Drive-to-store explained

First of all, let’s start by explaining what incrementality or incremental visits exactly are.

Incrementality is defined as a measure of supplemental business resulting from marketing tactics, which would have been missed otherwise. To clarify, it is the ratio between the amount spent on advertising divided by the incremental uplift (e.g. €100 spent on advertisements results in 50 additional sales, which is a €2 per incremental user). 

Common misconceptions

Today’s industry view on the concept of incrementality is often biased by the misconception that this only applies to frequently visited stores (e.g. supermarkets). Hence, the truth sheds a completely different light on the concept of incrementality and how it can boost your business.

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Many people assume that the effect of ad exposure on the number of visits can be accurately calculated by using a pre/post-test. However, this assumption is not entirely true. The effect is measured by comparing location data from visitors, before and after the ad exposure. Here we encounter the main issue: any differences can be mistakenly ascribed to the advertising campaign, without taking other factors such as weather, holidays, road traffic etc. into account. 

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Another issue relates to businesses with a lower customer visit frequency. This makes it harder to perform accurate analysis, since less data is available for visitor profiling. A well-known example is the comparison between a car dealership and a supermarket. Car dealerships will have fewer recurring customers than supermarkets, which makes it easier for the supermarket to obtain useful data from the pre/post-test. How many times per month are you going to the car dealership and the supermarket? 

The Accurat Method

Instead of the classical pre/post analysis we developed a method where both an exposed and control audience are offset. Our control group has not been exposed to the campaign and therefore if it’s audience grows we know there are other influencers at work beside the campaign. Incremental visits are then defined as the total exposed visits minus the corrections learnt from the control group. 

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We use a method of visitor tracking through users mobile device. This is done by collecting location data related to POI’s of certain brands on a GDPR compliant basis. In this way, we know which brands or places that the user has visited. 

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In a nutshell, we are able to predict the effect of the ad exposure in terms of increased visits. This is called the incremental visits, which enables us to extrapolate this even for businesses that have low customer visit frequency. 

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The best way to explain our methodology is by using an example. 

Car dealership example;

Car dealerships are not the everyday store for the average person. Most people only visit the car dealership to buy a car or maintenance. Our methodology starts working for you when someone visits your dealership during the advertising campaign.

1. We create two similar groups of users with machine learning

2. We identify an exposure group 

3. We identify a control group

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When the campaign starts, we are able to compare the visit statistics of the exposed group to the control group. In this way, the only difference between the groups is the ad exposure. Therefore we can provide real estimates on the effectiveness of the advertising campaign.