In this series of posts, we discuss the role of Product Manager in defining, documenting and communicating market opportunities – in particular answering five key questions about your proposed product…
In this post, we focus on your Market Sizing is a quantified analysis of how interesting the opportunity is. It is one component that can help in making prioritization decisions, gathering approvals, or determining appropriate resourcing. Some companies may ask for formal financial analysis, requiring you work with your Data and Finance groups.
There are three key advantages in estimating Market Size:
- Validate you have an interesting opportunity – Whether you’re creating a new product or improving an existing one, you are asking your company to invest time and resources. In return, you need to demonstrate the potential for financial return.
- Establish assumptions for future testing, validation and optimization – Market sizing estimates provide a quantified baseline that will be validated during customer testing and referenced when assessing if you met launch goals. If your product isn’t performing to expectations once in market, revisit your assumptions to develop an action plan.
- Communicate expected outcomes and sensitivities – When seeking buy-in, or if you have a formal approval process, expect your stakeholders to ask for some quantified indication of the opportunity, along with more scenarios and upsides.
Market Sizing Best Practices
Market sizing is useful only if conducted in a critical, conservative way – using reasonable assumptions and real data. If your initiative means increased revenue and cost savings, your sizing assessments may include financial projections. However, it is usually sufficient to calculate the number of potential customers or users who will benefit from the initiative.
1. Use real data over assumptions where possible
Hard data can be hard to come by. Unfortunately, if you have to make many assumptions in a market sizing model, these tend to build up upon each other, giving you a false sense of accuracy. Do your best to track down data from a variety of sources. Be creative and double-check assumptions. Always cite your data sources and describe your rationale.
Data sources may include:
- Your product tracking analytics
- Market reports and online searches
- Online search
- Historic growth data for comparable services (for example, if a similar service grew from X to Y, then it is often a reasonable assumption you might be able to do the same)
- Your team – poll them for their estimates and pick the average
- If possible, run a test or prototype/beta to gather definitive data before making a committed decision.
- Model less rosy scenarios, presenting them side-by-side with your optimal case.
2. Show restraint but make sure the opportunity is still interesting
You’re not pitching – you’re assessing an opportunity. Don’t show a large market size because you think that will appeal to a manager or investor, or get you through an approvals process. They have heard it all before.
A total addressable market (TAM) analysis sets an upper bound on your business. But the reality is that your business will likely capture a fraction of the TAM. Only the greatest of break-out products reach saturation points (nearing their TAM) – and often only many after years of operation.
You will share the market with several competitors. Their customers are unlikely to switch to your product if they are relatively happy with their current solution – even if yours is better.
Adoption is limited by how fast you can market your solution, sell it, hire personnel to support it, and successfully operate it. This holds true, even if you have captive customers or a large network of users.
Some real-life examples:
- A website launched new features, and promoted them on the homepage and in emails to their existing user-base. After three-months the new features had a discoverability rate of 5% (that is 95% of users still didn’t know about them or couldn’t find them).
- A subscription product typically converted between 1%-2% of users from trial to paid user, despite an excellent brand reputation among the target audience.
- A freemium product shifted 5% of their users from the free to the paid version (a relatively good result) after a very aggressive marketing strategy and after introducing paywalls throughout the product experience. The other 95% never
- After three years of selling by a sales team (with 40 sales people), an enterprise solution achieved revenues of $80m per year. This represented impressive growth, but only a fraction of the market opportunity (which had a TAM of $325 billion).
Growing a business takes time. Be objective, reasonable and conservative – and ask yourself if this is still going to be interesting. Here is a methodology called TAM-SAM-SOM which sets upper and lower bounds on your market sizing.
Any business plan won’t survive its first encounter with reality. The reality will always be different. It will never be the plan. – Jeff Bezos
3. Show a range, several scenarios and/or annual sequence
Don’t just provide market sizing as a single number. Develop ranges to test sensitivities (factors with high impact but low certainty) in your modeling and assumptions. This will help you when taking on a calculated risk. If the difference between a successful outcome and an unsuccessful one is driven by only a small variance in one factor, for example, it is highly likely that your sizing will be inaccurate.
Take advantage of these two techniques, which can be combined together:
- Model an optimistic (high), average (expected), and baseline (low) case. Make assumptions that are within a range of possibilities and see how the calculations work out.
- Show a 3-5-year plan. Start with a conservative couple of years based on operational realities (adoption, speed of development, a limited target market). Over the next few years, you can show more optimistic outcomes based on building upon the smaller, early successes.
Beyond these “quick-and-dirty” techniques, you can use many advanced modeling and statistical analysis approaches (they are, however, beyond the scope of this book). Take the lead from your Data Analyst team for advanced modeling needs.
4. Illustrate your sizing in a highly readable form
Lay out your sizing clearly and neatly, so anyone can easily follow along. Imagine you are breaking out a math equation. Show each assumption in turn. Use tables, calculation trees, a spreadsheet, and diagrams. Note all sources and describe assumptions. Avoid blocks of text and lengthy descriptions of your logic.
Also avoid “false precision”. Round up to the most significant figure. For example, don’t add 724,500 to 20.1 million prospective customers across your two key target markets, and report 20,824,500 in total. And then multiply by a 5% conversion assumption to get 1,041,225 customers in total. The answer is 1 million (5% has a single digit of significance.) And no, we’re not making this up – this really happened.