
I identified two key trends that
“The U.S. self-improvement market was worth $9.9 billion in 2016. It is forecast to post 5.6% average yearly gains from 2016 to 2022, when the market should be worth $13.2 billion.” (Source: marketresearch.com).
I have been into this personal development topic for around 6 years now and it really feels like more and more people aim to become a better version of themselves. Experts in this field such as Brian Tracy, Tim Ferris or Tony Robbins push and support this market. More and more books about this topic are coming out. Guess what top writers on Medium like Benjamin Hardy are writing about — How to become the best version of yourself, how to become productive, how to create a successful morning routine, and so on.
I couldn’t find a valuable source yet, but at least it feels to me that time is becoming more important for the people. Time is our most valuable asset, we want to spend time with our family and friends and save time. We often hear people complaining about having not enough time. A good indicator for this is also huge success of the book “The 4-Hour Workweek: Escape 9–5, Live Anywhere, and Join the New Rich” by Tim Ferris.
Competitors
As mentioned, there are many apps in this field available. For the competitor analysis, I focussed on the main competitors: Toggl, RescueTime, Timely, SaveMyTime, FocusMe and TodoIst.
For each one, I collected information such as pricing models, features, downloads, revenue and so on.
This allows me to better look for unique value propositions which serve as an important differentiator to my competitors.
🤨 Identifying the (riskiest) hypotheses
In the last post, I have described the various parts of the business model canvas. Now, the business model basically just consists of assumptions. I don’t know if these are my customers. I don’t know if they have these problems I have defined. I don’t know if my value propositions solve these problems well for these people. If they will accept them. If they will pay for them. These are assumptions, and I don’t know if they are true or false. I actually need to test them with experiments.
In the Grasshopper Herder Lean Startup Blog there is a great post explaining the difference between assumptions and hypotheses:
If we have an assumption, we can either accept the risk or convert it into a testable hypothesis. (Source: Grasshopper Herder Lean Startup Blog)
The first step we want to do is to identify the riskiest assumptions. If these are not true, our business model will not work. We should then convert them into testable hypotheses and create an experiment with the smallest amount of work that allows us to tell if this hypothesis is true or false.
To identify assumptions, we can have a look at the building blocks of the business model canvas, their relations and also the business model environment.
First of all, Ash Maurya identifies three stages of startups:
- Problem/Solution Fit: Do I have a problem worth solving?
- Product/Market Fit: Have I built something people want?
- Scale: How do I accelerate growth?
We are clearly in phase 1, where it’s important to get a fit between Customer, Problem and Solution: Our defined customer has the defined problem and accepts (or better: prefers) our defined solution and would pay for it.
Let’s have another look at the Business Model Canvas:
I listed these blocks and mapped them into the following table with two dimensions:
- The possibility that I am wrong with this assumption
- The Level of the impact if I am wrong
Now what we instantly can see is that the riskiest assumptions in the Desirability, Viability and Adaptability blocks. This is because this is a bootstrapped business so my dependencies on partners and resources are pretty unimportant and I can estimate pretty good what I can do and what I can’t do. The higher risks lie in the following questions: Do people actually want to receive my created value? Are they ready to pay for it? Can I successfully distinguish from my competitors?
Thus, I will focus on these assumptions. If we put these blocks into relations, we can basically form the following general assumptions:
- Cost Structure & Channels: The costs for the channels [ch1, ch2, ch3, …] are [c1, c2, c3, …].
- Cost Structure & Customer Relationship: The costs to maintain the customer relationships [cr1, cr2, cr3, …] are [c1, c2, c3, …].
- Cost Structure & Value Propositon: The costs to create the value propositions [v1, v2, v3, …] are [c1, c2, c3, …].
- Cost Structure & Revenue Streams: The revenue streams [r1, r2, r3, …] are higher than the cost structures [c1, c2, c3, …].
- Channel & Customer Relationship: We can establish the customer relationships [cr1, cr2, cr3, …] through the channels [ch1, ch2, ch3, …].
- Channel & Value Propositon & Customer Segments: We can deliver the value propositions [v1, v2, v3, …] through the channels [ch1, ch2, ch3, …] (to the customer segments [cs1, cs2, cs3, …]). We can reach the customer segments [cs1, cs2, cs3, …] through the channels [ch1, ch2, ch3, …] with our value propositions [v1, v2, v3, …].
- Customer Relationship & Customer Segment: We can build and maintain the customer relationships [cr1, cr2, cr3, …] with the customer segments [cs1, cs2, cs3, …].
- Customer Segments & Problems: The customer segments [cs1, cs2, cs3, …] have the problems [p1, p2, p3, …].
- Problem & Value Propositon: The value propositions [v1, v2, v3, …] solve the problems [p1, p2, p3, …] (aber auch in Kombination mit dem Kunden)
- Customer Segment & Value Propositon & Revenue Streams: The defined customer segments [c1, c2, c3, …] accept (or better: prefer) the value propositions [v1, v2, v3, …] and would pay [r1, r2, r3, …] for it.
- Business Model Environment: The value propositions [v1, v2, v3, …] are unique and distinguishing compared to the competitors [co1, co2, co3, …]. The customer segments [cs1, cs2, cs3, …] who are using products from the competitors [co1, co2, co3, …] are willing to switch to our product due to the value propositions [v1, v2, v3, …]
Now, these are probably not all. But it is a good starting point. This is an iterative process, when I encounter new hypotheses I will add them and validate.
Next, I have defined them concretely and created experiments how to test them. Let’s look at one example for the relationship between Customer Segments & Problems.
The customer segment [Developers] has the problems:
- Often getting distracted and thus lose focus
- Don’t know if they were productive today
- Don’t know where their time is going
- Want to get more productive by planning tasks at times when they can be accomplished the best
[Developers] refers to the corresponding customer segment represented by the Persona which I have created before.
The next step is to create a hypothesis out of this which we can test:
Each of the following problems is at least chosen 6 times in a sample of 10 [Developers]:
- Often getting distracted and thus lose focus
- Don’t know if they were productive today
- Don’t know where their time is going
- Want to get more productive by planning tasks at times when they can be accomplished the best
We could choose several different methods on how we could test this. However, at this stage, I want to focus on qualitative feedback. Thus, for many hypotheses, I’ll choose the experiment “Customer Interview” as an appropriate method for testing this hypothesis. However, it’s always important to set a success criterion. So in this case, when talking to 10 [Developers], they can choose multiple answers and I expect that at each problem is at least taken 6 times.
⏭️ Next steps
Now that I have identified my critical hypotheses, experiments with success criterions to test them, this is actually the next step. I will search people out of my defined customer segments and I will interview them.
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