Customers want value. It's our job to articulate it.
I work with both product companies and digital agencies. The same holds true for everyone – the level of competition out there is crazy. And that means we need to be able to articulate our value clearly. One of the easiest ways to do that is to build your own calculator.
But one of the most common mistakes when building an online ROI calculator is that we make it too simple. And if it's simple, it's likely not only not accurate, but it's not believable.
So in this first part of a two-part series, I'm going to step us into the complexity of the logic to make an ROI calculator persuasive.
Understanding the ROI Formula
You can't really build your own calculator that helps a customer understand the ROI of hiring you or buying your product if you don't know the formula.
The simplest way to think about the formula is Return divided by Investment. The image below shows it with a tiny bit more depth. Take your return and subtract your investment. That's your real return. Then divide it by your investment. But then multiply it by 100 so that it's a percentage, and easy to understand.
Let's look at this formula for three different examples to see how it would work in our ROI calculator.
Example One: Training / An Online Course
Let's say you're selling a course. It costs $1,500. But everyone who takes it says it saves them 2 days a month. For simple math, let's say that's 10% savings. And if the average person who takes the course makes $75,000 – then that's a $7,500 return.
So the ROI = (7500 – 1500) / 1500 * 100 = 400%
Example Two: Software Development Services
Let's say you're building some custom software. This software will allow the customer to have a tighter integration with an online store (like Amazon or Walmart) so that their site's articles can embed their products with real time prices and availability for greater affiliate revenue. The cost of the project is $100,000. But it will increase their affiliate revenue to $250,000 a month from $100,000.
Now we have to calculate the return of that investment, and for this example, let's calculate it for a 3 month period. So they'll improve their revenue by $150,000 each month, for 3 months. That's $450,000. (And that's only for 1 quarter!)
So ROI = (450000 – 100000) / 100000 * 100 = 350%
Example Three: Selling a Product
For our last example we'll sell an inexpensive product that costs $20 / month. This could be just about anything but since I really love the best testimonial product I've ever seen, I'll think about something like it. Let's say that having testimonials on the site will not only improve your visitor to lead rate, but also your lead to close rate. How do we do that math?
For this example I'm going to suggest that each conversion rate improves by 15%. So the return looks like this:
((visitors * visitor to lead rate * 1.15)*(lead to close rate * 1.15)* profit per order) – 20 / 20 * 100
The Complexity of an ROI Calculator
Did you catch the complexity as I went from one example to the next?
- In the first example, the math was easy and straightforward.
- In the second example, there's a predictive dynamic & timeline dynamic.
- In the third, we have to pull in much more internal data to make it make sense.
And the truth is that things are even more nuanced.
Let's look at the simple example (number one) again.
Does every person who takes this course save 2 days? What if we segmented our customers by role type (Senior Exec, Mid-level manager, Frontline Employee)? Would we find that different kinds of folks save different amounts?
Also, the return would be different because those different kinds of roles often make different amounts for their salaries. And that means the return calculation changes based on their role.
What about the nuances in the second example?
I don't know about you but in most cases, when I create an estimate for a customer, I can't predict with certainty the results they'll see from using the software we've created.
What if there's a delay in deployment of the software? What if the results are lumpy – such that we need to take into account some variability related to seasons?
What I'm trying to get at is that if you're going to build your own calculator, you can't make it so simple that it's just silly. It needs to take into account the complexity of the world that you're an expert in.
I know this because I'm working on my own ROI calculator for my coaching work. It's why you saw me write about conditional logic yesterday. Because these calculators require that we ask enough questions to capture the nuance and use the data in formulas to help us make the case.
But like I told you, this is only part one. This week I'll write you part two, so you can see me build the calculator with one of the form plugins I reviewed yesterday. I just didn't want to dig into the complexity without covering these basics first.
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