How a family-run furniture retailer in Germany cut paid catalogue sprawl, rebuilt Shopping and Performance Max around profit, and used a curated 20% of products to drive more than 80% of ad account revenue.

Large catalogues often look like an advantage in Google Ads. Sometimes they are. Sometimes they create catalogue sprawl: too many products eligible for promotion, too much budget spread too thinly, and too little control over which items are actually worth paying to show.

This case study looks at a family-run, multi-location furniture retailer in Germany with more than 8,000 SKUs across bedding, linens, sofas, chairs, tables, indoor-outdoor furniture, tableware, candles, and home accessories. The retailer had already been running Google Ads in-house on and off. That meant the account was not a blank slate. It had useful historical data, established demand in parts of the catalogue, and clear signs that some products could work very well online.

The problem was that too much of the catalogue was being allowed to compete for budget at once. The account was drifting around break-even, spend was leaking into low-viability products, and stronger products were not getting enough room to win consistently.

The job was not to make every SKU work. It was to stop financial loss, increase orders, improve return on ad spend, and make Google Ads commercially dependable again. What followed was less about finding a clever campaign trick and more about rebuilding the operating layer underneath Shopping and Performance Max: feed data, Merchant Center control, campaign segmentation, brand separation, and product-level profit logic.

Quick Takeaways

  • A wide catalogue was diluting budget and hiding the products that could actually carry acquisition cost.
  • We audited the full catalogue and created a supplemental feed with commercial fields such as margin, search volume, price competitiveness, seasonality, and stock availability.
  • Roughly 80% of the catalogue was excluded from direct paid promotion because advertising everything was not commercially sensible.
  • Hero products were separated into dedicated Performance Max campaigns, long-tail product groups were handled more selectively in Standard Shopping, and branded demand was split out more clearly.
  • Merchant Center diagnostics, feed disapprovals, title quality, and disciplined admin work played a bigger role than most advertisers realise.
  • Product titles were enriched around how people actually searched, not just how products were named internally.
  • The account moved from near break-even to a much stronger return on investment, and today the 20% of products promoted through the shopping feed drive more than 80% of ad account revenue.
  • That cleaner product selection and feed logic also created a better starting point for the business’s first test into Austria.

Case Study at a Glance

Area Detail
Business Family-run, multi-location furniture retailer in Germany
Catalogue size 8,000+ SKUs
Product range Bedding, linens, sofas, chairs, tables, indoor-outdoor furniture, tableware, candles, home accessories
Starting point Existing Google Ads account run in-house on and off, broad catalogue coverage, limited budget relative to feed size, performance close to break-even
Goals Stop financial loss, increase orders, improve ROAS, and shift budget towards products that could support profitable acquisition
Main changes Catalogue audit, supplemental feed, custom labels, Merchant Center cleanup, title enrichment, brand separation, Shopping and Performance Max restructure, POAS-led optimisation
Outcome More profitable product clusters, stronger brand performance, better budget concentration, and 20% of promoted products driving 80%+ of ad account revenue
Expansion First Austrian market test built from proven winners rather than starting from zero

The Starting Point: Too Much Catalogue, Too Little Control

This retailer did not have a small or narrow catalogue. It had a wide mix of product types with very different economics:

  • low-ticket and high-ticket products
  • lower-margin and higher-margin lines
  • categories with strong search demand and categories with weaker demand
  • products that could convert on the first click and products that made much more sense as add-ons once someone was already on the site

That matters because a store selling candles, bed linen, dining tables, patio furniture, and sofas is not really dealing with one catalogue. It is dealing with several very different acquisition models inside one feed.

To the retailer’s credit, the earlier testing had already produced something useful: data. We were not starting from pure guesswork. There was historical ad performance, sales data, and clear evidence that some products and categories had real potential. The issue was that the structure underneath that data was too loose to turn it into consistent profit.

The daily budget was limited relative to the size of the catalogue. So even though the product range was extensive, there was never enough budget to give every eligible product meaningful visibility. Too many items were effectively taking turns to underperform.

A few core products sold well and had good margins, but they were being crowded by sheer catalogue volume. At the same time, weaker products were still picking up impressions and clicks even when the economics did not justify it.

A candle, a fitted sheet, and a sofa do not belong under the same acquisition logic. Too much of the account was treating them as if they did.

