Vastraa Fashion's 14-store chain was spending on ads that seemed to be just moving existing store customers online. Here's how distinct promo codes and store-visit tracking proved the online push was adding real revenue, not cannibalising it — and delivered 3.2x ROAS on ₹22L a month.
Vastraa Fashion
14-store fashion & apparel retail chain across Tamil Nadu
Unproven online spend
Rising online orders, flat total revenue, suspected store cannibalisation
6 months
Omnichannel performance marketing program
Performance Marketing
Store-visit & incrementality attribution
Vastraa Fashion had run 14 stores across Tamil Nadu for over a decade and launched its online store two years before we arrived. Online orders were climbing every quarter — but total company revenue was flat, and the CFO had a growing suspicion the online campaigns were simply pulling customers who would have walked into a store anyway, especially in pincodes with a Vastraa outlet already nearby. The previous agency reported a single blended ROAS number and traffic growth, with no way to separate a genuinely new online customer from a store regular who'd just switched channels. Store managers were quietly blaming the online push for softening in-store footfall. Three months before we started, the CFO had given the marketing team an ultimatum: prove the online spend was adding revenue, not just moving it around, or the budget gets pulled entirely.
Mapped every store's catchment against the last 12 months of online order data to find where cannibalisation was actually plausible versus where it was assumed.
Issued a unique code for every combination of channel and store catchment, so redemptions could be traced back to the exact campaign that drove them.
Paused online ads entirely in a matched set of catchments while running normally elsewhere, isolating the true lift the campaigns were producing.
Reallocated budget away from channels that were mostly capturing existing demand and toward the ones the holdout test showed were generating new customers.
Rolled out direction-tap and in-store QR tracking across all 14 stores, tying online ad exposure to footfall, not just online checkout.
Delivered a monthly incrementality report the CFO could act on, splitting every rupee of ad spend into net-new versus shifted revenue.
Holdout tests, not attribution models, settle the cannibalisation question. The geo holdout revealed that stores near "paused" catchments saw no footfall lift versus stores where ads kept running — proof the online push was net-new demand, not redirected walk-ins.
Media mix rebuilt around the channels the holdout test proved were adding revenue, not just capturing existing demand.
Up from an unproven 0%, confirmed through geo holdout testing and per-store promo-code redemption data.
Stores closest to the heaviest online spend saw footfall rise, not fall — the opposite of the cannibalisation the CFO feared.
"Our CFO was three months from pulling the entire online budget because nobody could prove it wasn't just stealing from our own stores. The holdout test and the per-store promo codes gave us numbers he actually trusted — and it turned out the online push was growing footfall near our busiest stores, not draining it."
Incrementality figures come from a geo holdout test (ads paused in a matched set of store catchments) combined with distinct promo codes issued per channel and store, reconciled against POS footfall data. ROAS and spend are reported from Meta and Google Ads platforms cross-referenced with the client's finance team, tracked over the 6-month engagement stated above. As with every case study we publish, the methodology and baseline are stated plainly.
We'll check how your stores and online channels currently show up to shoppers, benchmark you against 5 competitors, and map out the store-visit tracking that would tell you, store by store, whether your digital spend is genuinely incremental. Free, and useful even if we never work together.
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