Performance Marketing
Industry: SaaS
3.1x
ROAS
In short
Arcetis rebuilt a SaaS company's Google Ads and Meta Ads funnels end-to-end — targeting, landing pages, and GoHighLevel-based lead scoring tied to GA4 — so every dollar of ad spend could be tracked from click to closed revenue. The result was a 3.1x return on ad spend and a 42% reduction in cost per lead, with budget shifted toward the channels and audiences that actually converted.
This engagement involved a SaaS company running paid acquisition across Google Ads and Meta Ads without a reliable way to connect ad spend to actual revenue. Like many software businesses scaling through paid channels, the client had reasonable click volume but lacked the infrastructure to know which campaigns, keywords, or audiences were producing paying customers versus just traffic. Arcetis was engaged to rebuild the full paid acquisition funnel — from ad targeting and landing page experience through to CRM-based lead scoring and revenue attribution — so marketing spend could be evaluated on actual business outcomes rather than surface-level metrics like clicks or impressions. The work spanned both the marketing/media layer (Google Ads, Meta Ads) and the operational layer (GoHighLevel CRM, GA4 analytics), reflecting the reality that fixing paid acquisition problems in SaaS almost always requires touching both sides of the funnel at once, not just the ad accounts.
The client, a SaaS business, was spending meaningfully on paid acquisition across Google Ads and Meta Ads and generating a steady volume of clicks — but those clicks weren't converting into qualified leads at a rate that justified the spend, and worse, there was no reliable system in place to explain why. This is a common failure pattern in paid acquisition for software companies: campaigns get optimized against upper-funnel signals (click-through rate, cost per click, impression volume) because those are the metrics readily visible inside the ad platforms themselves, while the metrics that actually matter to the business — qualified leads, sales-accepted opportunities, closed revenue — live downstream in a CRM or sales process the ad platforms have no visibility into. Without that connective tissue, the marketing team was in a difficult position: every dollar spent had to be justified using proxy metrics that only loosely correlated with revenue. When results plateaued or slipped, there was no way to isolate the cause — was it targeting drift, landing page underperformance, poor lead quality once a click occurred, or leads that were fine but that sales failed to convert? Each of those has a different fix, but from inside the ad platforms alone, they all look identical: a click that didn't turn into revenue. This kind of attribution gap tends to compound over time. Budget gets allocated based on last-known platform performance rather than true return, so underperforming campaigns or audiences that generate cheap clicks but low-quality leads keep absorbing spend simply because nobody can prove they should be cut, while better-performing segments don't get the additional budget they've earned. For a SaaS business, where customer acquisition cost and payback period are core to unit economics, this isn't a minor reporting gap — it directly affects growth efficiency and how confidently the business can scale its paid channels. The client needed the funnel rebuilt end-to-end: targeting and campaign structure on the ad platform side, a landing page experience that actually qualified visitors rather than just capturing them, and a lead-tracking system that could follow a prospect from initial ad click through CRM stage to closed revenue — so every subsequent budget decision could be made on real conversion and revenue data instead of platform-reported proxies.
Arcetis led the end-to-end rebuild of the client's paid acquisition funnel across Google Ads and Meta Ads. Arcetis restructured campaign targeting and account architecture on both platforms to focus spend on audiences and keywords more likely to convert into qualified leads rather than just clicks. Arcetis designed and built new landing pages aligned to specific campaign intents, replacing generic destination pages with pages built to qualify and convert visitors. Arcetis implemented lead scoring and tracking inside GoHighLevel so every lead generated could be followed through the CRM pipeline rather than treated as a one-time conversion event. Arcetis configured GA4 tracking and connected it to CRM data so ad spend could be tied to actual lead quality and revenue outcomes. Arcetis also managed the ongoing reallocation of budget across campaigns and channels based on the resulting performance data.
Arcetis audited and rebuilt the client's Google Ads account structure, refining keyword targeting, match types, and campaign segmentation to concentrate spend on search intent most likely to produce qualified leads rather than generic clicks. Ad groups were reorganized around specific product use cases and buyer intent rather than broad keyword themes, and negative keyword lists were expanded to cut spend on traffic unlikely to convert. The goal was to shift optimization away from click-based metrics and toward the lead-quality signals living downstream in the CRM.
Arcetis rebuilt Meta Ads targeting and campaign structure alongside Google Ads, refining audience segments and aligning ad creative and messaging to the specific landing pages each campaign fed into. Rather than running Meta as a generic awareness channel, campaigns were restructured to work as a qualified-lead-generation channel, with performance measured against the same downstream lead-scoring and revenue data used for Google Ads so the two channels could be compared on equal footing.
