I recently led a roundtable with Epsilon loyalty clients, and one of the key areas of discussion was how machine learning is transforming the loyalty industry. After more than 25 years in this space, I continue to be amazed by the many ways the industry can improve the customer experience and drive more revenue for companies. During the roundtable, there were discussions on how machine learning will reshape the way companies utilize loyalty programs in the near future, augmenting what can be achieved by humans alone, to deliver truly personalized experiences. Today, machine learning is enhancing data-driven marketing strategies, creating a shift from 1:1 (a messaging strategy that’s ‘generically personalized’ with promotional offers) to 1:You (a holistic customer experience strategy that’s personalized with the best choice for individuals across all points on interactions).

Let’s further explore how you can take your loyalty strategy from 1:1 to 1:You

Data-driven marketing is an advanced strategy that marketers have implemented to both enhance and personalize the customer experience leveraging transactional and engagement data to achieve 1:1 communications. However, when you add machine learning to the equation, the personalization opportunities far exceed transactional and engagement data because machine learning technology has the ability to make real time decisions on all relevant data.

Further, marketing programs can be enhanced through machine learning because unlike a campaign-based approach, machines operate in a 24/7 mindset, learning and adjusting in real time based on the data coming in. Typical campaign-based approaches use static content based on one specific segment; instead machine learning creates dynamic content using words, pictures, colors, a variation in tone, length and much more. Rather than focusing on a campaign based on discounts or double points, machines can help marketers present the best choice for every customer in regards to product, creative, channel, value proposition and more. Data-driven loyalty marketers can enhance their personalization efforts through machine learning technology to shift from standard personalization (name, point level, preferred channel, etc.) to a much more customized interaction that’s focused on an individual: 1:You.

For example, eBay is starting down the path of an enhanced customer experience by using machine learning to drive better results. Their holistic approach includes utilizing larger data pools for decisioning for real-time interactions, product recommendations and channel preferences on a continual, around-the-clock basis to learn what is working and what is not. No two emails, product recommendations or curated purchasing paths are the same. Machine learning is even defining what colors and pictures are more successful; and it’s automating the process of improvement allowing the humans (marketers, product managers, etc.) to better focus on strategy versus managing a campaign. Success is leading to the expansion of machine learning into search analytics, the creation of citizen data scientists and voice-assisted interaction.

Loyalty programs are invaluable when it comes to getting to know your customers. The multiple components of a loyalty program – acquisition, increased engagement, redemptions, attrition and re-engagement – are enhanced through machine learning to enable our goal of 1:You.

With this new approach, acquisition will now focus on more real-time efficiency to find the most profitable customers who are likely to engage with your brand. Increased engagement is inspired through the variety of content that’s available to share with members. Redemptions will provide marketers with insights into the members’ choices, like their preferred times of redemption and channel preference, to create a better balance of redemptions with liability management. And from analyzing member data, ‘at-risk’ members are easily detected and can proactively be communicated and marketed to in more precise offers or solutions. For re-engagement, enhanced analytics will help guide decisions on what gets an inactive member to re-engage, whether it’s through value choices, dynamic content or other personalized tactics. Loyalty program data fuels data-driven marketing strategies. When machine learning is applied, you’re able to communicate 1:You.

As you’re incorporating machine learning into your marketing programs to create a 1:You, take a crawl, walk, run approach with your marketing roadmap. Begin with an audit and review of your loyalty roadmap. Consider bringing in an expert to do a one-day workshop with your marketing and analytics team to identify opportunities. It’s important to recognize that a 1:1 strategy is advanced; you’ve carved the path to continue with technology innovations to achieve 1:You. So don’t hesitate, get started today.

Topics: Loyalty, blog post, Personalization, Machine Learning, Marketing Technology, Customer Experience

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