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What is data-driven marketing, and how do you use it?
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Although it may sound like something out of a sci-fi novel, machine learning is very much a reality in the digital realm.
While its relevance to marketing is wide-ranging and evolving, one clear benefit of the technological development is as a powerful tool to help drive customer loyalty.
Machine learning is an application of artificial intelligence (AI) that gives systems the ability to automatically learn and improve from experience, without being specifically programmed to do so.
It allows marketers to collect and process massive amounts of data and act in real-time to create a personalised and engaging experience, and to provide relevant offers to customers. Machine learning can be a powerful and innovative tool to help you drive customer relationships and optimise your loyalty programmes.
The last thing anyone wants is to get scammed while in the process of going about their daily business. However, with intuitive systems in place, the chances of a fraudster getting through the virtual door can be drastically reduced.
At Epsilon, we have had more than our fair share of experience with handling fraudsters and finding the right protocols to keep them at bay. One of our solutions allows you to set-up configurable, action-based scoring rules to evaluate the risk of loyalty redemption fraud in real-time. And if a high-risk redemption order is identified, it will be suspended for review before it has a chance to do any nasty business.
Our fraud detection capability also provides you with the reporting you need to monitor and analyse orders by risk status and to make modifications to your scoring algorithms as patterns of fraud evolve.
Trust us, it’s easier than it sounds.
With our VAP (Value Attrition Potential) solution, we use an advanced statistical model to segment a customer base. It determines how valuable customers are, how likely they are to leave, and what kind of potential they have in the future.
With machine learning, marketers can automate the collection of data and get much more detailed segmentation. This means our data scientists spend time evaluating outcomes and creating strategies, not compiling data and processing it.
The implications of this are pretty massive. You can benefit from deeper insight,s delivered faster, with the machines doing the heavy lifting. Customer scores are created and delivered as profile attributes to the platform, before strategies are then created to determine how best to engage with customers.
Different brands are at different stages when it comes to implementing the latest technological developments. Each brand should develop a strategy about how to best deploy machine learning in a way that will work for their individual marketing objectives and to optimise their marketing performance and efficiency.
Evaluate your current technology infrastructure to see if it can support machine learning, and how. You can then use your loyalty programme as the foundation of your developing AI initiatives.
