Smart Retail Industry
Track Shopper Behaviour
Capture every customer footprint: clicks, views, purchases, and in-store actions and build a real-time view of shopper intent. This behavioral data fuels machine learning models that deliver personalized recommendations and targeted offers.
With platforms like Nussknacker and Shomnify, retailers can respond instantly to customer actions, improving engagement, increasing conversion rates, and creating seamless, relevant experiences across all channels.
Turn Visits into Conversions
Turn every customer visit into a high-impact moment with real-time insights delivered directly to store staff. As shoppers move through different areas, systems powered by Nussknacker detect presence and preferences instantly, highlighting loyalty status, product interests, and recent interactions.
This empowers POS teams to offer timely, personalized support that feels natural and relevant. The result: stronger engagement, increased sales, and a more dynamic in-store experience that adapts to each customer in real time.
Unified Customer Experience Anywhere
Deliver consistent, personalized experiences across all customer touchpoints - online, displays, in-store, mobile, or call center. Nussknacker seamlessly integrates with any channel, enabling real-time decisioning and business logic to run wherever your customers are. This ensures smooth, unified journeys that adapt instantly to behavior in any context.
Retail Low-Code Solution
Nussknacker is a low-code, drag-and-drop solution for fast-moving smart retail industry. The platform enables teams to act on live data, driving timely decisions and personalized customer experiences. Users can spot in-store and online sessions in real time, allowing action at the "moment of intent". Seamless integration with existing systems, CDPs, and ML models ensures easy adoption.
Because the personalization algorithms are built using a visual interface approach, both personalization teams and developers can create, experiment and tune session detection logic, in-store and on-line activity correlation logic and the recommendation logic.
Designed for Real-Time Data Processing
Retail Use Cases
Personalized ML Recommendation
Hyper-Relevant Suggestions That Convert
Retailers use real-time machine learning to recommend products, bundles, or promotions personalised to individual shopper behaviour. The integration displays live ML results throughout the customer journey - triggering the right recommendation at the right time, whether online or in-store.
POS Engagement
In-Store Intelligence for Frontline Impact
Leverage real-time data at the point of sale to deliver smarter, personalized interactions. Nussknacker enables dynamic prompts based on cart contents, customer profiles, and store context - boosting upsell potential, customer satisfaction, and in-store experience quality.
Marketing Automation System
Always-on, Personalized Campaign Execution
Trigger real-time, behavior-based marketing campaigns without developer involvement. Nussknacker enables marketers to visually build, test, and deploy personalized promotions across omnichannel, improving targeting, speed, and engagement.
Real-Time Fraud Detection
Live Transactions Monitoring and Protection
Monitor transactions and behaviors in real time to detect fraud patterns instantly. Nussknacker applies streaming analytics and business rules to flag anomalies across payments, returns, and loyalty, helping reduce fraud losses and improve security.
Trusted by financial and telecom companies to handle heavy data processing and decision making
Case Studies
Is Your Retail Strategy Real-Time Ready?
Stay ahead of shifting demand, customer expectations, and operational complexity with Nussknacker’s real-time decisioning platform. Empower your teams to act instantly - not eventually. Get in touch and discover how to turn your retail data into ROI today.
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