Startups that shortcut the initial testing phase risk premature scaling
For many founders, trying to make sense of the impact of Covid on their companies has been a daunting and unexpected task. The earthquake has hit and the foundations of the business have been tested – in some cases to destruction.
As a result, many early stage companies are in the process of some form of pivot; the cornerstones of the old business model - the target customer segment and the value proposition – look vulnerable. There is a desperate need to quickly rebuild.
The reality is that developing and proving new business models takes time. Early stage companies rarely process all the insights required to pivot quickly. But, with cash flow pressures building, there is a temptation to sprint ahead in the execution of new ideas before they have been properly tested. The spectre of premature scaling - traditionally one of the biggest startup killers - then raises its ugly head.
Often, the biggest challenge is letting go of current beliefs. In studies into why so many well-intentioned entrepreneurs fail, one reason that is often cited relates to the product itself: In Nathan Furr’s book ‘Nail It then Scale It’, he says:
“Although passion, determination, and vision are important, they can also be extremely dangerous. For entrepreneurs who have risked their time, reputation, and cash, passion can quickly become dogmatism, determination can become commitment to a failing course of action, and vision can lead one down a dead-end road. All too often, entrepreneurs fall in love with their product or technology, they ignore negative feedback from customers, and they spend years building a product based on a vision that no one else shares.”
As we help facilitate the pivot process for a number of businesses, we’re not only providing a framework for constructing and testing the new business model, but we’re bringing an objective and watchful eye. Our goal is to help channel the passion, determination and vision into a scalable business proposition that is highly fundable.
In such a short article we can’t really do justice to all the aspects of building out a new business model. Instead, our aim is to share some initial observations on new business model testing in the hope that this may assist others as they start to evaluate their own changes.
First, what is a ‘business model’?
In their seminal book, Business Model Generation, Alexander Osterwalder and Yves Pigneur state: “A business model describes the rationale of how an organisation creates, delivers and captures value.”
This definition goes beyond just describing the ‘transactional’ aspects of the model i.e. SaaS, eCommerce, subscription, and so on. It incorporates ALL the essential elements that must be present to enable the business to succeed as it creates, delivers and captures value.
In the Tech industry, there has been a dawning realisation over recent years that the business model is the competitive differentiator – especially when a strategic inflection point is occurring. Those who have read Only the Paranoid Survive by former Intel CEO Andy Grove, will recall the power of inflection points and how they can be exploited. Competing on technology, product or price alone creates a high vulnerability to disruption.
Business model innovation, rather than technology innovation or sustaining innovation, has now become the key to building resilience in high growth companies. As we have observed many times through our earlier work, having a framework for business model development also accelerates investment readiness through each stage of the startup to scaleup journey.
The use of easily digestible, visual models - such as the Business Model Canvas - is particularly important. This ensures that during this stressful and uncertain time, nothing is forgotten, and the entire leadership team is synchronised on the mission.
Testing the new business model
The essential first step is to state the business model hypothesis: Who has the problem? How big could the market be? What will our value proposition be? What channels will we use? What partners will we need? and so on.
The goal is to convert these assumptions into facts before:
(i) we declare that the basic problem/solution hypothesis is likely to be investable and,
(ii) following customer validation, that product/market fit has been achieved, and we are ready to scale.
Here we focus on the first of these, testing the problem/solution hypothesis.
Even in normal times, early business model testing can be challenging. It is an iterative process that starts with the lowest cost experiments and gradually gathers information from the target market that either proves or disproves the hypothesis.
Talking to customers regularly – especially potential early adopters – is paramount. We want real feedback and lots of it, not just a small number of anecdotal data points or information from industry reports. Acting on insufficient or dubious evidence can easily lead to false positives. In the Covid era, this has become much more problematic - face to face meetings are often needed to gather evidence and reveal the deepest insights. This is particularly important for offline businesses.
Without a rigorous approach to testing, the temptation is to jump ahead too quickly, assume Product/Market fit - but then crash land as costs rise whilst commercial traction remains elusive (premature scaling). So, it is imperative that we start with Problem/Solution testing, and nail this first.
The concept of ‘being investable’, as we mentioned above, is crucial. Unless you are self-funding your company it is highly likely that you will require external funding at some point. Any external investor will first need to be convinced that:
You will therefore need to design some simple experiments. As Steve Blank says in The Startup Owner’s Manual, “Regardless of whether it’s a physical or web/mobile product, …experiments are short, simple, objective pass/fail tests. You’re looking for a strong signal in the noise. The pass/fail tests give you a ‘good enough’ signal to proceed.”
