Retail

OmniPersonal Retail 

Deliver intimately personal shopping experiences that serve valuable unmet customer needs, and respect customer privacy, by design – with OmniPersonal Retail.

What if your loyalty app could increase basket size by understanding what each customer actually needs this week, without collecting a single additional data point?

DataSapien makes this possible. Our SDK embeds into your existing retail app, processing rich personal context entirely on the customer’s own smartphone. The result: deeply contextual product recommendations, personalised promotions, and intelligent customer journeys that feel anticipatory, empathetic, and genuinely useful. From beauty and skincare to fashion, grocery, wellness, and luxury retail — customers stay in control of their data, and you get the outcomes that matter: increased basket size, stronger loyalty, and higher lifetime customer value.

Omnichannel connected the touchpoints. OmniPersonal makes them intelligent — understanding each customer’s full context, privately and in real time, without ever collecting their data.

Whether tailoring product bundles to lifestyle shifts, adjusting recommendations based on seasonal routines, or anticipating moments of need with emotional intelligence, retailers can offer smarter, more empathetic experiences — powered entirely by data the customer chooses to share. With Private Personalisation, the value is mutual, the experience is elevated, and the data and AI always stay in the customer’s hands.

Why Retail Needs a New Paradigm: Omnipersonal

From Omnichannel to OmniPersonal: Why Retail Needs a New Paradigm

Omnichannel solved the consistency problem. Whether a customer shops in-store, online, or on mobile — the experience feels unified.

But connected doesn’t mean personal. Most customers still receive generic promotions, irrelevant recommendations, and loyalty rewards that don’t reflect their actual lives. We achieved omnichannel. We haven’t achieved OmniPersonal.

The reason is structural. Cloud-based personalisation can only work with the data it can collect: purchase history, browsing behaviour, survey responses. A narrow window into a complex life. A customer’s dietary restrictions, health goals, household makeup, fitness routine, budget pressures, seasonal needs — all sit outside the retailer’s data environment. On the customer’s phone, scattered across health apps, calendars, and daily habits.

74–80% of enterprise AI initiatives fail to deliver ROI. The promise of AI-driven retail personalisation is real. But the data access problem means most implementations fall short.

74–80% of enterprise AI initiatives fail to deliver ROI
— BCG/McKinsey 2025

Intelligence Where Your Customers Data Lives

DataSapien solves the data access problem at its root: our technology enables you to process personal context where it already lives — on the customer’s own device.

Our SDK (Software Development Kit) easily plugs into your existing retail app and accesses a far richer picture of each customer’s life than any cloud platform can ever reach: health data, location patterns, dietary needs, household context, fitness goals, and more. All processed locally, in real time, from deterministic rules through machine learning to on-device generative AI. The customer chooses what, if anything, to share back as Zero-Party Data.

This is the leap from Omnichannel to OmniPersonal: every touchpoint becomes contextually aware of what matters to each customer right now, while keeping their personal data private. Intimately personal experiences that customers trust, delivered through the omnichannel infrastructure you’ve already built.

Key capabilities

Contextual Product Recommendations Go beyond purchase history. Recommendations that factor in dietary restrictions, health conditions, lifestyle goals, seasonal routines, household needs — all processed privately on-device. Not demographic segments like ‘active women 25-34’, but individual contexts: the runner training for a marathon who’s also managing type 2 diabetes. The new parent navigating allergies and sleep deprivation. The professional trying a GLP-1 diet while travelling for work.

🟠 Intelligent Meal Planning & Nutrition

The top unmet customer need in grocery retail is dietary support. DataSapien enables personalised meal planning that accounts for allergies, weight management, type 2 diabetes, GLP-1 diets, fitness goals, and more — matched to your catalogue and current promotions. The app understands the job each customer is trying to get done, not just the products they might buy.

🟠 Emotional Intelligence at Moments of Need

Customers don’t always shop rationally. Life events, stress, seasonal changes, emotional states all influence purchase behaviour. On-device AI detects contextual signals and adapts the experience — offering support, not just products.

🟠 OmniPersonal Loyalty

Transform your loyalty programme from generic points collection into a participatory relationship. Customers privately share their context and receive offers genuinely relevant to their current life. You earn deeper brand connection; they feel understood and valued.

