The reliable spine
The reliable spine is deterministic: actual store revenue against actual spend, the account's own ROAS floor, true blended CAC after COD and RTO loss, and the courier-weight and returns arithmetic by SKU, channel and pincode.
Retail & D2C
Ad-spend and true-blended-margin leak sweep
The business is profitable on paper but quietly leaks rupees through ad sets running below the account's own break-even, through ROAS reported better than the real blended return, and through a CAC that ignores the COD and RTO loss riding on every order. The leak is real money, it is in the brand's own ad and revenue data, and it is recoverable by reallocation. Two silent leaks sit in the brand's own dispatch and order data: couriers bill on a charged weight that drifts above the catalog weight, and returns and RTO carry forward-and-back freight, handling and resale loss concentrated by SKU, channel and pincode. Both are accepted unread because nobody has time to tie every shipment back or to quantify the return loss by line.
Who has it
D2C / online-first consumer brands feel the ad-spend read most, and it is the cleanest found-money read in the sector for any marketplace-led seller, omnichannel retailer or retail chain running meaningful paid spend. The courier-weight and returns/RTO read sits with D2C brands, marketplace-led sellers and omnichannel retailers, and with retail chains shipping online, and is sharpest where COD share is high.
What we build
A sweep that reads Meta and Google spend against actual store revenue (not platform-reported), flags ad sets and campaigns burning budget below the account's own ROAS floor, and exposes true blended CAC after COD and RTO loss. A quantified, line-level read, then a recurring sweep that keeps catching the drift. A courier-weight-dispute read (billed versus catalog weight, with the clawback rupees and the evidence) and a returns and RTO margin read that quantifies silent loss by SKU, channel and pincode so the brand can see which products, channels and areas are costing it. The findings feed the pincode-serviceability and courier-allocation rules so the worst pincodes get COD friction or a prepaid nudge.
What is automated, where AI helps, who signs off
Automation for the routine. A person on every decision that matters.
Where AI helps
AI reads the messy ad exports, settlement files and shipment data, matches spend to real orders, and clusters the loss by SKU, channel and pincode so the leaks rank themselves; the cut or the dispute is a human call.
Who signs off
A named person signs off anything touching money, stock, a customer promise, a payment, a price, a credit decision or people; the sweep surfaces the recoverable rupees, it does not reallocate spend or raise a claim by itself.
What changes day to day
Loss-making ad sets surface while they can still be cut; the founder sees true blended CAC and real ROAS; spend follows the brand's own arithmetic instead of platform-reported numbers. Charged-weight overcharges get caught and disputed; the brand sees exactly which SKUs, channels and pincodes its returns and RTO are bleeding into, and acts on the worst ones.
Illustrative outcome
Ad waste identified and reallocated; true blended CAC made visible, all traced to the brand's own accounts. Recovered courier-weight clawbacks; quantified returns/RTO loss that drives the worst SKUs and pincodes to a fix. Illustrative; final numbers come from your own data.
Illustrative; final numbers come from your own data.
Path to the build
How this one gets built.
Book a free 60-minute call, then a free Blueprint on the firm's own records. Deep-dive and build, followed by run and govern so the workflow keeps paying back.
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