Merchant Center & Feed Rebuild
Disapprovals cleared at source, GTIN, MPN and attribute gaps closed, and titles rewritten to lead with searched terms. Custom labels for margin, stock cover and seasonality.
Shopping, Performance Max and Search built around a Merchant Center feed that satisfies German requirements before a single bid is touched.
Delivered remotely for brands across Berlin and Germany.
The Berlin buyer has already decided they want a 1000-watt cargo bike or a specific desktop synth; the only question left is who supplies it. On Shopify that contest is decided in Merchant Center, not in the campaign builder, and German feeds carry requirements that an American account never encounters. Unit-price attributes are expected wherever the price-indication rules apply, which covers most food, drink and cosmetics catalogues. Energy-labelling data is required for the electronics categories that fall under EU rules. Missing either does not produce an error your team notices — it produces products that quietly stop serving.
Structure comes second and matters more than people think, because German brand names are frequently ordinary German words. If your brand term overlaps a category noun, brand and non-brand blended into one campaign will produce an excellent ROAS that tells you nothing about whether the account works. We isolate branded demand into its own campaign with its own target, so non-brand performance becomes a number you can act on rather than an average hiding behind it.
Then the auction context. In German categories the Shopping results are frequently occupied by Amazon.de, price-comparison portals and large domestic retailers with a cost base you cannot match. The response is not a higher bid; it is a feed segmented by margin and stock cover, PMax asset groups split accordingly, and query mining aggressive enough to stop budget draining into research and comparison traffic that was never going to buy from a brand.
Two things change materially about a Google account run out of the EEA. First, Shopping ads in Europe can be served through a Comparison Shopping Service rather than through Google Shopping directly, and which CSS your feed runs under affects what you effectively pay to appear in the same slot — it is a structural decision most Berlin accounts we audit have never consciously made. Second, the feed itself has to satisfy German and EU attribute expectations: unit pricing for consumables so a coffee or cosmetics feed is complete, energy-efficiency data where the category demands it, correct shipping and returns policy per country, and tax-inclusive pricing that matches the storefront exactly, because a mismatch between feed price and landing-page price is the single most common disapproval we clear. On top of that, the three DACH markets need separate campaigns rather than one euro-priced blur: Austria takes the euro catalogue with its own delivery reality, Switzerland needs francs, its own feed and a clear duty position, and mixing them produces bids against wildly different margins under one target. We build the account per market, per margin band, in that order.
The same standard of work we run for every client — applied to a Berlin brand’s realities.
Full service detailDisapprovals cleared at source, GTIN, MPN and attribute gaps closed, and titles rewritten to lead with searched terms. Custom labels for margin, stock cover and seasonality.
Branded demand isolated into its own campaign, budget and target so non-brand performance becomes visible. Competitor conquesting runs as a separate line, judged separately.
Asset groups split by margin band and product type instead of one catch-all, with listing-group bids, product exclusions and brand-term controls applied wherever PMax still allows them.
A weekly pass over search terms and PMax category reports, with a maintained shared negative library so budget stops leaking into research, DIY and job-seeker queries.
Merchant promotions, sale price annotations, shipping and returns policy setup, product ratings, and local inventory ads where you have stores worth feeding.
Targets set from margin per product group rather than a platform default, moved in controlled increments, with a written reason attached to every bid and budget change.
We do not work off a rate card. Every Berlin engagement starts with a fixed statement of work — named deliverables, named dates, one number — written after we have looked at your store, not before. If a smaller first step would serve you better, we will say so.
Get this scopedMerchant Center diagnostics, attribute coverage, campaign overlap and wasted spend scored against ninety days of search terms. You get the findings whether you hire us or not.
Titles, attributes, product types and custom labels rebuilt before any campaign work. A perfectly structured account on a bad feed still shows the wrong products to the wrong queries.
Brand, non-brand, Shopping, PMax and Search rebuilt with hard budget boundaries and a shared negative library, so each line answers a different commercial question.
tROAS targets derived from contribution margin by product group and applied gradually, so the account keeps its learning instead of resetting it every Monday.
Weekly query mining, monthly feed reviews, then expansion into the categories the search data says you can profitably win. Nothing scales before the query set is clean.
Anonymised under NDA. Figures pulled from the client’s own analytics.
~$6M/yr DTC, 900+ SKUs across size and colour variants, US · Shopify Plus
Returns ran at 31% and refund cost consumed the entire paid media margin. One size chart image served 40 different fits, and 62% of add-to-carts started on a collection page that never showed variant availability. The named constraint: no new product photography budget, so every fix had to come out of the existing asset library and the review corpus.
~$9M/yr, 210 SKUs, US + AU · Shopify Plus (migrated from BigCommerce)
Meta ROAS had slid from 3.6x to 1.9x in a year and the team had spent twelve months buying new creative to fix it. The real cause was measurement: the BigCommerce checkout dropped 22% of purchase events and the Conversions API had never been installed, so both ad platforms were optimising on incomplete data. The named constraint: peak season was 14 weeks out, and the replatform had to be live and stable well before Black Friday traffic arrived.
“Six thousand products and a Shopping feed nobody had touched since it was first generated — a third of it was disapproved and we had no idea. They rebuilt the feed off our real product data, fixed the GTIN and size attributes, and split brand off from non-brand so I could finally see what we were actually paying to acquire. They also cut the broad 'baby clothes' terms that were eating a quarter of the budget on people who were nowhere near buying. Spend is roughly flat and non-brand search revenue has close to doubled.”
Thirty minutes with the strategist who would actually run your account. We screen-share your store, read your data live, and tell you the three highest-value things we can see from the outside.
Prefer to write it out? [email protected] gets a real reply the same business day, Mon-Fri, 9am-6pm MT.