Data-driven customer acquisition in retail

Data-driven marketing is the best tool to attract the maximum number of new customers with a limited marketing budget. In this post, you'll learn how this works and what to look out for when selling your offers not only online but also offline.


In this e-book you will learn which possibilities and best practices exist in offline conversion tracking.

Download now


What is Data Driven Marketing?

Data-driven marketing, or data-based marketing, is the form of online marketing that uses data to make online marketing measures more targeted and therefore more successful. On the one hand, performance must be measured precisely, on the other hand, this data must be evaluated to determine and implement measures that increase efficiency and ROI (more about data-driven marketing at Searchmetrics).

Data Driven Marketing with focus on new customers

In order to identify potential new customers based on data, the first step is to define a basic target group that serves as a model for the new customers. This is typically done by using a group of existing customers who already exhibit the desired behavior. For example, this could be customers who have achieved purchases with above-average shopping cart values in your stores (learn more about base target groups on Facebook).

Then, machine learning is used to find people who are similar to the base target group. People who are already customers can be excluded to target only new customers. By analyzing millions of data points about each individual user, the people who are most similar to the base target group can be found. As a result, wasted media spend is avoided and the revenue generated is optimized (Read more about Machine Learning for new customer identification at Google).

The success factors in data-based new customer acquisition

When it comes to data-based marketing, in addition to general factors, everything around the data used is particularly important:

Collect the right data

Data should be collected about the customers that best reflect the desired behavior. For a retail company, for example, this could be the digital profiles of customers who have made particularly profitable purchases at the POS (more about the right data at ZHAW).

Merge data correctly

When merging data, care should be taken to ensure that all possible links between data points are mapped. This can mean, for example, that different user identifiers such as cookies or account and device IDs are linked across platforms (more on merging data correctly at Mbmedien).

Analyze data properly

The more data you have available, the better your prospects - but the harder it is to analyze it properly. It is recommended to use artificial intelligence and machine learning, which are provided by vendors like Google and Facebook (more about data analysis at Peakdemand).

Measurement and traceability of results

All results should be measured and fed back into the process. By feeding the results back as input data, the result is a system that can learn on its own. For example, the digital customer profiles of the sales achieved at the POS and their shopping cart value can be reported back to the base target group (more on this at Gonnado under Offline Conversion Tracking).

If these factors are taken into account, the foundation of successful new customer acquisition is in place.

What retailers should consider in particular

Retailers typically generate the majority of their sales in bricks-and-mortar retail, although the online store also plays a decisive role in the customer journeys. Therefore, retailers should also consider the following points in particular:

Store locations

Retailers should definitely include the locations of the stores and the locations of the users. The proximity of a potential customer to the nearest store significantly influences the likelihood of purchase. Therefore, all stores should be integrated into the data pool, taking geodata into account (read more at Marketingscout).

On- and offline identification

Retailers should also link the data about their customers' behavior in the online store with their behavior in the stores. After all, around half of all in-store purchases are linked to a preceding interaction on the Internet. Only by linking these data, an overall picture of the customer-jurney emerges (more about the ROPO-effect at Worldsites).

Start your data-based acquisition of new customers

The approach described in this article can be realized with the available online marketing tools. In addition to the online marketing team, the implementation typically involves people from CRM, sales and software development. If resources are limited, you can bring in a data-driven marketing agency like Gonnado. Also, get inspired by the published case studies on data-driven marketing examples or read more about the affiliate marketing solution for retailers with Gonnado.


Jetzt herunterladen