What the Audit Revealed

The audit did not reveal one dramatic fault. It revealed a stack of smaller commercial and structural problems that were combining into one larger performance issue.

1. Budget was being diluted across too many products

Too much of the catalogue was eligible for paid promotion. That meant budget was being spread across far more product opportunities than the account could sensibly support.

The result was predictable:

  • stronger products lost impression share they should have won
  • weaker products kept entering auctions they were unlikely to justify
  • daily pacing was less stable than it should have been
  • the account was not staying focused on the products most likely to generate profitable orders

2. Commercial filtering was too weak

Not every live product had a strong case for paid acquisition. Some items had weak margins. Some were too uncompetitive on price. Some had little search demand. Some had already shown that their CPCs were too high for the kind of order they generated.

Without stronger filtering, the account was still being asked to give budget to products that simply did not deserve it.

The feed was not empty or broken. But it did not contain enough commercial structure on its own.

Internal product naming, merchandising language, and ecommerce feed conventions are not always the same thing as paid search language. People often search differently from the way a business names a product internally. In several categories, the titles and data were technically correct but not strong enough for how Shopping and Performance Max needed to understand and match them.

4. Merchant Center needed tighter control

A meaningful share of ecommerce performance sits below the campaign layer. Merchant Center diagnostics, feed issues, product disapprovals, price and availability mismatches, shipping settings, and country readiness can all suppress visibility before bidding ever gets a chance to do its job.

That was part of this account too. The problems were not catastrophic, but there was enough friction in the operating layer to reduce stability and waste time.

5. Brand and broader catalogue demand were not cleanly separated

Branded demand behaved very differently from generic product demand, but the structure was not separating those two realities clearly enough.

That weakened budget control and reporting clarity. It also made it harder to judge what the account was genuinely doing to create new demand capture versus simply harvesting people who were already searching for the retailer or its brands.

6. Some products were better sold on-site than through first-click acquisition

This was one of the most important commercial insights in the project.

Some products simply did not make sense as lead acquisition items. That did not mean they were bad products. It meant they were better sold through:

  • related product modules
  • complementary product suggestions
  • basket-building
  • upsell and cross-sell behaviour once a stronger product had already brought the visitor in

A product can be approved in Merchant Center and still be the wrong product to lead with in paid acquisition.

The account did not need more coverage. It needed better judgement.

The Strategy: Rebuild the Account Around Commercial Reality

Once the audit made the pattern clear, the strategy was straightforward in principle, even if the execution was detailed.

We needed to:

  1. build a better decision layer around the catalogue
  2. stop advertising products that did not justify paid acquisition
  3. restructure campaigns around product roles and commercial value
  4. improve Merchant Center and feed hygiene
  5. optimise for profit, not just revenue

1. We turned the feed into a decision-making layer

This was one of the most important changes in the whole account.

A raw ecommerce feed rarely contains enough commercial logic on its own. So we audited the full catalogue and added our own fields through a supplemental feed. That let us enrich the product data without relying on the core platform feed alone.

We combined the retailer’s own business data with Google demand data and ad history to add fields such as:

  • margin tier
  • search demand
  • price competitiveness
  • stock availability
  • seasonality
  • bestseller or hero-product status
  • product role within the wider catalogue

We also used custom labels to organise products more meaningfully inside Shopping and reporting. These labels helped segment the catalogue by things like:

  • margin
  • seasonality
  • stock position
  • product priority
  • hero versus long-tail status

This gave us far more control over what should be promoted, when it should be promoted, and how aggressively it should be bid.

The feed stopped being just a product export and became a commercial control layer.

2. We excluded roughly 80% of the catalogue from direct paid promotion

This was the most visible change, but it only worked because the decision layer above had already been built.

Based on the audit, we excluded about 80% of the full catalogue from paid promotion. These were products that fell into one or more of the following groups:

  • poor historical sellers
  • weak-margin items
  • products with unworkable CPC economics
  • products with weak price competitiveness
  • products with very limited search demand
  • products better suited to basket-building than first-click acquisition

That did not mean these items disappeared from the site or stopped selling. It meant Google Ads stopped being asked to make them all carry their own acquisition cost.

