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Predictive Personalization is the ability to predict customer behavior, needs, or wants and then precisely tailor offers, products, and messages to each recipient across channels and touchpoints. These messages differ greatly than traditional manual segmentation and personalization tactics as they are based on insights revealed through automated data-driven algorithms, not just past behavior, and are continually optimized through machine learning and Artificial Intelligence.

Predictive Personalization Strategies to Boost Engagement and Revenue

While traditional personalization tactics will boost conversion rates 10% on average, we’ve seen Predictive Personalizationlift revenue 22% and increase Click-to-Open-Rate a whopping 83%. Here are five proven Predictive Personalization tacticsto implement that will drive a significant increase in engagement and revenue

Predictive Segmentation

Called “the future of marketing” by Forrester, Predictive Segmentation provides customers with highly precise, contextually relevant messages at machine learning speed and scale. As your customer base evolves, predictive models automatically retrain to provide the best assessment of what future actions each customer will take.

Quickly build your highest-performing customer microsegments, uncovering hidden opportunities by identifying subscribers who may have been left out of previous segments that used traditional activity filters

  • Segment based on predicted lifetime value, likelihood to purchase, brand or category affinities, discount affinities, and much more
  • Acquire new customers using lookalike audiences based on predicted customer lifetime values and affinities
  • Save customers who are at risk of churning using enhanced, automated post purchase and loyalty campaigns

Predictive Product Recommendations

Quickly lead customers to the merchandise they’ll love the most – and they’re most likely to purchase – throughPredictive Product Recommendations on your site, in your mail campaigns, and in your targeted display ads. Advanced machine learning algorithms provide the ability to layer deeply customizable merchandising decisioning, predicting the most relevant, data-driven, and personalized products to influence the unique customer journey toward the path to purchase.

  • Leverage anonymous browse data to personalize recommendations
  • Show products that haven’t been purchased or previously suggested with intelligent recommendations
  • Open time optimization ensures you never recommend an out-of-stock item
  • Use across multiple campaigns and channels: email, on-site, display ads

Listrak processes millions of rows of data per second.

This allows you to segment, mine, cross-reference, and overlay customer data in real-time to create the most targeted and personal campaigns across every channel and touchpoint.

Predictive Content Recommendations

Strengthen readership and improve engagement through context-aware content recommendations. This is a game changer that enhances customer experience by identifying and delivering the exact content that will make the biggest impact while helping customers remain engaged and active during the sales journey.

  • By applying natural language processing, artificial intelligence, and machine learning algorithms to your website content, Predictive Content automatically interprets and understands the context of your content
  • Dynamically-adapt and personalize your recommendations to each user’s preferences, brand or category affinity, and real-time intent
  • Automatically discover new content
  • Maximize your content investment