Using a Marketing Recommendation Engine to Personalize the Customer Experience

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Business Solution Sep 24, 2020

Christian Jabon

Executive Vice President, Business Solutions

The “New Normal” of Covid-19 means companies are forced to develop new customer engagement strategies to attract consumers and their changing priorities and interests. More than ever, companies will need to invest in their customer experience through personalization to drive revenue.

But these evolving patterns present a challenge for marketers to gather profiles and keep opportunities alive with personalized customer messaging. If you do not have a profiling mechanism in place, a more efficient approach could be to rely on marketing recommendation engines to supplement a CRM platform.

What is a Marketing Recommendation Engine?

Marketing recommendation engines ensure that customer profiles are updated regularly to help identify new customer engagement and communication opportunities to drive growth. They use machine learning, advanced algorithms and natural language processing to understand your customers and provide you with precise business solutions to drive customer acquisition and engagement.

This platform is aimed at helping marketers identify the right customers at the right time, the right content for the target audience, the optimal budget to drive incremental profit, and ultimately, the updated customer lifetime value.

Because the value of customers may evolve daily, marketing recommendation engines are designed to revisit the valuation frequently to ensure that any shifts in lifestyle, spending and behaviors are considered when recommending a specific offer for a customer.

Given the current climate, a successful recommendation engine should offer specific adjustments to adapt to the New Normal. Among the considerations, defining your customers and grouping them according to their current personas is key.

Marketing Personalization to Drive Value

By segmenting customers with common attributes and leveraging those segments as variables in the marketing recommendation engine, marketers can now get recommendations on offer types, targeted messages and potential response rates by customers within location, age and worth.

By linking offers to potential and existing customers based on their defined personas, companies can lower their marketing costs, create better connections and drive measurable value. They can also get an understanding of the expected stream of discounted revenue, assign new customer lifetime value and calculate a reinvestment amount that may generate incremental profit.

With a marketing recommendation engine, the opportunities to drive growth are endless, offering marketers a way to think creatively about how they incentivize customers. By investing in tools that make recommendations based on data and behavior, you can increase not only customer satisfaction, but overall profits.

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