Shifting budget from weak categories to 7.6× winners

Challenge

One personal care appliances account spanned many categories. Top lines carried the P&L at roughly ~7.6× ROAS on more than ₹1 Cr of ad spend. Weaker categories sat closer to ~1.3–1.6×. Hand-editing budgets across Sponsored Products, Brands, and Display meant low-return lines still absorbed spend while winners waited for someone to notice—and revenue growth stalled where it should have compounded.

Agencies and in-house teams faced the same ops problem: too many campaigns, one Friday export ritual, and no shared rule pack that funded what worked.

Approach

In Sapyon, the team defined reusable budget and performance rules—ROAS floors, spend pace, and time windows—then applied them across categories instead of campaign-by-campaign guesswork. Ranked AI recommendations gave managers a prioritized queue: protect top-category efficiency, pressure weaker lines, and stop equal-budget thinking.

One reporting view replaced stitched exports, so agency leads and brand owners shared the same source of truth for revenue and ROAS—across ~₹9 Cr of attributed revenue at a blended ~6.7× ROAS in the full window.

Results

In 12 months, attributed ad revenue grew about 5.4× (same calendar month, year over year), while overall spend scaled nearly 5× without collapsing efficiency. The operating model stayed clear: put weight behind categories that already return ~7.6×, and stop treating ~1.3–1.6× lines like they deserve equal budget.

Across the full measured window the account delivered on the order of ₹9 Cr attributed revenue at ~6.7× blended ROAS. If you run Amazon for a multi-SKU personal care appliances brand—or an agency book that looks like one—this is why rules beat manual edits: winners get funded, waste gets constrained, and revenue compounds on one dashboard.