There are countless articles about the importance of defining and tracking the key metrics for your mobile app or web app. Conversion rate, user adoption, and all the standard app metrics are valuable, don’t get me wrong – but what really matters is how those metrics translate to business outcomes.
That’s a question worth asking yourself: do you know how to translate your app metrics into the business outcomes your leadership actually cares about? Into the numbers that make them realize you know what is important to the organization? Into the pitch that will get your project the go-ahead?
If yes, then get outta here and go do your thing. If not, buckle in. I’m going to break down the process of translating app metrics to business outcomes for you. From there, you’ll be able to do the work that allows you to speak intelligently and confidently when pitching your project – like this:
By adopting or building an application to handle our employee’s time off requests, instead of manually doing it the way we are now, we can save at least $133,000 every year in HR management time. And that’s only if half the company adopts the software. If 75% of the company adopts the tool, that number climbs to nearly $200,000 per year.
Let’s start with a hypothetical example of what I mean, using conversion rate (CR). In this scenario, let’s say you’re aiming to grow your in-app conversion rate, from freemium to paid accounts, from 3% to 5%. Stating, “Our focus this quarter is to grow our in-app conversion rate from 3% to 5%” is great, but it doesn’t directly translate into a tangible outcome for the organization, and thus it doesn’t necessarily resonate with your leadership. Why should they care? What impact does this have on the business?
What if you said instead, “Our focus this quarter is to grow our in-app conversion rate from 3% to 5%. If we hit that goal with our current user base, we’ll generate an additional $100k in recurring revenue per year at our standard paid account level.”
The 2% increase in CR doesn’t make your CEO, your CMO, or any other executive sit up in their chair. But the $100k in additional revenue will.
That’s how you get buy in for your project and the work you want to do. You’re translating what you’re saying into the language your audience needs to hear.
Put yourself in the shoes of whomever you’re trying to get to sign-off on the work. What would you need to know to make a decision? Retention is important, but how does it really impact the organization? Which of the following would you respond more positively to?
“If we spend $50,000 I believe we can improve our retention 3%”, or
“If we spend $50,000, I believe we can improve our conversion rate 3%, which will lead to an additional $250,000 in revenue per year and reduce our current advertising spend.”
That’s what I mean by “translating app metrics to business outcomes”, and that’s just one example. Let’s explore more examples, and learn how to put this method into practice.
When we’re looking to map mobile app or web app metrics to business outcomes, there are a few steps to take in the process – but don’t worry, they aren’t overly complicated steps.
Here’s the outline of what to do:
Let’s put these steps into practice, with some common examples below.
Let’s go back to the original example and follow the process I outlined above.
Step 1 is identifying the metric – but note that, in this case, conversion rate can have a lot of meanings. What does the definition of conversion rate mean for you? It could mean account creation, or checkout, or a workflow completion, or an app download, and so on. So make sure you know the precise definition of your metric – in this example, we’re using an upgrade from a free account to a paid account within the app.
You need to set a goal, because just having a metric isn’t helpful. In this example, we want to go from 3% to 5%, also known as a 2% increase.
Math – everyone’s favourite! In order to translate the metric to a business outcome, you need the formula to do so. Developing the formula is arguably the most challenging, and there are a few ways to tackle it. Here’s one we could use:
Additional Revenue = ((10,000*.02)*$45)*12
Here’s what those hypothetical numbers mean:
In this example, a 2% CRI gets us to $108k a year in additional recurring revenue. That’s what we’re talking about! Using variable placeholders, the formula looks like this:
Additional Revenue = ((Users*CRI)*MRR)*12
Now that we have the formula, we’re on to step 4: developing a hypothesis (or hypotheses).
Basically, a hypothesis here is just a strategy, tactic, or educated guess as to how CR could be improved through, say, specific UX/UI decisions. It’s as simple as writing out a hypothesis following a structure like this:
“By (action), we can increase (metric) to (results), because (rationale)”
A few examples pertinent to this overall hypothetical:
The beauty of having a hypothesis statement is that action is clearly tied to results, and it forces you to articulate why you feel the action will have results.
The final step has you wrapping all this work, and the associated findings, up into a tidy little statement so you can get buy-in from your decision-makers. Something like:
“By implementing a few key changes in our app – for example, driving more users to upgrade through in-app notifications and clear calls-to-action – we could increase CR by 2%, which results in an additional $100,000 in annual recurring revenue.”
