I help consumer durables and apparel brands turn messy field data into decision-ready reporting — store-level sell-through, rep productivity, promo compliance, and out-of-stock visibility your team will actually use.
Not open-ended consulting. Each engagement has a defined outcome, timeline, and price — so you know exactly what you're buying.
A full review of how your store-level and field data is captured, where it breaks, and what it would take to trust it. You get a findings report and a prioritized fix list.
End-to-end reporting your sales and trade teams open every Monday: sell-through by store and SKU, rep productivity, promo effectiveness, OOS alerts.
Your part-time retail data person. I maintain the reporting, answer the "why did this drop?" questions, and prepare your data for AI-assisted analysis.
We map how data flows today — from store visits and apps to spreadsheets — and agree on the metrics that actually drive your decisions.
I clean, model, and connect your data, then build the reporting layer. Every number is validated against source before anyone sees a dashboard.
Your team gets trained, reports refresh automatically, and we review what the data is telling you — so insight turns into action, not decoration.
Delivered for 10+ global and national brands across consumer durables, apparel, smartphones, EV, logistics, and skincare. Names withheld under confidentiality — happy to walk through specifics on a call.
For several of the largest air-conditioning, home-appliance, and electronics brands sold in India — including global Japanese and British names — field teams captured daily sales and stock data from thousands of retail counters through mobile apps. I built and ran the reporting layer on top: sell-through by region, dealer, and SKU, target vs. achievement, and coverage reporting that brand sales leadership used to run weekly reviews.
For a national menswear retail chain, I delivered recurring store-performance reporting — sales vs. target by store, staff-level productivity and conversion, and scheme execution — giving retail operations a single comparable view across the entire store network instead of store-by-store spreadsheets.
Brands that sell through offline retail depend on large deployed field teams — in-store promoters, merchandisers, and sales staff. Across clients in smartphones, electric vehicles, logistics, and skincare, I built the HR reporting that tracked attendance, deployment coverage, attrition, and productivity per head — connecting workforce data to the sales those teams generated.
I'm Vipul Tyagi, an analytics professional based in India. My background isn't generic dashboarding — it's retail execution: working with global consumer durables, appliance, smartphone, EV, and apparel brands whose field teams capture data in thousands of stores through web and mobile applications, and turning that raw capture into the sales and workforce reporting that brand leadership actually runs the business on.
That means I already speak your language: secondary sales, sell-through, promoter productivity, scheme effectiveness, coverage, OOS. And I know the unglamorous part too — the data cleaning, validation, and pipeline work that makes any of it trustworthy, and that makes your data ready for AI-assisted analysis rather than a liability.
Tools I work in daily: Power BI, Tableau, SQL, Python, Excel — plus the modern AI tooling that makes analytics faster when the foundations are right.
A free 30-minute call. Bring your messiest reporting problem — worst case, you leave with a clearer picture of what to fix first.
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