
One of the biggest hurdles online retailers have long faced is the lack of personal touch they can offer customers.
Today, however, data-savvy retailers are flipping the script. Advances in technology and analytics now allow retailers to deliver highly targeted offers based on behavior, loyalty data and historical patterns. The days of blanket, one-size-fits-all promotions are fading; tailored discounts can now be delivered instantly through apps and loyalty platforms.
Loyalty programs also look very different from those of just two or three years ago. Instead of relying on batch processing to deliver weekly or monthly promotions built around broad demographic segments, modern systems use AI and real-time data. Retailers can now respond immediately to a customer’s behavior with personalized offers.
When paired with a retailer’s mobile app, this capability becomes even more powerful: Dynamic discounts can be generated based on a customer’s shopping history, preferences and even the availability of local inventory. A retailer’s POS system plays a huge role in their ability to offer specialized promotions. Retail Pro Prism is a promotions powerhouse – with endless promotion types and combinations available to retailers – and paired with the AI-powered loyalty and personalized marketing tool AppCard for Retail Pro, retailers have the ability to analyze purchase history of a customer, set up triggers and personalize offers.
Next Step: Putting AI to Work

Data analytics helps put a customer’s historical purchases into context, while AI predicts what they are likely to do next. Retailers can use these insights not only to recommend products but also to refine inventory planning. In addition to identifying which promotions will build loyalty or increase basket size, AI can determine which offers are most likely to prevent churn or cart abandonment.
Starbucks’ loyalty program is a prime example of this predictive, data-driven approach. The app tracks visit patterns, time of day behavior and order customizations. AI then analyzes this data to create individualized offers—such as bonus stars on a customer’s favorite drink or incentives to shift a shopper’s routine to help boost traffic during off-peak times.
Micro segmentation

Of course, applying data analytics isn’t new. However, the granularity of each segment can now be made much finer. Consider the value of being able to drill down, not only to determine which customers are “millennial moms,“ but instead learning which 35-45 year old female customers with children buy organic snacks weekly. That type of segmentation can be invaluable for delivering relevant promotions to customers — and for increasing visibility for specific products as well as ones that are closely related but perhaps new to the market.
Everyday Value

Another trend are retailers meeting customers where they are in terms of comfort with technology: Many shoppers don’t want another app on their phone or are cautious of sharing too much personal information with retailers or are just focused on stretching their budgets. The everyday value proposition positions a retailer as one with consistent, trustworthy pricing paired with occasional deep promotions, and builds consumer confidence in the brand.
The more transparent pricing strategy fosters trust for this segment of shopper and positions retailers as reliable sources of quality products at good prices. Many of these shoppers experience “sales fatigue” and prefer fewer, more significant promotions rather than constant discounting. Walmart and Aldi exemplify retailers that succeed with this everyday low-price model.
As retailers infuse their loyalty programs and promotions with advanced data analysis, AI and real-time targeting, a new trend is emerging: using technology to enhance, but not overwhelm, the customer relationship. The most successful retailers are finding the balance between personalization and customer comfort by offering meaningful value without excessive complexity. Whether through highly tailored offers or reliable everyday pricing, this trend reflects a shift toward building trust, reducing friction and meeting shoppers on their own terms. Retailers that strike this balance will be best positioned to deepen loyalty and drive long-term growth.











