More likely to keep in paid promotion More likely to remove from direct paid promotion
Strong margin or strong contribution Weak margin or weak contribution
Clear search demand Little search demand
Competitive pricing Price position too weak for paid traffic
Good sales history Poor or inconsistent sales history
Reliable stock and category relevance Weak availability or low strategic importance
Capable of winning the first click Better sold as an add-on or related product

This one decision changed the economics of the account. Once the catalogue was narrowed, budget stopped leaking into products that were never likely to justify it, and stronger products got more room to surface consistently.

The goal was not to make every SKU sell through Google Ads. The goal was to make Google Ads commercially sensible.

3. We rebuilt Shopping and Performance Max around product roles

Once the catalogue had been filtered, we restructured the campaigns around how products actually behaved instead of treating the feed as one undifferentiated mass.

Hero products went into dedicated Performance Max campaigns

Products with a strong sales history, good margins, or clear category-leading potential were separated out into dedicated Performance Max campaigns where signal and volume justified that treatment.

These products were the ones most capable of carrying budget and learning quickly. Giving them cleaner separation helped stop them being buried under the rest of the catalogue.

Long-tail products were handled more selectively in Standard Shopping

Longer-tail products that still had a credible commercial case were grouped more tightly in Standard Shopping, with target ROAS used where the product sets were commercially consistent enough for it to make sense.

This gave us more control over how those products were segmented, reported, and optimised without forcing everything into the same campaign logic.

Custom labels created smarter product groups

The enriched feed and custom labels let us build cleaner product groups around:

  • margin tiers
  • seasonal lines
  • in-stock versus constrained stock
  • hero products
  • lower-priority but still viable long-tail products

That meant product grouping inside Shopping reflected business reality far better than the original feed structure did.

Campaign priorities and exclusions improved traffic routing

Where Standard Shopping remained part of the mix, campaign priorities and exclusions helped keep broader traffic from swallowing more valuable product groups.

This is often overlooked, but it matters. Shopping structure is not just about what products are live. It is also about which products get the clearest chance to catch the right type of search.

Brand demand was split out more effectively

One of the simpler but important wins came from separating branded campaigns more clearly from the broader catalogue.

That improved:

  • budget control
  • reporting honesty
  • performance interpretation
  • brand defence

Branded demand became easier to protect, and non-brand activity became easier to judge properly. The account stopped using brand performance to flatter broader catalogue activity that was not as healthy underneath.

4. We treated Merchant Center and feed admin as performance work

A lot of the gain in this account did not come from a flashy tactic. It came from disciplined admin work that too many advertisers leave half-managed.

We reviewed and tightened areas such as:

  • Merchant Center diagnostics
  • product disapprovals
  • price and availability mismatches
  • shipping and country settings
  • landing page alignment
  • feed-source logic
  • country feed readiness

In catalogue-led Google Ads, this is not background housekeeping. It affects whether products are approved, trusted, eligible, and stable enough to stay visible.

A meaningful share of the win came from paying attention to detail and removing avoidable friction from the operating layer.

5. We enriched product titles around how people actually searched

This was another major contributor.

The retailer’s internal naming conventions were not always the same as the language shoppers used. That is normal. It is also exactly why feed enrichment matters.

We combined client data, category knowledge, historical search terms, and Google search demand data to improve titles around real paid search behaviour.

That meant:

  • using wording people actually searched for
  • reflecting commercially important attributes more clearly
  • aligning product titles with demand patterns rather than internal product database language
  • making products easier for Google to understand and match in Shopping

This is where many catalogue-led accounts lose ground without realising it.

SEO language and PPC language are not always identical. A product can be perfectly well described for browsing or even for organic site structure, yet still be weakly positioned for paid search matching.

People do not always search for a product in the same way it is named in an ecommerce backend. Once the feed titles were brought closer to actual search behaviour, matching quality improved and stronger products became easier to surface.

6. We shifted optimisation from ROAS alone to POAS

The account had to move beyond raw revenue efficiency.

ROAS is useful, but revenue alone does not tell you whether a product deserves more paid visibility. Some high-ticket products look attractive in revenue terms while contributing too little margin once CPCs are accounted for. Other products with slightly lower revenue can be far stronger commercially because they leave more profit after acquisition.

So POAS, profit on ad spend, became much more important in how the account was managed.

That meant:

  • prioritising products with stronger contribution, not just higher turnover
  • adjusting bidding logic around margin and customer value
  • creating reports that highlighted where pricing needed to change to make paid acquisition viable
  • reducing spend on products that could not carry their own acquisition cost
  • letting pricing and margin insight influence campaign decisions rather than asking the campaigns to compensate for weak economics

Some problems were not really advertising problems at all. They were pricing or merchandising problems. The account became stronger once it started reflecting that reality instead of spending through it.

