Gathering the Right Data for Conversion Optimization: Does Data Really Don’t Lie? — Pt.2

In this post, we will take a look into some terms such as attribution modeling and incrementality in terms of gathering data for conversion optimization. These are the answers to the common problems in marketing measurement, which I mentioned in part 1.

They can help you for a deeper understanding of data-driven marketing and structure digital marketing efforts better.

What is the Attribution Model?

The attribution model is a set of rules that determines which touchpoints and weights the credit will be distributed for the actual conversion. There are six common attribution models: the last click, first click, linear, time decay, location-based, and data-driven. The following are Google’s attribution models, but Facebook’s, Yandex's’ and Adobe’s attribution models are not much different.

Last click: Gives credit for the actual conversion to the action just before the conversion.

First click: Credits the actual conversion to the point where the user first contacted the business.

Linear: Distributes the actual conversion across all interactions.

Time-dependent reduction: Evaluates interactions based on distance from when a conversion occurs, halfway to interactions that occurred before 7 days.

Location-based: Gives 40% credit to the user’s first and last pre-conversion touchpoints and allocates 20% credit to interactions in between.

Data-driven: When you provide enough data (as of December 2021, 2000 interactions and 200 conversions must have occurred within 30 days to use Google’s data-driven model and must not fall below these numbers during the period of use of the model) with artificial intelligence support, reducing the conversion process from the most valuable to the least value.

Default Attribution Model

The default attribution model of Google, Yandex, Adobe, and Facebook is the last click, which gives all credit to the last click made, no matter how complicated the visitor’s path is.

Of course, there may be cases where the last-click model provides meaningful data for the business. For example, in low-budget situations, it often makes sense to first collect data with the last-click model and optimize the final stages to ensure that existing or planned traffic will convert. There may be businesses that don’t need an upper-funnel investment and have decided to focus on the mid to late stages. If you are already getting enough traffic but can not convert your unqualified traffic into sales or if you are in a niche area and the market volume is not much more than the traffic you get, briefly, if for some reason your priority is to convert the traffic into sales, you may want to base some of your decisions on this data by using the last click model and optimizing the conversions just before the conversion takes place.

For the last-click model to provide reliable data on which you can base business decisions, you need to decide what is important to you and what you want to invest in the path that leads to the last click.

Choosing Valuable Attribution

Consider a small business with a Google search campaign and a mobile app download link on its Instagram profile. A visitor saw your ad and entered your site, while doing research on the benefits of rice on her computer, skipped all the call-to-action buttons as she did not intend to shop at that moment but clicked on the Instagram icon, started following you, saw a story on another device 1 week later, entered your profile and downloaded your mobile app. In this case, will you give all the credit to social media and invest only in social media to download more mobile applications?

If you have a product category like bikes that people rarely buy, getting new leads can be more important to you than maintaining customer loyalty. Or, if you have a product that people continue to consume regularly, such as bread, you can make most of your investments towards gaining customer loyalty.

In order to decide which conversion is more valuable, you need to really understand your target audience and their purchasing journey.

You can download an empathy map template we created that can help you with this.

Incrementality

Let’s say that as a local business, you offer home delivery service limited to a few neighborhoods through a marketplace application and you sold rice with the campaign you carried out on the application that day. Do you think you sold rice by convincing your potential customers who did not plan to make rice that day or did you make the people who would already buy rice buy rice by ordering at home instead of coming to your store? If the answer is the latter, is it correct to consider this conversion when calculating the ROI for your mobile app? If you do not count this conversion, decide that the return on investment is low, and do not invest in this application, how will you win over your potential customers who buy rice from another business because it offers the option to order it home that day?

What Is Incrementality Anyway?

With incrementality, we aim to measure the real effect of that effort by simply subtracting the benefit from the total benefit in the event that an effort does not exist at all. To see the growth, what you should do is measure your campaign’s performance depending on your other campaigns. However, with a mindset that values the incrementality of efforts, you should also measure an effort’s success compared to a situation when there are no campaigns.

The presence of your mobile application, which we measure here, maybe your advertising campaigns or influencer submissions. There may be marketplace applications that reduce your profitability with the time you spend being active on social media or high commission rates. How will you measure whether all of this is actually increasing your sales?

In fact, with a very simple formula:

Your incremental sales = your total sales — your basic sales.

But learning your basic sales is not that easy.

Focusing on Incremental Conversions

Incremental testing works in the logic of experiments where the control group is given the placebo drug while the experimental group is given the real drug. Focusing on incremental conversions enables us to see the impact of your interaction with the customer across all touchpoints on the growth of the business, revealing the truly transformative points. It shows what needs to be focused on by showing what needs effort and what benefits the business.

Among the channels that convert your target audience into customers, which channel should you give the credit to? To what effort do you owe a customer who follows you on social media, encounters your ads, or reads your blog?

When you identify touchpoints that really make a difference, you really start running the right campaigns. Running an incremental value test or at least thinking about it can help you better manage all your digital efforts.

To sum,

Data really doesn’t lie; but it must be correctly constructed, collected, and read.

Feel free to get in touch!