Define the Formula that Drives the Business

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My passion for building businesses and products started years ago when I had the opportunity to co-found my own start-up. We had all the right ingredients for success; a unique idea, and committed team, and right amount of funding to make it a runaway success. We built a product that many loved and could see the potential in, but at the end couldn’t scale it into a successful business. After years of experience, when I look back, I am convinced that a lack of focus on the metrics that mattered most was a key factor that led to our failure. Focusing on what matters most and why is a critical key to success for any business/product and this intense focus is ever more important in a startup with limited resources and where time to market is a matter of life and death for the company.

Why is defining and communicating your product/ business model formula necessary?

It is well regarded that Product Managers are the “CEOs” of their product; meaning we are ultimately responsible for the commercial success of our products working hand-in-hand with our partners in engineering, sales/business development and marketing. However, in the midst of executing our day-to-day responsibilities, the link between the high-level business objectives and the product(s) we manage could be missed or not measured/articulated properly. Moreover, too often we may be measuring the wrong metric when evaluating the success of the product, which if not course corrected early can lead to wrong decisions.

The link between a product change and its impact to the bottom line should be clear and measurable; anyone working on the product should have a clear picture of how a feature (or even a bug) they are working on translates to success. That’s where having a clear, well articulated formula can help.

With that said, one framework that we have found effective is distilling your company/product’s business model into discrete variables that can be measured and can help to communicate the business goals and focus everyone on the team on what matters most.

So how do you get to the variables and metrics that matter and can be measured?

You define the formula that drives the business and your product and live by it as you execute on day to day activities. A the high-level, this formula is relatively straightforward: It is the revenue and expense equation that describes your company/product’s business model. For example, Uber’s revenue formula for a day/week/month would be: Total # of rides people take * $ per ride * % Uber’s share of rides taken

Now that’s of course over simplifying it and not accounting for other sources of revenue (UberEats, etc) but keep this in mind when thinking about your formula.

Here are some concrete steps to follow:

To keep this post short and digestible let’s focus on the revenue side of the equation of a company with one product line — a free mobile app that users have to download, sign up/create an account to use and perform a transaction (i.e., buy something) in order for the company to make money:

Hint: You are gonna need a nice clean whiteboard for this exercise because it’s going to get messy

  1. Write up the high-level formula that clearly describes your business model- variables that make up the revenue (and expense side) of your equation. A simple revenue formula (for a given time period) for our sample app would be: Number of users * transactions per user * monetization rate per transaction
  2. Now break up each top variable into its sub-variables in order to build a hierarchy
  3. Continue the hierarchy one level at a time until you can get to a specific feature/event in your product that you can measure. Here is what a breakdown of our sample revenue formula above (Number of users * transactions per user * monetization rate per transaction) could look like (in a given period such as day/week/month):
  • Number of users = Number of new users + number of retained users
  • Number of new users = # of distribution channels available for target segment * # of users that can be reached per channel * conversion rate
  • Conversion rate = # of promotional messages * % click through * # of users who completed the download * % of users who completed on-boarding * % of users who signed up for our service
  • Number of retained users = number of new users from the previous period * retention rate (We’ll cover retention rate in a separate post)
  • Transactions per user = # of active days per user * # of sessions per active day * opportunities to perform the transaction * conversation rate
  • Opportunities to perform the transaction = # of times per session the “buy” button is presented to the users
  • Monetization rate per transaction = $ revenue per transaction * % share of our revenue

And so on…. Ok. I think you get the point of this exercise. Although this might sound simple at first, the trick is to force yourself to drill as far down as you can to get to variables that you can control and measure. Otherwise, this will not produce effective results because it will again be high-level and abstract that no one can really connect the dots.

Hint: One way that you know you have hit the end is if the formula contains all the answers that you frequently cite when investigating and explaining the reasons behind changes in higher-level metrics.

4. Now that you have broken down your formula, for each node at the bottom of your hierarchy, identify the activities required to help move the variable in the desired direction. These activities could include increasing the number of distribution/marketing channels, forming new partnerships, new pricing strategy, working with suppliers and partners on cost structure as well as potential new features for the product. These actions require close partnership with various functions across the organization.

Here is an example for our hypothetical case (you can download the template here):

(Excel has been our tool for this exercise, but feel free to use whatever tool you desire. The advantage of using excel is that you can connect each variable to your experiment data and operations KPIs for real-time analysis -more on both of these topics in future posts)

5. Now that you have all your variables broken down, it’s time to populate them with actual data to make your formula come alive. Create an inventory of all the data points you have. This might require a bit of investigation since data may be getting collected in multiple data warehouses or analytic systems and/or you may not have the right level of access to get to them. If the data you need doesn’t exist, create a plan to collect it as soon as possible — this will be more valuable than creating the 14th visualization of data you’ve been looking at all along…

6. You are not going to get this right on the first try… Keep evolving the formula and adjusting your variables to get this to the point that it makes sense for your product/organization. There is often more than one way of breaking down your formula and you should pick the one that best represents how the product is used and purchased — It should be self explanatory and make sense to everyone on the team

7. Congrats! You have a working formula — now what? This step requires that get buy-in and alignment from every other function in your organization. Since you have a “live” formula that can be presented and discussed (not just a theoretical example), setup a time (this will take more than one session) with all functions and discuss the formula and define and get agreement on all the activities that need to be performed. You most likely don’t have the resources to move the needle on all variable at the same time, therefore you must decide as team which area is most important to focus on given the state of your company/product. Is it getting new users? Is it retaining the ones you have better? Or is it monetization? These are questions that only your team can answer.

Note that if you are part of a large enterprise with multiple product lines, you should define a formula for each product line (or business unit) and make sure it aligns with the overall organization’s business goals. Also, based on my experience the same framework can be applied as effectively in a B2B product/organization with one key difference to watch out for: Your buyer and user personas might be different so make sure to keep this in mind when breaking down your variables. For example, # of retained users/retention may not be a variable that you need to measure if you are selling your product as a package with set number of users to the buyer (i.e., license for 10 users).

Wrap up

Defining the formula that drives your business is critical and a well thought out one can help connect the dots between the product and its impact to the bottom line, ensure that the right metrics are being measured and help focus the team on what’s important and why.

If you have related experiences or additional suggestions, I would love to hear about them below. And if you enjoyed the post and found the helpful, please share it with a friend!

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