Sample case study for demonstration. This engagement is illustrative: the scenario is typical of the work Axoria does, and the results are described without figures until verified client data is published.
The situation
A B2B technology company selling infrastructure monitoring software to mid-sized IT teams relied on Google Ads for most of its inbound demo requests. The account reported a healthy cost per lead. The problem surfaced in the CRM rather than the ads platform: many leads were students, job seekers, existing customers looking for support, or companies far too small to buy.
Marketing and sales disagreed about whether paid search was working. Axoria was brought in to run the PPC programme and settle that disagreement with data.
The challenge
The account was optimising for the wrong signal. Smart Bidding had been trained on form submissions, so it had learned to find cheap form fills wherever they came from. Loose broad match, a single generic landing page and no feedback from the CRM meant the algorithm could not tell a demo request from a hobbyist apart from one from a head of infrastructure. The real objective was not a lower cost per lead but a lower cost per sales-accepted opportunity, measured in the CRM.
Research and analysis
We exported a year of search-term data and joined it to CRM lead status by click ID. Support-intent queries, competitor-brand queries and “free” or “open source” modifiers accounted for much of the spend and almost none of the pipeline. Product-category queries with a company-size qualifier converted less often on the form but far more often in the CRM.
A tracking audit found duplicate conversion actions double-counting submissions, and a conversion window too short to capture the lag between first click and demo request for this buyer.
Strategy
One principle: give the bidding algorithm the outcome the business cares about, then structure everything else so that outcome is easy to find.
Offline conversion import
Push sales-accepted and opportunity-created stages from the CRM back into Google Ads via GCLID, so Smart Bidding could optimise toward qualified outcomes rather than form fills.
Intent-led structure
Rebuild campaigns around intent themes with tightly matched ad groups, controlled use of broad match, and a negative keyword architecture shared across the account.
Landing pages by intent
Replace the single generic page with a small set of pages matched to query intent, each with a qualification question on the form to filter obvious non-buyers before they hit the CRM.
The trade-off was accepted in advance: form-fill volume would fall and cost per raw lead would rise. Both numbers went on the dashboard so nobody would be surprised.
Execution
The first month went on tracking: deduplicating conversion actions, extending the window, capturing GCLID into hidden form fields and scheduling daily CRM uploads. We switched the bidding target only once the offline import had accumulated enough qualified conversions, because moving Smart Bidding to a sparse signal too early would have starved it.
The restructure followed. Campaigns were rebuilt around intent themes with a shared negative list covering support, careers, education and competitor-brand terms. The new landing pages went live at the same time so message match improved alongside targeting. A deliberately small competitor campaign was kept with its own budget cap and a qualification-heavy page.
Optimization
With CRM outcomes flowing back into the platform, weekly optimisation came down to one question: which search terms, audiences and pages are producing accepted opportunities? Search-term hygiene became a scheduled discipline. Bid targets were adjusted gradually as the signal matured, landing pages were tested on qualified rather than raw submission rate, and budget was moved toward the intent themes with the shortest path to pipeline, which our lead generation reporting tracked through to closed-won.
Results (illustrative)
Figures are withheld until verified, client-approved data is published. Measured in the CRM against the six months before the engagement, the movements typical of this kind of work are:
- Cost per qualified lead: falling meaningfully even though cost per raw form fill rose, because spend stopped going to queries that never produced pipeline.
- Lead quality: the share of paid-search leads accepted by sales rising to the point where sales asked for more budget in the channel.
- Pipeline contribution: paid search becoming the largest single source of new opportunities in the CRM, on an attribution basis agreed by both teams.
What we learned
- Fix the signal before the structure. Restructuring an account that optimises for the wrong outcome just finds it more efficiently.
- Expect volume to drop, and say so. Putting raw and qualified lead counts side by side on the dashboard prevented a panic in the second month.
- Qualification questions are a feature. Adding a company-size field reduced form completions and improved everything downstream. This applies broadly across technology and software buyers.
- The CRM is the source of truth. Google Ads reporting is only as honest as the conversion data you feed it. Read more on how we approach Google Ads management.