Conversion rate is a powerful metric, and relatively easy to derive business outcomes (like additional revenue) from. You can use it to improve existing web or mobile apps, like we did above, but you can also use CR with hypothetical numbers to evaluate new app ideas for business feasibility.
Let’s look at another common, and valuable, application metric that we can translate to a business outcome your boss will care about.
Let’s use the example of an internal app for a human resources (HR) department, used for managing employee time off requests. In this scenario, the app has already been deployed across a 1,000 person company and has been adopted by 50% of employees. This means 500 users have adopted the tool and are using it consistently for requesting time off. We’ve learned that the new system has an estimated time savings of 15 minutes per vacation request & approval for the HR managers, compared to the old manual system. Lastly, let’s assume the average salary for HR managers is $75,000.
In this example, the metric we’ll be working with is user adoption. That can be defined as the percentage of users that have adopted the platform for consistent use.
Currently we’re at 50% user adoption. The goal we’re going to set is 75%.
This one is a bit more complicated. We want to sort out the savings in dollars that the app provides, based on the time savings of 15 minutes per vacation request & approval. In order to know this, we want to estimate savings per request. To get that, we need to first break down that $75,000 average annual HR manager to not just hourly rate, but 15 minute increment rate.
That’s pretty straightforward. Assuming 44 working weeks in a year (accounting for sick time, vacation time, and statutory holidays), and 40 hours in a work week, we get 1,760 working hours in a year per FT employee.
(75000/1760)/4= $10.65</pre The above tells us that every 15 minutes – so, every request – saves the company $10.65. That's our savings per request. Here's what the numbers in the above formula mean:
So, remember that of the 1,000 employees, 50% have adopted the app. If each of the 500 users requests time off through the system 25 times a year (for reference, we averaged about 30 per employee over last year at Paper Leaf), there is a reduction in annual expenses associated solely with time off requests of approximately $133,000. Here’s how we get that:
(500*25)*$10.65 = $133,167
If you want to get fancy, you can wrap it up into one formula:
(500*25)*((75000/1760)/4) = $133,167
So, even at 50% adoption of their new HR app, the company is saving a good chunk of change every year. That’s great, but in this example, our goal is to get the user adoption up to 75% – then translate that to savings. The formula we use to get that is the same as the previous, but we just change the User figure from 500 to 750:
(750*25)*((75000/1760)/4) = $199,751
The above means that, if user adoption increases 25% to 75% total, then 750 employees are using the tool, which means annual savings of nearly $200k (precisely, $199,751) – an additional $66,584 compared to the 50% adoption savings. For more math fun, that user adoption improvement amounts to 89% of the average HR manager salary.
Remember, our hypothesis should follow a structure like this:
“By (action), we can increase (metric) to (results), because (rationale)”
Here are some example hypotheses, around increasing user adoption to 75%:
This one is pretty straightforward. If you’re pitching a new HR system internally:
“By rolling out a new HR system to manage time off requests, we will save approximately $133k a year if half the staff adopt the tool. If 75% of the staff adopt the tool, that number nears $200k. That’s the equivalent to two and a half full-time HR managers.”
Bonus points if you can marry that with a ballpark cost estimate to develop or deploy the app – because you can be guaranteed your stakeholders will ask that question next.
And if you want to get buy-in for strategies to improve the adoption of an already-deployed app:
If we take a few concerted steps to drive more employees to adopt our HR tool – like encouraging HR managers to redirect manual time off requests to the new HR app, and adding a sitewide notice and stickied news post to our intranet about the new HR app – we can derive additional time savings that amount to over $66,000.
I’d greenlight that. Wouldn’t you?
If you have a project commencing in the near future, figure out the metrics that can be most effectively – and convincingly – translated into forecasted business outcomes. Do the math and add it to your internal pitch.
If you have an existing app that you know needs some love, but you aren’t sure where to start, evaluate it against some of the examples above, or other well-known app metrics. Collect the data and start forming some hypotheses to sort out what work should be done, and why, based on the upside of the business outcomes. Prioritize that work by finding the right balance of effort, upside, risk, and probability, then get cracking.
We all want to do work that matters, and be heard. Remember that speaking the language that resonates most strongly with your audience – in this case, your stakeholders – gives you the best odds of making that happen.