Demand volatility, inventory mismatches, and pricing inefficiencies limit growth. We unify signals across channels to enable real-time demand sensing, inventory optimisation, and margin-aware pricing decisions.
Optimise pricing, promotions, and markdown decisions using demand elasticity models and real-time competitive signals to protect margin at scale.
Reduce out-of-stocks and overstock exposure with shelf-level demand sensing, replenishment models and planogram compliance tracking.
Deliver individually relevant offers and content by building customer propensity models, lifetime value segments and next-best-action engines.
Connect supplier, warehouse, and last-mile data to improve lead times, reduce landed costs and build resilience against demand shocks.
Measure store and workforce efficiency through operational KPI dashboards that surface bottlenecks and guide labour allocation decisions.
Automate regulatory and policy monitoring across product data, pricing rules and labelling requirements to reduce audit risk and operational overhead.
Attribute revenue across paid, owned, and earned channels with unified measurement frameworks that go beyond last-click to true incremental impact.
Score, benchmark, and monitor supplier performance using delivery, quality and cost data to strengthen negotiation and reduce dependency risk.
Build data-driven range decisions using category affinity analysis, localized demand signals and space-to-sales optimization models.
Track conversion funnels, search ranking drivers, and basket behavior across digital channels to improve discovery, engagement and checkout rates.
Surface the metrics that matter to each business function through role-specific, near-real-time dashboards that replace fragmented spreadsheet reporting.
Unify customer identity and behaviour across in-store, online, and app touchpoints to create a single source of truth for cross-channel decision-making.
Apply machine learning to demand, sales, and return forecasting to sharpen planning cycles and reduce reactive decision-making across the business.
Quantify the contribution of each marketing channel to sales outcomes and optimise budget allocation using econometric models calibrated to your data.
Segment, profile, and score your customer base to identify high-value cohorts, predict churn and target acquisition spend where it generates the most return.
Most businesses treat all customers the same, overlooking the customers who drive the most long term value. Without a clear understanding of customer lifetime value, marketing remains generic and high potential customers are often ignored. A leading US retailer faced this challenge while scaling its ecommerce business without a centralized view of customer data. ZDS built a unified customer view, segmented customers based on behavior, and estimated lifetime value to help the business target the right customers with more focused strategies.
Customer intelligence gaps quietly limit retail growth because businesses cannot identify which in store shoppers are most likely to engage across channels and increase long term value. One of the largest retailers in the United States, operating nearly 5,000 stores and serving roughly 240 million customers each week, partnered with ZDS to build an omnichannel lookalike modelling system using more than 200 behavioral variables. The solution identified high potential shoppers, enabled targeted adoption campaigns, and surfaced nearly 1.7 million likely omnichannel customers.
Behavioral intelligence systems that improve unclear user journeys into stronger monetization and sharper customer segmentation. Most digital products struggle when user behavior stays fragmented because feature adoption, retention, and monetization decisions become difficult to scale. A global technology company launching a collaborative application built a multi-stage behavioral modelling framework to classify users, identify high-value engagement patterns, and improve paid user conversion by 24% while creating reusable customer intelligence capabilities.
Tell us about your data challenge and we'll come back with a clear, actionable plan — no jargon, no fluff, just a path forward.