What Changed Over the Following Weeks and Months

The first improvements came from tighter filtering, cleaner segmentation, and better feed control. The bigger gains came as the account had time to learn inside that cleaner structure.

Over the following weeks and months, we kept refining around the same principles:

  • isolating winners sooner
  • spinning profitable clusters into their own campaigns
  • tightening negative keyword and search-term control
  • rotating emphasis by seasonality
  • watching stock position and not pushing products that could not support demand
  • keeping Merchant Center stable as the feed evolved

Outdoor furniture, for example, naturally earned stronger visibility in warmer periods. As the season shifted, budget and promotional emphasis moved back toward stronger indoor lines and other categories with better cold-season relevance.

This is where the catalogue started to behave less like one large store feed and more like a group of profitable product clusters.

That mattered for pacing too. Once low-viability products were stripped out, campaigns could stay present for stronger product groups throughout the day instead of spreading budget too thinly across weak opportunities early on.

Winning products were finally getting room to keep winning.

Results

We are not sharing every account metric here, but the commercial outcome was clear.

The account moved from near break-even performance to a materially stronger return on investment. Order volume improved. Brand performance improved once it was separated more clearly. And spend became much easier to defend because it was being concentrated on products that could actually support acquisition cost.

A simple before-and-after snapshot looks like this:

Area Before After
Catalogue strategy Broad product coverage with too many items eligible for promotion Roughly 20% of the catalogue actively promoted based on commercial viability
Product data Core ecommerce feed only, limited commercial structure Supplemental feed + custom labels for margin, demand, seasonality, stock, and product role
Campaign logic Broader mixed Shopping structure Hero products in dedicated Performance Max, long-tail products in tighter Standard Shopping, branded demand separated
Merchant Center control Avoidable diagnostics and feed friction Cleaner approvals, tighter settings, stronger operational stability
Optimisation lens Revenue and general ROAS Profit on ad spend, contribution, and product-level viability
Expansion readiness New market learning would start from scratch Proven winners and feed logic ready to support a first test in Austria

The most useful single stat is this:

Today, the 20% of products promoted through the shopping feed drive more than 80% of ad account revenue.

That is the clearest summary of what changed.

The account did not become stronger by advertising more of the catalogue. It became stronger by getting much more selective about which products deserved paid visibility in the first place.

Why This Worked

The performance gain came from several layers reinforcing each other.

We understood the business, not just the platform

The strategy only worked because it was built around the retailer’s real-world operations: margin, pricing, stock, seasonality, product role, and category behaviour.

Google Ads was not treated as an isolated media system. It was treated as one part of a commercial model.

We improved the data layer underneath the campaigns

Better product data created better control.

Once the feed included margin, seasonality, price competitiveness, and product priority logic, the campaigns stopped guessing so much. Shopping and Performance Max had a cleaner operating environment, and reporting became more useful.

We treated admin discipline as a performance lever

Merchant Center cleanup, disapproval work, feed stability, settings, and diagnostics are easy to dismiss as admin.

In a catalogue-led account, they are often part of the performance engine itself.

We stopped asking every product to justify a first-click CPC

This was a major shift in thinking.

Some products deserved paid visibility because they could win the click and the order. Others were better sold once the user had already arrived through a stronger lead product.

That distinction made the catalogue much easier to manage profitably.

We optimised for profit, not just revenue

This is where the account became commercially honest.

A high ROAS number can still hide poor economics if the wrong products are generating the revenue. By focusing more deliberately on profit on ad spend and contribution, budget started to move toward products that were actually worth scaling.

Using Germany to Test Austria

One of the quieter advantages of this kind of work is that it makes future market launches cleaner.

The retailer is now testing its first launch into Austria. Because the account in Germany had already been rebuilt around a cleaner product selection and supplemental feed structure, we did not need to relearn the entire catalogue from zero.

We could start with:

  • the products that had already proven themselves in Germany
  • the same custom feed logic around margin, demand, seasonality, and stock
  • a cleaner sense of which categories deserved early emphasis
  • better expectations around what the budget could realistically support

That does not mean Austria was treated as a copy of Germany. It still required market-specific judgment around:

  • CPCs
  • competition
  • brand recognition
  • product mix
  • pacing
  • the finer details of demand by market

But the business did not have to begin with 8,000 open questions again. It could begin with a shorter list of proven commercial hypotheses.

