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.
Pittsburgh, PA
Google Ads Management in Pittsburgh, PA
Capturing the demand that already exists in Pittsburgh's search results — starting in Merchant Center, not the campaign builder.
Delivered remotely for brands across Pittsburgh and Pennsylvania.
Grow · Pittsburgh
Why Pittsburgh brands come to us for this
- Merchant Center feed rebuilt for technical catalogues: identifier handling where no GTIN exists, titles rewritten to searched language
- Price and availability mismatch disapprovals traced to the ERP sync rather than resubmitted and hoped over
- Brand separated from non-brand, because a decades-old Pittsburgh name flatters blended ROAS
- Negative library maintained weekly against student, job-seeker, datasheet and repair-instruction queries
- Merchandise campaigns and budgets pre-built in August with trigger conditions for a playoff run
A replacement bearing, a case of the imported olive oil, a jersey before Sunday — the decision is already made, and the only open question is who sells it. On Shopify that competition is settled in Merchant Center rather than in the campaign builder, which is why the first month of a Pittsburgh engagement is usually spent in the feed rather than in bidding.
Technical catalogues break feeds in specific, repeatable ways. Manufactured parts frequently have no GTIN, so brand and MPN have to be right and the identifier-exists declaration handled properly or the products simply stop competing. Titles are exported straight from an ERP and read like internal SKU names, which means they never match the phrase a buyer types. Product types mirror an internal hierarchy nobody outside the building uses. Pricing and availability drift out of sync with the ERP and trigger mismatch disapprovals that nobody sees because nobody opens the diagnostics tab. Fixing that moves revenue before a single bid changes.
Then structure. Brand gets separated from non-brand, which matters more here than in most markets because a lot of these companies have a name that has been on a building since the 1940s — branded search looks like performance and is mostly people who were always going to call you. Performance Max asset groups get split by margin band and stock cover rather than run as one catch-all. Search covers the query space a feed cannot reach: cross-references, application questions, competitor part numbers. Bidding to contribution margin comes last, in controlled increments, with a written reason attached to every change.
Local context
The query set here is full of people who will never buy
Pittsburgh accounts leak budget in a very particular way, and it is almost always visible in the search terms report. A metro with a heavy industrial base, two large universities in Oakland and a robotics cluster generates enormous volumes of non-commercial search around exactly the terms you sell: students researching a material for coursework, engineers looking for a datasheet with no procurement authority, job seekers searching a trade plus the city, and people looking for repair instructions rather than a replacement part. Left alone, Performance Max will happily spend against all of it. We maintain a shared negative library that gets a weekly pass, mine PMax category reports for the same patterns, and separate the queries worth serving with a datasheet from the queries worth serving with a buy button. On the consumer side the shape is different again: fan merchandise demand spikes on results, not on schedule, so campaigns and budgets are pre-built in August with clear triggers rather than assembled in a hurry after a win.
Scope
What Google Ads includes
The same standard of work we run for every client — applied to a Pittsburgh brand’s realities.
Full service detailBrand, Non-Brand & Conquesting
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.
Shopping & Performance Max Structure
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.
Query Mining & Negative Hygiene
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.
Promotions & Merchant Programs
Merchant promotions, sale price annotations, shipping and returns policy setup, product ratings, and local inventory ads where you have stores worth feeding.
tROAS Bidding to Contribution Margin
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.
Scoped and quoted for your Pittsburgh store
We do not work off a rate card. Every Pittsburgh 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 scopedHow it runs
From kickoff to results
Feed & Account Audit
Merchant 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.
Fix the Feed
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.
Restructure
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.
Bid to Margin
tROAS targets derived from contribution margin by product group and applied gradually, so the account keeps its learning instead of resetting it every Monday.
Mine & Expand
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.
Proof
Google Ads results
Anonymised under NDA. Figures pulled from the client’s own analytics.
Performance Apparel (DTC)
~$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.
+29%sitewide conversion rate1.71% to 2.21%, five-month average
+14%average order value$84 to $96 once the threshold bar and cross-sell shipped
31% → 22%return ratenine-point drop, roughly $310k/yr in recovered margin
1.9x → 2.4xblended MERwith paid spend held flat throughout
Consumer Electronics & Accessories
~$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.
1.9x → 3.4xMeta ROAS, once the 22% event gap closed60 days after server-side tracking went live, spend up 18%. Most of that is signal we recovered, not performance we invented — the honest number is the blended CAC below, which is measured against Shopify orders
-32%customer acquisition cost$44 to $30 blended across Meta and Google
4.1s → 1.7smobile LCPdesktop went 2.9s to 1.2s over the same window
+47%peak-season revenueBlack Friday through Cyber Monday, year over year
In their words
Clients on this work
Non-brand search revenue ~2x at flat spend
“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.”
Director of OperationsKids & baby brand, ~$5M/yr · Atlanta, GA
Verified via Shopify Partner referralFAQ
Google Ads in Pittsburgh — your questions
Yes. For products you manufacture, brand plus MPN with the identifier-exists attribute handled correctly is the accepted route, and Google serves them normally once it is set. What breaks accounts is leaving the field blank or filling it with a placeholder, which produces intermittent disapprovals that look random. It is a feed configuration problem, not a limitation on your business.
Keep it, but not first. The part number matters because buyers do search it, so it belongs in the title — after the words that describe what the thing is. A title that leads with a code matches almost nothing, while a title with the product type, key specification, brand and then the number matches both the specification search and the part-number search. That single change is often the largest Shopping lift available.
With a negative library that is maintained rather than written once. Coursework, datasheet, salary, apprenticeship, hiring and how-to-repair patterns get added continuously from the search terms report, and PMax category reports get the same treatment since the search terms there are less visible. We also review what a genuine research query should be served — sometimes a datasheet landing page is worth the click, and that is a decision rather than an accident.
By importing the outcomes Google cannot see. Quote requests and calls get tracked with a click identifier, and when the deal closes in the ERP the value is imported back as an offline conversion. That lets bidding optimise toward orders that actually happened rather than toward form fills. Until that loop exists, we optimise on qualified quote volume and say plainly that it is a proxy.
Yes, once the feed and the exclusions are right. PMax on a clean feed with margin-segmented asset groups and brand controls is the strongest Shopping vehicle Google has shipped. PMax on a neglected feed is an expensive way to sell bestsellers to people who were buying anyway.
Because Shopping never sees your keywords, only your feed. Title, product type, GTIN and attributes decide which queries you are even eligible for. We routinely find a quarter of a catalogue disapproved or serving on the wrong terms, and fixing that moves revenue before a single bid changes.
Usually yes, but as a separate campaign with its own target and its own conversation. Branded clicks are cheap and convert well, which is exactly why blending them into non-brand hides whether the rest of the account works. Where the spend is material we run a holdout to see what is genuinely incremental.
Next step
Google Ads for your Pittsburgh brand.
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.
Shopify or Shopify Plus stores doing $150k/mo or moreFounder, CEO or eCommerce lead on the callNo deck and no pitch — we open your store instead
Prefer to write it out? [email protected] gets a real reply the same business day, Mon-Fri, 9am-6pm MT.