Predictive Analytics Consulting

Group customers by behavior, value, and needs—not just demographics. We run clustering on purchase cadence, AOV, product affinities, and engagement signals, then convert clusters into operational “personas” with clear inclusion rules. Each persona ships with targeting criteria, content themes, and product/pricing levers. Segments sync to your CDP, ad platforms, and CRM for campaigns, upsell, and retention plays.

Forecast what each customer or account is likely to spend over time and how cohorts decay. We use BG/NBD and machine-learning regressors to project spend and repeat probability, layered with cohort curves by acquisition source, region, or product line. The result: LTV by segment and channel, break-even CPAs, and budget allocation guidance. Dashboards show LTV shifts as pricing, promotions, or onboarding change.

Serve the next product, content, or action with a ranking model tuned to business goals (revenue, margin, engagement). We blend collaborative filtering with content features (attributes, embeddings) to handle cold start and long-tail items. Policies manage constraints like margin floors and exclusions. Recommendations plug into web/app/API, email, and POS, with A/B and bandit testing to learn quickly.

Predict demand at daily/weekly cadence with seasonality, promotions, price, inventory position, and external drivers (weather, macro, events). We build hierarchical forecasts across SKUs, stores, and regions with calibrated prediction intervals for supply and finance. Planners get scenario tools for “what if” changes — new promo depth, price moves, or assortment shifts — before committing inventory.

Quantify price elasticity and uplift, then recommend prices and offers that hit revenue or margin targets. We estimate cross-effects and cannibalization, simulate outcomes, and solve a constrained optimization under guardrails (MAP, category roles, competitor bands). Merchandisers can review them via a “what-if” simulation tool, or optionally push changes automatically via API.

Balance service levels and carrying costs using demand variance, lead times, and supplier constraints. We set safety stock and reorder points per SKU-location, support multi-echelon flows, and flag exceptions (lumpy demand, substitutes, end-of-life). Outputs integrate with ERP/WMS to create purchase proposals and transfer orders, cutting stockouts and aged inventory.

Prioritize accounts by close likelihood and expected value. Features include firmographics, intent data, web/app behavior, sequence of touches, and email engagement. Scores sync to CRM with reason codes so sales sees “why now.” For revenue ops, we calibrate stage-to-close curves, identify slip risk, and produce a probabilistic forecast with confidence bands for the quarter.

Catch payment fraud, promo abuse, claims anomalies, or account takeovers in real time. We combine supervised models with unsupervised techniques (isolation forests, autoencoders) and graph analysis to surface rings and synthetic identities. Alerts include risk scores, contributing signals, and entity links for investigators. Connectors support payment gateways, claims systems, and security logs; decisions and outcomes feed back for continuous learning.