🟠 Real-Time Journey Orchestration

Design, test, and deploy customer journeys through the DataSapien Orchestrator — with fine-grained audience targeting, rapid A/B and multivariate testing, and no app store approval cycles.On Device Data + Private Cloud LLIn this video, we demonstrate how to deploy Edge AI into mobile applications, specifically showcasing a compact LLM running on a smartphone. We walk through an example of generating a one-week meal plan using personal data and various models, including Llama. The goal is to illustrate the versatility of our platform across different algorithmic models and data sets. It also hints at how the technology can be used in many different verticals, from travel and finance to health and government.

Retail ‘How-To’ Demonstrations

We’ve built a series of working demonstrations showing how Device Native AI transforms the retail experience. Focusing on Grocery retail, each demo showcases a different type of AI-assisted customer journey. Every DataSapien account comes with a free SandBox app (iOS and Android), showcasing these and many other demonstrations.

Adding Edge AI To Any App

In this video, we walk you through how we can integrate Edge AI into existing and new mobile apps, focusing on meal planning applications for Grocery Retail. We demonstrate how the app addresses the top unmet customer needs in Grocery Retail, particularly dietary restrictions and preferences. The app allows users to input their health goals and dietary needs, making meal planning easier and more personalised. The dietary restrictions catered to could cover any customer need, for example: weight-loss, allergies, type2 diabetes management, Bulk-Up, or specialist GLP1 (e.g. Ozempic) diets etc.

On Device Data + Private Cloud LLM

In this video, we demonstrate how to embed Edge AI into existing mobile applications using Google Takeout data and a private LLM connected to the Ocado Grocery API. We focus on a meal planner example, showcasing how data can be pulled from devices to create personalised meal plans with a private LLM, that can then be checked and ‘made safe’ by rules and deterministic AI elements held on the Smartphone.

Data and AI Driven Journey Orchestration

In this video, we demonstrate how to easily embed Edge AI into existing mobile applications using our Orchestrator. We explore a meal planner example, showcasing how data can be structured and manipulated in real-time without the need for lengthy app approval processes. I emphasise how our platform allows for rapid iteration and A-B / Multivariate testing with fine grained audiences, selected based on any data attribute.

Universal AI On The Edge

In this video, we demonstrate how to deploy Edge AI into mobile applications, specifically showcasing a compact LLM running on a smartphone. We walk through an example of generating a one-week meal plan using personal data and various models, including Llama. The goal is to illustrate the versatility of our platform across different algorithmic models and data sets. It also hints at how the technology can be used in many different verticals, from travel and finance to health and government.

The OmniPersonal Architecture

OmniPersonal Retail isn’t a replacement for your omnichannel infrastructure — it’s the intelligence layer that makes it deeply personal. Your existing app, your catalogue, your CRM, your promotions engine — they all stay. DataSapien adds the on-device AI that transforms generic touchpoints into contextually aware, intimately personal moments.

DataSapien’s platform has three components that work together to deliver OmniPersonal Retail experiences:

The SDK embeds into your existing iOS or Android retail app — typically in hours, not months. It creates a private data store on each customer’s device and runs a multi-tiered intelligence engine locally: deterministic rules for precision, machine learning models for pattern recognition, and small language models for conversational AI — all with guardrails to ensure safety and accuracy.

The Orchestrator is your control surface. Design customer journeys visually, define audience segments based on any data attribute, deploy A/B and multivariate tests, and iterate in real time — without app store approval. Connect to your existing catalogue, promotions engine, and CRM through our API-first architecture.

Intelligence provides the platform infrastructure: hosted on Azure, enterprise-ready, with identity management, data science training environments, and integration into your existing Customer Data Platform, CRM, and analytics stack.

Data never leaves the customer’s device unless they choose to share it. You control the experience. They control their data. The result:

• ~44X engagement
• 25%+ activation uplift
• 100% compliance
• Zero of the most sensitive personal data in your cloud

See OmniPersonal Retail in Action

Whether you’re a grocery chain, fashion retailer, beauty brand, or luxury house — we’ll prepare a personalised demo showing how OmniPersonal Marketing works for your specific retail category.

Tell us about your challenge, and we’ll show you what’s possible — with a walkthrough tailored to your use case.