The Challenge
Selling Screws at Scale — to Two Very Different Buyers
Fixings and fasteners is a deceptively complex category to advertise. The product catalogue runs into the thousands — screws, bolts, nails, anchors, hangers, workwear, sealants, adhesives — and the customer base is split across two distinct audiences with very different purchasing behaviours.
The trade buyer — a site manager, purchasing manager, or construction business owner — is largely driven by availability, price, and reliability. They buy in volume, they have preferred suppliers, and they search at specific times of day, often early morning before site starts or during scheduled procurement windows. The consumer buyer is more price-sensitive, less brand-loyal, and more likely to browse before purchasing.
Running a single campaign structure across both audiences was leaving significant revenue on the table. The opportunity was to build something more intelligent: campaigns that understood who was buying, when they were buying, and which products were worth advertising in the first place.
Strategy 01
POAS: Optimising for Profit, Not Just Revenue
The starting point was replacing a ROAS-only framework with a POAS (Profit on Ad Spend) approach. In a category with highly variable margins — where the difference in profitability between a box of drywall screws and a specialist anchor bolt can be significant — optimising purely to revenue tells only half the story.
The POAS model incorporated management fees, stock costings, cost per acquisition, and product margins into the campaign decision-making. This meant bidding strategies were calibrated not to what a product sold for, but to what it actually returned after costs. Products with high revenue but thin margins were treated differently to high-margin lines, even if their headline ROAS looked similar.
Chasing ROAS without understanding margin is one of the most common and costly mistakes in e-commerce PPC. A 700% ROAS on a low-margin product may be less valuable than a 400% ROAS on a high-margin one. POAS removes that ambiguity.
Strategy 02
Scheduling: The Right Ad at the Right Hour
One of the most impactful optimisations was understanding the temporal pattern of purchase intent. Trade buyers — site managers, procurement leads, construction businesses — follow predictable rhythms. Orders are placed early morning before site work begins, during lunch, or at end of day during admin time. Weekday behaviour differs sharply from weekends, where the audience shifts more heavily towards retail consumers.
Data from the account was used to map hour-by-hour and day-by-day conversion patterns, and bid adjustments were applied accordingly. Budget was concentrated in the windows where purchasing intent was highest, and pulled back during lower-converting periods. For a trade-skewed account, this meant heavier weighting towards Monday to Friday business hours, with adjusted allocations across the weekend consumer audience.
The result was the same budget working considerably harder — more spend landing in high-intent windows, less wasted on low-converting periods.
Strategy 03
Feed Optimisation: Human Titles, Better Results
For an e-commerce retailer with thousands of SKUs, the product feed is the engine of paid search performance. Auto-generated product titles pulled from a CMS rarely reflect how buyers actually search — and in a category as specific as fixings, where buyers search by thread size, material, head type, and pack quantity, relevance is everything.
Key product titles were rebuilt manually, drawing on three data sources: Google Search Console (actual search queries driving organic traffic), Google Merchant Center (product-level impression and click data), and human knowledge of how trade buyers describe what they need. Titles were structured to lead with the most commercially important attributes first.
The impact was measurable across multiple dimensions: higher click-through rates from more relevant titles, improved ad rank through better quality scores, lower average CPCs, and stronger conversion rates from more qualified traffic arriving at the right product page.
Strategy 04
Organic Exclusions: Spend Where It Actually Counts
One of the less obvious but highly effective levers in the account was the systematic exclusion of products already ranking in positions one to three organically. For these products, paid investment is largely cannibalising clicks the business would have received for free — spending budget to appear above results you already own is rarely incremental.
By identifying high-ranking organic products through Search Console and excluding them from paid campaigns, budget was freed up and redirected towards products where paid coverage was genuinely generating incremental revenue: lines ranking on page two, or absent from organic results altogether.
The goal wasn't to dominate one product — it was to grow revenue horizontally across the catalogue. Paid media should be doing the work organic can't, not duplicating it.
Strategy 05
Best-Seller Campaigns: Where 70% of Revenue Lives
Across most e-commerce accounts, a relatively small proportion of the product catalogue drives a disproportionate share of revenue. Identifying that core group — and building campaigns specifically around it — is one of the highest-leverage activities available.
Best sellers were identified using a combination of platform data (Shopping performance, Search impression share, conversion volume) and offline data (sales records, stock velocity, margin data). The resulting product set was built into dedicated campaigns with tailored bidding, bespoke feed entries, and higher budget allocations.
These campaigns ultimately accounted for approximately 70% of total account revenue — a focused, high-performing core that the broader catalogue campaigns could build around without diluting efficiency.
Strategy 06
Microsoft Ads: Expanding Reach After Six Months
After the Google Ads foundation was established and performing consistently, Microsoft Ads was introduced at the six-month mark. The decision was deliberately sequenced: build a proven structure on Google first, then replicate it on Microsoft where the trade buyer audience — slightly older, more desktop-heavy, often procurement-focused — over-indexes significantly.
Campaigns were built to mirror the Google structure, with the same feed optimisations, scheduling logic, and best-seller prioritisation applied. The incremental reach came at a lower average CPC than Google, contributing additional revenue without meaningfully increasing the cost per acquisition.
The Result
Consistent Growth. Consistent Profit.
Across the engagement, the account delivered consistent month-on-month growth — not as a one-off spike, but as a sustained trajectory. Spend scaled from £8k to £15k per month as results justified each increase in investment, with ROAS holding between 600 and 800% throughout.
The campaign structure across Search, Shopping, Display, and Performance Max gave the account full-funnel coverage: Shopping and PMax capturing active purchase intent, Search picking up specific product and trade queries, Display maintaining visibility with past visitors and lookalike audiences.
The combination of POAS discipline, intelligent scheduling, feed quality, organic exclusions, and best-seller focus meant that growth was not just in volume — it was profitable growth, accountable at every stage.