That is one of the real advantages of good catalogue discipline. It does not just improve the current market. It creates leverage for the next one.

Lessons for Other Ecommerce Brands With Large Catalogues

This case study is not only about one furniture retailer. The same pattern appears in a lot of catalogue-led ecommerce accounts.

1. A wide catalogue is not a paid media strategy

More products do not automatically mean more profitable opportunity. If the budget is limited, prioritisation matters far more than raw feed size.

2. Merchant Center approval is the starting line, not the finish line

A product can be approved and still be weakly positioned for visibility or profit. Feed quality, title strength, attributes, and market relevance all matter after approval too.

3. SEO language, merchandising language, and PPC language are not always the same

If product titles are not aligned with actual paid search behaviour, Shopping performance can stay weaker than it should be even when the feed looks technically fine.

4. Not every product should carry its own acquisition cost

Some products are lead products. Some are basket-builders. Treating them the same is one of the fastest ways to waste budget.

5. Profit should influence promotion

High revenue products are not automatically the best products to scale. If margin, CPC, and price competitiveness do not support them, they may be the wrong place to concentrate budget.

6. A cleaner first market makes the next market easier

Once the product set, feed logic, and campaign structure are working in one market, expansion stops being a full reset and becomes a more informed rollout.

Conclusion

Large catalogues do not usually need more campaigns first. They need better control over what gets advertised, how product data describes it, and whether each item can justify paid visibility in the first place.

In this account, profitable growth came from removing sprawl.

We audited the catalogue, enriched the feed, cleaned up Merchant Center, separated brand from broader demand, rebuilt Shopping and Performance Max around product roles, and shifted optimisation toward profit on ad spend instead of raw revenue alone.

The result was a much more commercially dependable account:

  • fewer budget leaks
  • stronger orders
  • better brand control
  • cleaner product clusters
  • and a clear proof point that a curated 20% of the catalogue could drive more than 80% of ad account revenue

That is what turned catalogue sprawl into profitable growth.

FAQs

Why would you exclude 80% of a catalogue from Google Ads?

Because direct paid promotion is not the same thing as being available for sale. In large catalogues, a big share of products may be weak candidates for first-click acquisition due to low margin, low search demand, poor price competitiveness, or weak historical sales. Excluding them from ads can make the remaining budget far more productive.

Do excluded products still sell?

Often, yes. Many lower-priority products still sell through onsite merchandising, related product blocks, category browsing, or basket-building once a stronger product has brought the customer in. The point is not to remove them from the business. It is to stop asking Google Ads to make every product pay for its own first click.

Why did Merchant Center matter so much in this case?

Because Shopping and Performance Max depend on a stable, trustworthy product data layer. Diagnostics, disapprovals, price mismatches, shipping settings, and feed hygiene can all suppress visibility or create instability before campaign optimisation even begins.

Why separate branded campaigns from the rest of the catalogue?

Brand demand behaves differently from broader category demand. Splitting it out improves budget control, protects branded visibility, and makes reporting more honest. It becomes much easier to see what the account is doing to capture new demand versus simply converting people who already knew the retailer.

Why was title optimisation so important?

Because people do not always search for products using the same language a retailer uses internally. Titles that are technically accurate can still be weak for paid search. Enriching them around actual search behaviour makes it easier for Google to understand, match, and prioritise the right products.

Can this kind of structure help with new market launches?

Yes. Once product groups are already segmented by margin, demand, seasonality, and performance, that logic can be reused when testing a new market. It does not remove the need for local judgment, but it gives the launch a stronger starting point than simply duplicating an undifferentiated feed.

Need Help Making Your Catalogue More Profitable?

If your Shopping or Performance Max setup is live but too much of the catalogue is still fighting for budget, the issue may not be bidding first. It may be product selection, feed quality, Merchant Center control, or the lack of a clear commercial logic underneath the account.

Borderless helps ecommerce brands rebuild Google Ads around cleaner catalogue decisions, stronger product data, and multi-market structures that are easier to trust and scale.

If you want to see where your own setup is leaking budget or suppressing visibility, book a call and we can map out the most practical next step.