The process is to first create the business model hypothesis (write it down, ideally using a business model canvas), design some experiments to test your assumptions, and then gather insights that help hone your hypothesis. It is an iterative process shown as follows:
The most critical assumptions to test first relate to your target Customer Segment (i.e. the ‘problem’, who has it, and how big it is) and your Value Proposition (i.e. the solution you will create). You need to identify a sample set of customers, engage with them, then capture and measure their reaction. Above all you want to know, have I found some real monetizable pain?
Let’s look at two commonly used methods for initial Problem/Solution testing:
The Smoke Test
A ‘smoke test’ is the offer of a product that doesn't exist yet. Its particularly useful in B2C settings. Creative entrepreneurs excel at developing such tests and they should be fast and cheap. You don’t want to waste too much time and too many resources only to discover you are wrong.
A simple smoke test is to preview a product or service by writing an article and placing it in a suitable industry publication. The objective is to gauge initial reaction and hopefully gain some insight from your target audience: If you are inundated with enquiries you know you are onto something. If there is no reaction, it may be time to rethink. You can then follow up enquiries and have live conversations with prospective users.
A similar idea is to preview a product or service on your website. This can work if you have an effective way of driving traffic from your target audience to your site. The landing page describes the problem you are solving and outlines the solution. Visitors click on a link to find out more and are taken to a second page where the heading is “Hello, You Caught Us Before We’re Ready”, with a place for people to enter email addresses if they are interested.
There are many other smoke test methods. The ones you choose will need to be appropriate for your target sector. Once you have this primary data, it can be supplemented with secondary research, such as market reports.
The low fidelity MVP
In B2B settings, words or promises can only take you so far. Some form of demo is often essential to make you look credible. But this doesn’t require you to build a full product. You should only need to build a virtual prototype at this stage i.e. your ‘low fidelity minimum viable product’.
For web-based businesses, we are all familiar with online demos. But even for businesses that will sell physical products through physical channels, online ‘demos’ can still be powerful and in the present climate these are essential. You may also have a number of useful building blocks from the prior solution that can be repurposed.
You are going to use your low fidelity MVP to answer two key questions: do you understand the customer problem or need, and when you do, do lots of customers care? i.e. Will they pay money for it? So, designing a set of relevant questions to wrap around your demo is extremely important. You also want your prospect to do most of the talking.
It’s crucial to remember at this stage that you are not trying to actually sell a product or service. You are listening and learning. This is often one of the hardest things to grasp in the early part of the pivot process.
In fact, immediately trying to sell a product or service before you have determined if this is a viable market opportunity may lock you into developing (and supporting) a string of ‘point solutions’ that may never scale.
Testing for competition
In the Problem/Solution phase, there is one other job to do. An early assessment of the competitive landscape is vital. Those that have seen the low fidelity MVP may be most likely to help here as they may have already been searching for solutions. Find out who else is on the scene and when you Google them read their blogs first. They are often the most illuminating.
There are dozens of information sources available, so drilling down into what alternative solutions might exist should be undertaken as soon as possible. If you find that many others have tried and failed this could be an essential insight. Market timing often has a key role to play in the adoption rate of new solutions.
Gather all your insights – pivot or proceed?
The volume of data points and insights gleaned through this first part of the process is very important. You are searching for a customer segment where a real problem or future opportunity exists. You want to sense real customer enthusiasm right from the outset.
This will be a market that is large both in terms of potential $TAM and the number of customers. It must afford you the opportunity to really scale over time. It should not already be occupied by strong competitive incumbents.
Keeping track of all your experiments and insights as you go is key. Use these to regularly update the canvas with the team. Many of our clients are updating weekly, or as soon as important new information arrives.
Don't be afraid to stop if the insights are telling you to. Use the feedback to navigate to a customer segment that does respond to your proposition. Only when you run dry here should you consider reworking the proposed solution. Be careful not to do this too early or you will fall into the trap of creating a never-ending feature enhancement list for those that shout the loudest.
Another word of caution: Do not be deflected from your course by opportunities that may suddenly appear from left field – unless they align well with your vision. In the current climate there can be pressure from investors to chase opportunistic deals purely in the pursuit of short-term revenues. Your investors, who may have a portfolio of 10-20 businesses, have their bets spread around. You are making a bet on a portfolio of one.
Finally, if all the traffic lights look green, you are ready to proceed to the next stage – building out your solution by creating a high-fidelity MVP. This will allow you to engage more meaningfully with prospective early adopters and start on the path to Product/Market fit.
About the author: John Hall is CEO and co-founder of Duet Partners, a corporate finance firm that provides specialist funding support to high growth technology companies. His 30-year tech career began with major US semiconductor and software companies, and was based in the Valley during the late '90's. Before Duet he was CEO of a VC-backed consumer electronics company, sold in 2009 following several rounds of capital raising. In the past 10 years he has advised dozens of founders on the startup to scaleup journey and is a retained Board advisor to a number of UK technology companies.