Data is becoming increasingly important in marketing, especially in digital.
Everything that happens online can be analyzed and followed. We know what users do on our platforms and, based on the given information, we make decisions and changes in order to get the best possible results according to previously set goals. But clients, as well as performance-oriented agencies, want to know something more about those three magical letters – ROI (return on investment). And yes, we totally agree with our clients when they want to know how much money did they get in return from their campaign.
Unfortunately, sometimes you can’t know ROI because it depends on set goals. However, in most cases, those goals include generating some sort of lead – email subscriptions, reservations, bookings, etc. People usually find the number of leads to be relevant data… but what do those numbers mean?
What’s the difference between one email contact or one hundred reservations? How can we know if the budget was efficiently invested in a campaign that results in a positive ROI? It’s easy to calculate ROI on eCommerce websites. Usually, there are webshops or booking pages with a clearly defined monetary value of the product or service and the payment is usually done via some web service. It’s possible to analyze all data using web analytics software (Google Analytics) with monetary values accompanying all other statistics. But it’s also possible to calculate the precious ROI even when the website is not an eCommerce website. I give you two examples of how it’s done.
Example 1 – private medical institution
There are usually two main goals when creating campaigns for private medical institutions. One is brand awareness, and the other is lead generation through appointment reservations. Let’s take the second one for this example. To calculate ROI for the second goal, we need to know the monetary value of an inquiry for an appointment. That number is easily calculated by analyzing historical data. We can find out how many actual appointments were made in relation to the number of inquiries.
For this example, let’s say that the relation is 1/4 or 25%. To implement precise monetary value in the calculation, we also need to know the monetary value of each patient, it can be the price of an appointment or average future value of each patient – money that average patient spends on services of a private medical institution during his lifetime.
Let’s say that the patient value is 100€ for this example. We can calculate the monetary value of an inquiry using this data – it’s 25% of 100€. So, in this example, monetary value of one inquiry is 25€. So, if we invest 2.500€ in an advertising campaign, we need to have at least 101 inquiries to have a positive ROI. In this way, we can see if our campaigns are successful. If we didn’t have the monetary value of an inquiry, we would probably be happy with 50 of them. Now we know that it isn’t good enough.
Example 2 – tourist accommodation
I’ll use a tourist accommodation website without a booking engine for our second example. Let’s say it’s a website for camping with three types of accommodation – parcels, mobile homes and bungalows. If we follow our method from the first example, we can easily define the monetary value of our goal – inquiry for accommodation booking. In this case, the calculation is a little bit more complicated.
Let’s say that 20% of inquiries for parcels result in booking (conversion rate), with an average booking value of 1000€. Now we know that the monetary value of an inquiry for parcel booking is 200€. On the other hand, only 10% of inquiries for mobile homes result in actual booking, with an average booking value of 2500€. This results in a monetary value of 250€ for an inquiry for a mobile home. Finally, 15% of inquiries for a bungalow result in a booking with an average value of 2000€, which means that the monetary value of an inquiry for a bungalow is 300€.
In this case, Google Analytics can really simplify ROI calculation. Goals and their monetary values should be implemented in Google Analytics, and it does the rest of the job. For example, if we had 10 inquiries for parcels, 1 inquiry for a mobile home and 1 inquiry for a bungalow with an investment of 3000€ in an advertising campaign, we wouldn’t have a positive ROI. But, if we had 6 parcel inquiries, 4 mobile home inquiries, and 3 bungalow inquiries, we would have a positive ROI with the same investment.
One of the most important things in this process is to analyse historical data to find out how many inquires resulted in some sort of service or product use (sales). In other words, the conversion rate from a lead to a customer. When you have that data, you can easily assign a monetary value to your goals. After that, all you need is an Analytics Specialist who can implement that data within Google Analytics, and provide you with a nice custom report. With it, you can see if your campaigns have a positive ROI in real time, and it doesn’t matter if you don’t have an e-commerce website.
