To demonstrate the process of identifying your Minimum Viable Customer that I described in my post here, I've created this simplified example of a semi-fictional company (semi-fictional in that it is based on my experiences with several real-life companies but I've changed many details for confidentiality purposes).

As a reminder, the 5 steps to identify your Minimum Viable Customer (MVC) are:

1. List all of the currently viable customer archetypes you have identified
2. Rank the value catalysts required from your early adopters (revenue, legitimacy, evangelism, engagement data, and/or user density) in order of importance to your firm at this time. (Again, see my last post for a discussion of this topic.)
3. Rank each viable group based on how well they provide these value catalysts, and then rank each group based on the combined catalyst achievable
4. Estimate the relative cost to your firm of driving adoption in each group
5. Choose the group with the highest expected value catalyst and the lowest expected cost

In this example, ResearchCo is a startup that has built a new SaaS tool for running financial analyses on companies and industries, and this tool is ready for use by early adopters. The company has self-funded to date but will need to raise capital in approximately 6 months.

 

Step 1: List all of the currently viable customer archetypes you have identified

ResearchCo's product could be useful to a wide range of users, at various levels of organizations and across many subsectors of the Financial Services industry. A few examples include: buyside analysts, sellside analysts, Registered Investment Advisors (RIAs), corporate finance managers, CFOs, insurance underwriters, bond rating analysts, auditors, startup founders, corporate development professionals, and more.

Let's construct a table to help keep our thoughts organized. I have provided an example with just a few of the customer archetypes below (for brevity, I'm not including the full analysis).

Customer group	Viability of product	Viability of firm-wide capabilities	Is customer viable (Y/N)?
Buyside analysts	**No** (Product can't yet pull financial data from Bloomberg, CapitalIQ, or similar sources used by analysts)	**Yes** (ResearchCo's team has industry expertise and sufficient support staff to service the demanding needs of several customers simultaneously)	**Not yet**
Sellside analysts	**No** (Same reasons as for buyside analysts. Additionally, the product has not yet been subjected to an independent security audit and therefore may not pass a larger institution's strict IT policies)	**Maybe** (ResearchCo does not yet have sufficient support staff to onboard and train a large financial institution, but a small organization is viable from this standpoint)	**Not yet**
Corporate finance managers	**Yes** (Product provides significant value with current functionality)	**Yes** (Same as for buyside analyst)	**Yes**
Auditors	**Yes** (Same as above)	**Yes** (Same as for buyside analyst)	**Yes**
Startup founders	**Yes** (Same as above)	**Yes** (same as for buyside analyst, though "demanding needs" likely doesn't apply to this group)	**Yes**
And so on...

We've just eliminated two groups that are not currently viable, and we're only on Step 1.

You may have also noticed that one of the answers above is "maybe". Sometimes you need to break down the customer segments further based on the size of the firm that a prospective customer works at. Location can also be an important factor. I simply wanted to keep this table as small as possible to make it more easily readable, but please add as many rows or columns as you need to better organize your thoughts.

 

Step 2: Rank the value catalysts required from your early adopters in order of importance to your firm at this time

If you read my post on value catalysts, you've already thought about this concept. In this step, simply rank each group as high, medium, or low importance. In the case of ResearchCo, it looks like this:

Value catalyst	Importance	Reason
Revenue	**Low**	ResearchCo is disrupting several highly entrenched incumbents. Prior to raising VC financing, ResearchCo will likely need to demonstrate that they can meaningfully change user behavior. Relying solely on potential revenue sources to fund ongoing operations would be highly risky since this change in behavior could take much longer than expected.
Legitimacy	**High**	Given that ResearchCo is attempting to displace entrenched incumbents, citing concrete examples of success with real-life users will aid significantly in both pitching new customers and raising capital.
Evangelism	**Low**	Low-cost, word-of-mouth-driven growth is always fantastic, but it is not a necessity for ResearchCo at this stage. They can easily reach a currently sufficient number of customers through direct outreach.
Engagement data	**High**	ResearchCo has built many innovative features but now needs to measure how real-life users interact with its product so that it can further refine these features and determine what new features to add. This should also help significantly in raising capital.
User density	**Low**	Since ResearchCo's system can import/export the file formats used by incumbent products, the benefit from network effects that could be gained from user density are limited.

