The work spans every surface where products are bought. Google Shopping and Performance Max for high-intent search, Meta catalog and dynamic product ads for demand creation and retargeting, and marketplace advertising on Amazon and Flipkart where a growing share of product searches now start. Each channel has its own auction logic and its own failure modes, and treating them as one portfolio, with budget flowing to the surface earning the best marginal return, is where most of the gains hide.

Underneath the campaigns sits the unglamorous work that decides results: feed titles rewritten so products enter the right auctions, GTINs and attributes completed, prices and availability synced so ads never sell what the shop cannot ship, conversion tracking rebuilt so bidding algorithms learn from truth. We treat the feed as the campaign, because on shopping surfaces it is: the auction reads your data, not your ad copy.

Timing matters more in ecommerce than in any other paid discipline. Auction prices swing with the retail calendar, competitors discount in waves, inventory runs out mid-flight, and a product that printed money in October can be a budget leak by January. Our management rhythm is built around that volatility: weekly reallocation, sale events planned like campaigns in their own right, and a promotion calendar wired into feeds and creative so the account is always selling what the business actually wants to move. Set-and-forget is how ecommerce budgets die; supervised motion is how they compound.

We report the way an operator would want: revenue, margin after ad spend, new versus returning customer split, and the honest incrementality of brand spend. The numbers in our results band are from real client engagements, and the same discipline that produced them, test, measure, reallocate, is the rhythm we bring to every account. If a channel or a product segment cannot pay for itself, you will hear it from us first, with the data attached.

Google Shopping and Performance Max. We structure Shopping and PMax around product economics: campaigns and asset groups segmented by margin band, price point, and strategic role, with search themes and negatives keeping queries where they belong. PMax gets supervised, not trusted: placement exclusions, brand traffic carved out, and product-level performance pulled into daylight so winners scale and dead SKUs stop draining budget. The result is an account you can actually steer instead of a black box you hope behaves.

Product feed management and optimisation. Feed quality decides which auctions your products enter and at what quality score. We rewrite titles around real query language, complete attributes, fix GTIN and category mapping, build supplemental feeds for promotions and labels, and keep price and stock sync tight so disapprovals never silently switch off your best sellers. Custom labels encode margin and lifecycle into the feed so every campaign decision can be an economic one. It is unglamorous work, and it moves numbers more than any bid change.

Marketplace advertising (Amazon and Flipkart). Marketplaces are where high-intent product searches increasingly start, and their auctions reward different behaviour from Google's. We run sponsored products, brands, and display with keyword harvesting loops, placement bid control, and ACoS targets set per product role, defending your listings on branded terms while attacking category demand where the margin supports it. The 9.6 percent ACoS in our results band came from exactly this discipline on a marketplace portfolio.

Meta catalog and dynamic product ads. Meta earns its budget in ecommerce as a demand engine: catalog sales campaigns, dynamic retargeting that stops at sensible frequency, and broad prospecting fed by creative built around products people actually buy first. We connect the catalog properly, dedupe audiences against purchasers, and judge the channel on incremental revenue rather than view-through claims, so Meta scales when it deserves to and shrinks when it does not.

Measurement, attribution, and incrementality. Bidding algorithms learn from your conversion data, so we rebuild it first: proper purchase tracking with deduplication, server-side events where the stack allows, consent handling, and new-customer conversion goals where acquisition is the aim. Then we separate what ads caused from what they claimed: brand versus non-brand splits, holdout reads on retargeting, and blended MER guardrails alongside platform ROAS so scaling decisions rest on money arithmetic, not dashboard flattery.

Landing experience and conversion alignment. Clicks are only half the trade; the product page and checkout decide the other half. We audit the post-click path for speed, price parity, stock accuracy, and friction, align promotions between ads and pages, and feed conversion findings back into campaign structure, because a losing auction is sometimes a winning auction with a broken page behind it. Where deeper work is needed, our CRO practice picks it up.