Coca-Cola Case Study: How spatial analytics makes perfectly targeted product sampling campaign

We all love nice product samplings. This is the best way to meet a product, to experience it from first hand. There are no words or even a picture capable of depicting particular taste. That’s why product sampling campaigns are deeply loved by marketers of foods & beverages. Because they work as nothing else.

Since the A4E blog is dedicated to all thing data analytics, we are willing to share our own experience on how to enhance the performance of such sampling campaign. The Coca-Cola Company representatives approached us with a pretty interesting case regarding their new 0.75l product pack. It is aimed to households consisted of 2-3 members which had to receive the sample during dinner time, providing a meal pairing experience in the comfort of their own home. Nice and sweet, isn’t it?

The main question is how analytics could help to increase the performance of such sampling campaign. The simple answer is by data modeling. Which kind of data you might ask. This is the most interesting part.

We were lucky enough to have access to the data received by a previous campaign run. The product sampling activity was accompanied by a brief questionnaire regarding consumers` attitude on the Coca-Cola beverage. On top of this, every survey response was linked with geo location data.

The goal of this analytical project for the Coca-Cola sampling campaign was to increase the percentage of the target reach compared to the previous campaign run as well as to support the product samplings logistics.

What our team was to examine as much as possible data sources capable of enhancing a spatial analysis. So, beyond existing data of the previous sampling campaign run we dig deep into open data sources like home prices, salary levels, demographics, just to name a few.

Armed with data like this (and some more we are not disclosed to discuss), our team performed the obligatory data preparation, correlation spotting, algorithms creation, modeling, and validation. The achieved granularity of data was bunch of districts where the density of the desired audience is at its best.

The Coca-Cola team goal with this project was to enhance the target reach with 5% compared to the previous sampling campaign run. Our efforts in spatial data analytics boost this KPI with more than 20%.

Learn more on this Coca-Cola sampling campaign analytics project

There are just three ingredients of a successful retail business – location, location, and location. It is just the same with the sampling campaigns. The product samplings location is extremely crucial since it is the main link to your target audience. The Coca-Cola Company made one step further by not just relying on foot traffic for their target audience at a particular location but to visit the right households at home at the right time.

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