Convert more and more profitably
Decision Deck helps retailers choose the right commercial action for each customer, basket and moment. Reduce checkout drop-off. Use incentives only where they change the outcome. Recommend products that protect margin. Act earlier when customers, baskets or demand start to move.
Higher conversion · larger baskets · less discount waste · stronger margin.
Checkout friction becomes a decision, not a lost sale
Customers abandon checkout for different reasons. Some need a better payment option or reassurance. Some are price sensitive or stuck. Some are only browsing. Treating every hesitation the same wastes margin and misses recoverable sales.
Decision Deck helps identify what might be blocking the purchase and selects the action most likely to complete the order profitably.
Components used
- Predictive models
Estimate purchase completion, abandonment risk, payment failure likelihood and response to intervention.
- Behavioural Dynamics ↗
Reads session behaviour, hesitation, repeated edits, device context, prior visits and checkout movement.
- Recommendations Block ↗
Selects the best next action: simplify the step, offer chat, change payment option, show reassurance, offer incentive or leave the customer alone.
- Noise Resilience ↗
Separates normal browsing behaviour from real abandonment signals.
- Monitoring
Tracks which actions actually improve completed orders.
Stop discounts leaking margin
Discounts can save a sale. They can also train customers to wait. The challenge is knowing when an incentive will change the decision and when it simply gives away margin.
Decision Deck helps decide whether to offer an incentive, what type to use and when to hold back.
Components used
- Predictive models
Estimate conversion uplift, price sensitivity, order value, margin impact and likelihood to buy without incentive.
- Behavioural Dynamics ↗
Reads whether the customer is stuck, comparing, returning with intent or waiting for a deal.
- Recommendations Block ↗
Selects the right incentive or non-incentive action: free delivery, bundle offer, loyalty benefit, product reassurance, service prompt or no offer.
- Policy Dynamics ↗
Sets incentive rules by margin, stock, customer state, campaign limits and brand constraints.
- Monitoring
Tracks offer fatigue, repeat discount dependency and margin impact.
- Evidence Vault ↗
Records why an incentive was shown, suppressed or changed.
Recommendations become commercial decisions
A product recommendation can increase revenue, reduce margin or damage the customer experience. The most clickable product is not always the best product to show.
Decision Deck recommends the product, offer or next action that fits the customer, the basket and the commercial objective.
Components used
- Recommendations Block ↗
Ranks products, offers or actions based on customer fit, expected outcome and business objective.
- Matching Block ↗
Connects the customer, basket, browsing history, purchase history, product affinity and similar journeys.
- Multi-output models
Estimate conversion, margin, return likelihood, repeat purchase and likely customer value together.
- Policy Dynamics ↗
Filters out unsuitable, unavailable, low-margin or strategically restricted recommendations.
- Demand & Capacity Intelligence
Takes stock, delivery pressure and fulfilment constraints into account before an item is promoted.
Basket growth protects margin
Upsell and cross-sell can grow order value. They can also push the wrong item, increase returns or discount away the profit. Retailers need to know which basket action creates real value.
Decision Deck identifies where a larger, better or more profitable basket is available without damaging conversion.
Components used
- Predictive models
Estimate attachment likelihood, margin contribution, return risk and effect on order completion.
- Recommendations Block ↗
Selects the best add-on, bundle, upgrade, warranty, delivery option or offer.
- Behavioural Dynamics ↗
Reads intent, urgency, sensitivity to price, category behaviour and loyalty state.
- Policy Dynamics ↗
Controls which bundles, thresholds and offers are allowed by margin, stock and customer segment.
- Forecasting
Estimates demand and stock pressure before pushing products that may create fulfilment issues.
Meet returning customers with the right next action
A customer who has stopped buying may need a reminder, a better offer, a new category, service recovery or no contact at all. Blanket campaigns create noise and burn margin.
Decision Deck helps identify what kind of customer movement is happening and selects the action most likely to protect lifetime value.
Components used
- Predictive models
Estimate churn risk, repeat purchase likelihood, customer value and response to different actions.
- Behavioural Dynamics ↗
Reads changes in purchase cadence, browsing, category movement, contact fatigue and service history.
- Risk Stratification ↗
Separates high-value recovery, normal inactivity, low-value discount dependency and customers at risk of leaving.
- Recommendations Block ↗
Selects the right action: product prompt, category offer, service route, loyalty benefit, reminder, suppression or win-back.
- Policy Dynamics ↗
Controls contact frequency, incentive limits and customer treatment rules.
Grow revenue without giving away the margin
Decision Deck helps retailers choose the right action at the moment it matters: checkout, offer, recommendation, basket, fulfilment, recovery and retention.
Use it to improve conversion, lifetime value and margin with decisions that learn from outcomes.