 

Step 3: Rank each viable group based on how well they provide these value catalysts, and then rank each group based on the combined catalyst achievable

In this step, we will again use a simple ranking metric: low, medium, and high. Since the estimated value of the catalysts is highly subjective, there's no need overthink it with a numerical calculation.

In this new table, I've included only the viable customers from Step 1, and the importance of each catalyst from Step 2 in the header.

	Legitimacy (High)	Engagement data (High)	Revenue (Low)	Evangelism (Low)	User density (Low)	Combined catalyst
Corporate finance managers	**High** (1. This group is likely to use the product frequently, creating numerous potential examples for case studies. 2. Firm's don't tend to have finance departments until they are more established, which will provide more meaningful customer references.	**High** (This group is likely to contain frequent and repeat users, since the product is useful in multiple aspects of their daily and monthly workflows)	**Medium** (Firms typically have moderate budgets for products in ResearchCo's hypothetical price range)	**Low** (Although this group may occasionally share best practices within their own firms and with peers at other firms, there are limited catalysts in their current workflows that would prompt this behavior)	**Medium** (There are millions worldwide) ** **	**High**
Auditors	**High** (Auditors have a high threshold for the quality of products they use)	**Low** (They would only use this product during a small portion of their audits, so usage will be sporadic throughout the year)	**High** (They can likely pass the cost through to their clients)	**Low** (Same as above)	**Low** (The size of this group is likely smaller than corporate finance managers) ** **	**Medium**
Startup founders	**Medium** (Although they may have time to participate in case studies and focus groups, they will not be well-known companies to use as references)	**Low** (Although they will use the product actively for a few weeks when planning to launch their companies, the product won't have a use for many months after that, so there will be limited ongoing data collected)	**Low** (They do not have large budgets, and since they will only use it for a few weeks, they will not become a recurring revenue stream)	**Medium** _(Startup founders are more likely to talk about new products with their peers)_	**High** (Including non-tech local businesses, there are tens of millions of small business owners in the US alone) ** **	**Low**

 

Step 4: Estimate the relative cost to your firm of driving adoption in each group

As with the previous steps, there's no need to overthink this estimation by numerically calculating the cost. Low/medium/high will suffice.

	Cost	Reason
Corporate finance managers	**Medium**	1. Adequate availability: They have sufficient availability to meet with ResearchCo for sales pitches and onboarding. 2. Moderate adoption risk: This is not mission-critical in their workflows, so an error or two, whether caused by the product itself or the user learning curve, will not be too risky for these users. 3. Highly targetable: It is easy to identify potential customers on Linkedin and other sources.
Auditors	**High**	1. Low availability: They have very full schedules and few people in an audit firm have the authority to demo new products, particularly with client data. 2. High adoption risk: Errors cannot be tolerated as it would risk an audit firm's reputation, so proving ResearchCo's accuracy may be a lengthy process.
Startup founders	**Low**	1. High availability: Even though they are quite busy, they are always looking for products that will make their jobs more productive. 2. Low adoption risk: Startup founders are risk takers by nature, and so they are much more likely to try a new products, particularly if it saves them money over an incumbent's product. 3. Highly targetable: Large groups of startup founders gather at Meetups and coworking spaces.

 

Step 5: Choose the group with the highest expected value catalyst and the lowest expected cost

	Catalyst	Cost	Is this my MVC?
Corporate finance managers	**High**	**Medium**	**Yes!**
Auditors	**Medium**	**High**	** **
Startup founders	**Low**	**Low**	** **

 

ValueStream Labs Specializes in Accelerating the Adoption of New FinTech Products

If you have a FinTech startup and would like to discuss how to apply this process specifically to your firm, please don't hesitate to contact my partners and I at ValueStream Labs.