Gathering the Right Data for Conversion Optimization: Does Data Really Don’t Lie? — Pt. 1

Marketing and advertising in history always had their methods of measurement, testing, and data gathering. But if this article had been published in a print magazine 50 years ago, I would have had to conduct ineffective research to create a heat map to identify the focus points of the readers.

The biggest difference between digital and traditional in terms of marketing and sales is the easiness to measure all processes based on up-to-date data and hold experiments that are related to the business and its audience directly in digital.

But on the other hand, we are talking about a world where the customer journey is getting more and more complex every day. In this chaotic world of data, if you have not set up the measurement phase with the right approach, relying on the data from measurement might be a mistake.

Now keep your business’ last conversion in mind. We will be looking for answers to these questions:

Would this sale happen even if you didn’t have investments for your conversion goals, such as your multi-channel ads, retargeting mailing campaigns, and big discounts?

Are you missing the chance to be more successful when you work with data that you didn’t shape properly?

There are 3 important points that you should pay attention to so that your digital data does not mislead your business decisions. We will talk about your conversion rates in this part.

Your Real Conversion Rates

Do all your high-conversion efforts add value to your business or do they take credit for the results that would occur anyway? Or we can ask: Are you using the right attribution models when distributing your conversion credit?

When you tend to take advantage of the advanced analytics possibilities of digital for a campaign, the best approach you can take is to follow all the metrics you set beforehand, compare the conversion rates with each other and invest more in the method where you see the best conversion rate. But to make sure you’re deploying conversions correctly, you need to think about attribution and incremental concepts as well as your customer’s journey.

In digital, the concept of conversion rate is used to measure how much of the traffic acquired in a given time in one of the channels such as a website, landing page, mobile application, advertisement, or social media results in a targeted action. If you want to read a more detailed article on conversion rate, you can check it out here.

Your conversion processes may differ depending on which stage of the marketing funnel you are at, what are your business goals, and business priorities. Viewing a specific page, clicking a button, leaving a contact address, or purchasing a product can be targeted conversions of a business. So we can say that the conversion rate of an effort = total target action is taken / total interest acquired * 100.

But does an increasing conversion rate mean you’re getting the best possible result for your business? Let’s take a standard conversion that is usually targeted on e-commerce websites, we want an average cart amount of sales as a result of a video impression. In this case, in an e-commerce business whose landing page is viewed by 100 unique visitors per day through this ad, without any other factors, the conversion rate will be 10% when 10 sales are made on that day at the desired amount.

But there are always other factors.

Let’s say you had 10 sales after a campaign. Among those sales, there may be consumers who came across your video even though it was from a different channel or former customers from previous campaigns. One of the buyers might be a customer who came to the website after watching your video and was distracted within 2 minutes, but then remembered you when you sent a notification. In this case, if you calculate your conversion rates as 10% without distributing the credit according to conversion time, you may be harming your optimization process.

Think of the example above, if you give the conversion credit entirely to sending notifications, it might cause you to stop producing videos. If you give all the credit to video production, then you might stop sending notifications. In other words, if you are not using the right attribution model, the data you need to lean on when calculating the ROI of your efforts and making investment decisions might mislead you. In pt. 2 we will fix these problems with attribution modeling and incrementality.