Playbooks

Digital Analytics

1. Acquisition Analysis & Campaign Optimization — Uses ROAS/CAC, CTR, CVR, and First-Order % to find underperforming channels/campaigns, then reallocate budget and fix creative/targeting with Explore follow-ups.

2. Conversion Funnel Optimization — Diagnoses where CVR drops (Traffic → PDP → Cart → Checkout), segments by device/source/geo, and prescribes PDP, UX, and checkout fixes with before/after monitoring.

3. Retention & LTV Growth — Tracks cohorts, repurchase, and RFM segments to raise LTV; pairs UNS engagement with UOS outcomes to trigger win-backs, subscriptions, and VIP programs.

4. Digital Channel Efficiency (Blended ROAS/CAC) — Evaluates the whole mix (paid + owned), compares attribution models, balances brand vs performance spend, and tunes budgets to hit sustainable LTV:CAC.

Grow, Expand & Defend Retail Distribution

1. Distribution & Velocity Overview — Explains how sales decompose into distribution (ACV/TDP) and velocity ($/TDP, units/store/week), then shows how to diagnose growth/decline by separating “more doors” vs “selling faster.”

2. Expanding into a New Retailer — A launch playbook to verify execution (doors live), measure early velocity, size phase-2 upside, and run quick lift tactics (e.g., TPR/demo) to accelerate ramp.

3. Defending At-Risk Distribution — Finds SKUs or accounts at risk (high distribution, low velocity; falling ACV), benchmarks against category, and outlines promo/placement fixes—or when to prepare a rationalized exit.

4. SKU Rationalization (Swap Out) — Ranks SKUs by velocity and contribution, flags low-productivity items, and shows how to model a swap to higher-performing SKUs while managing cannibalization.

5. Assortment Expansion in Existing Retailers — Identifies white-space SKUs per account, projects incremental sales using proven velocities, and packages a data-backed pitch for expanded facings.

6. Best Practices: Data Storytelling for Retail Decks — A narrative framework (context → drivers → proof → ask) with clear visuals (share/growth, ACV vs velocity) to persuade buyers and execs.

Promotional Analysis & Trade Spend ROI

1. Single-Product Promo Tuning — Pinpoints the optimal discount depth and frequency for one SKU in one account by comparing lift vs. baseline erosion, incrementality, and ROI; guides when to go deeper, go shorter, or pull back to protect margin while keeping velocity up.

2. Cross-Market Promo Benchmark — Compares like-for-like promotions across retailers/regions to reveal what truly drives results (depth, duration, feature/display, timing, execution); distills repeatable best practices and retailer-specific plays to raise lift and ROI everywhere.

3. Promo Calendar ROI Planning — Builds a seasonal promotion roadmap that balances goals, budget, and capacity; forecasts event-level lift & incrementals, spaces cadence to avoid over-promotion, and runs plan vs. actual loops to prune low-yield tactics and scale winners.

4. Wholesale Impact & Forward-Buy — Aligns sell-in vs. sell-through during promos to detect forward-buying, quantify true incremental consumption, and adjust deal mechanics (scan-downs, caps, duration) so shipments match demand and post-promo orders don’t crater.

5. DTC→Retail Launch Story — Uses early velocity, promo-driven trial lift, and post-promo baseline to prove retail traction; ties in category/share context and reorder signals to pitch store expansion, backed by a repeatable launch-promo playbook.

Pricing Analysis Optimization & Promotional ROI in Retail

1. Everyday Pricing Analysis — Reviews base vs average selling price, price position vs competitors, and ties price moves to velocity, with guidance on EDLP vs promo cadence and margin tradeoffs.

2. Price Elasticity & Competitor Benchmarks — Estimates elasticity from historical price/volume and promo lift, compares rival strategies, and runs “what-if” pricing scenarios to forecast revenue and profit.