New research shows retailers are shifting toward real-time personalization and next-best-action systems. Peloran has launched a commerce intelligence platform that connects customer, product, sales and pricing signals to guide what happens next.



NEWARK, DE, September 17, 2026 /24-7PressRelease/ -- E-commerce has spent years getting better at predicting what customers are likely to do. The next challenge is deciding what to do about it while the customer is still in the store.

That shift is beginning to change the role of e-commerce technology. Instead of relying only on historical behavior, fixed customer segments and predefined rules, retailers are increasingly looking for systems that can interpret what is happening now and determine what action makes sense next.

Adobe's 2025 retail research found that 45% of retailers were using generative AI for next-best-action recommendations and 46% were using AI to personalize experiences based on real-time customer behavior. Yet 41% said fragmented data was preventing them from delivering real-time personalization.

Adobe's 2026 research points to the same tension at a broader level. Fifty-six percent of organizations identified more personalized customer experiences as a top AI investment goal, while 80% said highly personalized experiences that anticipate customer needs in real time will define breakthrough customer experience over the next two to three years. At the same time, only 44% said their data quality and accessibility were adequate for AI, and 75% identified data integration and quality as a major challenge.

"The industry has spent years getting better at predicting customer behavior," said Ersan Erturk, founder of Peloran. "The harder question is what to do with that prediction when the customer, the product and the commercial context are changing at the same time."

From Prediction to Decision

A predictive model can estimate that a shopper is likely to purchase, hesitate or leave.

That prediction is useful. But it does not, by itself, determine the best response.

A customer may show strong purchase intent while also being sensitive to price. The product may have changed in availability or sales performance. The customer may have visited several times before. Another shopper looking at the same product may have a completely different history and commercial context.

The decision therefore depends on more than predicted customer intent.

It can depend on what the customer is doing, what the product is doing, what is happening commercially and what has already happened during the customer journey.

This is the problem Peloran is addressing with its commerce intelligence platform.

A Commerce Intelligence Layer

Peloran brings customer behavior, product activity, sales performance and pricing context into a common intelligence layer.

The platform generates behavioral intelligence including purchase intent, hesitation, value orientation, discount sensitivity and customer value, then connects those signals to customer journeys and automated actions.

A returning visitor who repeatedly views a product can therefore be treated differently from a first-time visitor arriving through a promotion. A high-value customer showing hesitation can be handled differently from a price-sensitive shopper.

The goal is not simply to predict what a customer will do.

It is to help determine what the merchant should do next.

For merchants evaluating a marketing automation tool, this creates an approach in which automation can respond to a broader set of customer and commercial signals rather than relying only on predefined triggers.

The Data Problem Behind Real-Time Decisioning

The move toward real-time decisioning creates a fundamental data problem.

Retailers have accumulated customer, product, transaction, marketing and operational data across systems that were often designed to work independently.

Adobe's 2025 retail research found that 41% of retailers said fragmented data was preventing real-time personalization, while 35% said it was creating inconsistent experiences across channels. The research also found that 44% were already using AI to determine the best experiences, messages or offers across channels in real time.

Adobe's 2026 research found that only 39% of organizations have a shared customer data platform capable of supporting widespread agentic AI adoption.

The challenge, in other words, is no longer simply collecting more data.

It is connecting the right signals quickly enough to make a useful decision.

Peloran is built around that problem, connecting customer, product, sales and pricing signals before they are used to drive an action.

From Intelligence to Action

Peloran connects its intelligence layer to customer journeys and marketing automation, allowing merchants to act across storefront experiences, email, WhatsApp, web push, advertising and product experiences.

A high-intent visitor showing hesitation can enter a different journey from a price-sensitive shopper. Product and pricing context can influence whether an intervention makes sense. A customer who does not need an intervention can be left alone.

That last point is important.

Real-time decisioning is not simply about triggering more campaigns. It is about deciding when an action is appropriate — and when it is not.

For merchants considering shopify marketing automation, the approach connects automated marketing decisions with the behavioral and commercial signals generated by the store.

Measuring the Decision, Not Just the Conversion

Real-time action also creates a measurement challenge.

A customer may purchase after receiving an offer, but that does not necessarily mean the offer caused the purchase.

Peloran uses exposed and holdout groups to compare outcomes and estimate incremental revenue from interventions. The objective is to distinguish revenue associated with an intervention from revenue that might have occurred without it.

That changes the question from:

Did the customer buy?

to:

Did the intervention create additional revenue?

As more commerce decisions become automated, measuring incremental impact becomes as important as deciding which action to take.

A Broader Shift in Commerce Technology

The move toward real-time decisioning is taking place alongside a broader transformation in e-commerce.

McKinsey's 2026 research describes AI reshaping the retail value chain and calls for retailers to embed AI into daily trading decisions, including continuous optimization of pricing, promotions and assortment. The firm also describes next-best-offer systems that combine behavioral and contextual data as capable of producing double-digit uplifts compared with static segmentation.

On the consumer side, McKinsey reports that 84% of European consumers now use AI in their daily lives and 38% actively rely on AI to research products and inform purchase decisions.

As both shoppers and merchants increasingly rely on systems that interpret information and make recommendations, the ability to turn continuously changing signals into decisions becomes more important.

Putting the Model Into Practice

Peloran has launched its commerce intelligence platform to put this approach into practice.

Rather than treating customer intelligence, product analytics, marketing automation and revenue measurement as separate functions, Peloran connects them around a common decision layer.

The sequence is straightforward:

Understand what is happening. Determine what matters. Decide what should happen next. Take the action. Measure the result.

The platform is available for hands-on evaluation through Peloran's live demo environment, giving merchants and industry professionals an opportunity to explore the product directly.

For merchants using customer journey mapping tools, this approach allows journeys to incorporate changing customer and commercial context rather than functioning only as fixed sequences of predefined steps.

The broader shift is not from prediction to no prediction.

It is from prediction alone to prediction-informed decisioning — systems designed to continuously determine what should happen next.

About Peloran

Peloran is an e-commerce intelligence and automation platform that helps businesses turn customer, product, sales and pricing signals into real-time decisions and automated actions.

By combining behavioral intelligence, customer analytics, marketing automation, customer journeys and incremental revenue measurement, Peloran helps merchants identify opportunities, act on them and measure their business impact.

Peloran supports e-commerce platforms including Shopify, BigCommerce, WooCommerce and Ecwid. Peloran is developed by Ayosem Ventures LLC, a Delaware-based company headquartered in Newark, Delaware.

Media Contact

Ersan Erturk
Founder, Peloran / Ayosem Ventures LLC
131 Continental Dr, Suite 305
Newark, DE 19713
United States

Website: https://www.peloran.com
Live Demo: https://app.peloran.com/demo?platform=shopify

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