After our webinars on unit economics, we are getting a lot of questions regarding the Unit Economics Calculator we developed. To answer all of them at once, we wrote this article, where our CEO Alexey Kulakov explains why we developed the Calculator, what is it made for, and how to use it. We also added some interesting case studies from our experience. Have a look.
"Five years ago, two events happened to me almost at the same time. First, I was asked to develop a board game about unit economics (that’s how I first found out about this term and how this concept works). Secondly, I began working as a product director at Rideró and using unit economics in practice. I must say that this is the most effective tool that I have found over the past ten years.
Very briefly, what is unit economics and how does it differ from performance marketing?
So, unit economics is an approach in which you compare all the costs associated with a particular client and all the profit that he or she brought to you. And you understand what you scale – profit or loss. This, of course, is not the whole economics, because we don’t take into account fixed costs. In its simplest form, this model could be described by the elementary formula:
(average check - average cost per customer) * repeat purchases – the cost of attracting a customer
In general, it seems very similar to performance marketing, right? I also thought so at the beginning. But the difference is: when you learn to think in terms of unit economics, you realise that all decisions that someone (designer / marketing specialist / product director / sales director / lawyer / production manager / no matter who else) makes in a product are made only so that something in this formula changes. And besides, most of these changes have a dark side: for example, if you raise the cost of a check, the conversion may drop.
And when you realise this, it becomes much easier to make decisions about the toolkit. Unlike performance marketing, the tools here are associated not only with the cost of the lead, the availability of traffic and conversion but with all the processes in the company in general. Since we are a production company, for us (and our clients) this knowledge is very valuable, because it allows us to discuss the price in terms of payback, rather than in terms of expenses. And it actually simplifies the sale and contributes to the duration of strong and lasting relationships with the client.
In general, having developed a board game and having worked as a product director, I learned to see an economic formula in any scenario. By the way, from the UX point of view, unit economics is just a user scenario written in Excel, rather than in Figma.
Why was it necessary to develop the calculator?
There is one problem: if you haven’t worked as a product director yet, it is somewhat more difficult for you to reason in a similar logic than for me. And, in particular, it was more difficult for our managers and designers. Therefore, we made a calculator that allows you to discuss right at the meeting with the client how this website / application / advertising channel / intranet / any other idea will pay off.
This is how our calculator works (on the example of e-commerce).
We suggest to enter the basic parameters of the economics of any similar project:
- how many users are available in the channel UA;
- how much one visit will cost you CPC;
- how much is the conversion to the right contact C1;
- how much is the conversion to purchase C2;
- what is your average check AvP;
- what are your average expenses (everything that you spend on the fact of purchase, including the cost of sales, but not including the cost of attraction) COGs;
- how many repeat purchases you will have Ret.
I will say in advance that we had an extensive internal discussion on how to correctly name all these terms in English. But, to be honest, this is not very interesting – it is important to understand what this means in reality.
Usually, before attempting to enter data into the calculator, we have a conversation with a client like:
- Yes, but we don't have this data!
- It's okay, let's start by simply estimating roughly. What industry are you in? So I checked, in your industry, the average cost per click is this much. Let's be optimistic and say that the conversion rate will be 4% ... How much do you usually get paid?
- Well, let's ask your financial director, he will give us some approximate number.
And so on.
As a result, we understand how much we can earn at all, and most importantly, how sensitive our model is to fluctuations. For example, if a step in a half-percent conversion point takes you out of payback, you can allow only very price-controlled channels and it is very important for you to track any changes in the conversion funnel. Or vice versa: when you sell high-margin products, you shouldn't limit yourself with expensive tools. It becomes clear when and whether to invest in the development or redesign of the site or application. And sometimes it turns out that you need to develop not front-end but back-end interfaces because the source of innovation is in raising the margin at the expense of the cheaper process.
By the way, a few words about innovation. Unit economics transforms the word “innovation” from a buzzword into specific knowledge. This is the answer to the question of how to make one of the key business processes cheaper. And, what’s important, how to discover these key processes.
Next step. After you’ve entered your metrics into the calculator, it will show you something like this:
This is a collection of basic metrics that it makes sense to discuss with the client. We could write a separate article about each of them, but we won’t do it now of course.
There are also other formulas. For example, if you are an advertising publication and sell access to an audience. Or you have an application, and your sales occur within it. Or something else. All of them are easy to do in Excel, and someday our calculator will learn how to count them. And yes, often there are much more additional parameters in such stories, and the numbers are not entered by hand but are taken from CRM, GA, your production ARM, etc.
To illustrate the work of the calculator, we asked our digital strategist Evgeny Kuznetsov to go through a few cases.
Case study 1. Online diaper store
Let's look at the source data. Direct promises us traffic at 19.7 rubles (100% of traffic on request “Merries diapers” across the Russian Federation), the average price tag on Beru.Ru, Ozon and similar platforms is 1259-1359 rubles per pack. Plus (probably) people will be buying some extras. But the margin on the diapers themselves is very low – 10 percent. It seems you can do a conversion in the region of 5% and at the same time close a large percentage of orders (if you respond to orders and calls, without skipping any). But at the same time, imagine that our delivery services are not good enough and we don’t work with repeat sales. As a result, due to low retention, we will have a minus (loss) model.
Case study 2. Online diaper store, improved version
And now let's imagine that we hired another manager, who implemented CRM, sorted out the delivery and figured out how to return customers. At the same time, due to discounts and other offers, the average check went down a little, but the cost price remained the same. As a result, this increase in repeat sales helped the store reach a small plus (profit).
Case study 3. Online diaper store, even more improved version
Now imagine that the manager asked designers and UX to come up with something to increase the average bill, plus the store started selling baby food and other goods with a good margin. As a result, by maintaining the achieved retention, increasing the average bill and adding more marginal goods, the store turned the business model into a very profitable business.
Case study 4. Sale of machines
And now, by contrast, imagine that we sell machines. One machine costs a lot, and we add a large margin on them. For example, take a CNC machine. The first one found on Yandex.Direct costs almost 3,000,000 rubles. Direct promises us 100% of traffic at 28.70 rubles per click, but at the same time it predicts a maximum rate of 300+ rub., therefore we will pay 49 rubles per click (we want to get a higher position). At the same time, the conversion rate is not the highest (in our country, like many others in this niche, the site is not optimised for mobile, and we didn’t adjust the rates for mobile and get a lot of negative traffic). And we also have lazy managers – they miss a lot of requests, but since we have good prices, we still close 20 percent of the deals. As a result, we get very expensive leads, and even despite no retention, we cover our expenses due to high marginality.
Case study 5. Sale of machines, improved version
And now let's imagine that we did our website redesign, optimised the mobile version and learned how to work with mobile traffic. At the same time, we have improved the motivation of managers, they now get a percentage for closed deals and additional sales (however, it is important to understand that in this case, we didn’t take into account site redesign in terms of costs in this model, since these costs should be divided into all channels in which the site is involved , but by looking at the increase achieved, we can tell that it easily covers even the most expensive design).
This is how you can quickly test hypotheses with the help of our calculator :–)