Arcetis designed and built new landing pages tied directly to specific ad campaigns and audience segments, replacing generic destination pages with pages built to qualify visitors before they ever reached the CRM. Page structure, forms, and calls to action were built around collecting the information needed for lead scoring, so a visitor's on-page behavior and submitted information could immediately feed into how that lead was prioritized in GoHighLevel.
Arcetis implemented lead scoring inside GoHighLevel so every lead entering the CRM was automatically evaluated and routed based on defined criteria rather than treated as a single anonymous form fill. Leads were tracked through pipeline stages from initial capture to sales handoff and closed revenue, creating a persistent record that connected each lead back to the specific campaign, ad, and landing page that generated it.
Arcetis configured GA4 to track the full visitor journey from ad click through landing page interaction, and connected that tracking to the CRM data captured in GoHighLevel. This closed the loop between ad-platform reporting (Google Ads, Meta Ads) and actual business outcomes, giving the client a single source of truth for evaluating which campaigns, audiences, and keywords were producing revenue rather than just traffic.
The rebuild followed the standard sequence for fixing a paid acquisition funnel where spend and revenue have become disconnected: audit the existing setup, rebuild the parts that are broken, instrument the connections between systems, and then let the data drive budget decisions rather than working from account managers' priors. The first step was auditing the existing Google Ads and Meta Ads accounts to understand where spend was going and why the resulting clicks weren't turning into qualified leads at an acceptable rate. On the Google Ads side, this typically means reviewing search term reports against actual keyword targeting to find mismatches, checking match type usage (broad vs. phrase vs. exact) for waste, and evaluating whether campaign and ad group structure reflected distinct buyer intents or was too broadly bucketed. On Meta, it means checking audience overlap, creative fatigue, and whether campaigns were optimized for the right conversion event rather than traffic or engagement. With the audit complete, Arcetis rebuilt campaign structure on both platforms around intent rather than broad topic match, tightened targeting, and expanded negative keyword coverage on Google Ads to reduce spend on searches unlikely to convert. On Meta, audiences were rebuilt and creative was aligned to the specific landing page and offer each campaign pointed to, rather than running the same generic ad across multiple destinations. Landing pages were rebuilt to match this new campaign structure — a common failure point in paid acquisition is sending well-targeted ad traffic to a generic homepage or a single catch-all landing page that doesn't map to the visitor's actual intent. Each landing page was built around a specific campaign or offer, with forms and content designed to qualify visitors rather than simply capture an email address. The connective work — the part that actually closes the attribution gap — involved wiring the ad platforms, landing pages, GoHighLevel, and GA4 together. This is typically done through a combination of UTM parameter conventions applied consistently across every campaign and ad, GA4 event tracking configured to capture the full visitor journey from ad click through landing page interaction to form submission, and a direct integration so every lead captured on a landing page lands in GoHighLevel tagged with its original campaign, ad, and keyword source. Inside GoHighLevel, lead scoring rules were configured so incoming leads are automatically evaluated against defined criteria — the specifics vary by business, but typically include factors like the information provided on the form, on-site engagement behavior, and pipeline stage progression — so sales and marketing could distinguish a high-intent lead from a low-quality one without manually reviewing every submission. Leads were tracked through pipeline stages so a lead's eventual outcome (qualified, opportunity, closed-won, closed-lost) could be tied back to its original campaign source. With that tracking in place, GA4 and GoHighLevel data together gave a full picture of performance from click to closed revenue — not just cost per click or cost per lead, but cost per qualified lead and, ultimately, return on ad spend. That data was then used on an ongoing basis to reallocate budget: campaigns, audiences, and keywords with a proven path to revenue received more spend, while segments generating clicks or unqualified leads without downstream conversion were scaled back.
Consistent UTM parameter conventions across Google Ads and Meta Ads campaigns, combined with GA4 event tracking and a direct integration into GoHighLevel, allowed every lead to be traced back to its originating campaign, ad, and keyword. This closed the gap between ad-platform reporting and actual CRM outcomes, making it possible to calculate cost per qualified lead and ROAS rather than relying on click-based proxy metrics alone.
Lead scoring logic was configured inside GoHighLevel to automatically evaluate and route incoming leads based on defined criteria as they entered the CRM, rather than requiring manual review of every submission. Leads were tracked through pipeline stages from capture to sales handoff to closed revenue, creating a persistent, campaign-tagged record for every lead the funnel produced.
Google Ads campaigns and ad groups were reorganized around specific buyer intents rather than broad keyword themes, with tightened match types and expanded negative keyword coverage to reduce spend on non-converting search traffic. Meta Ads audiences and creative were similarly rebuilt and aligned to the specific landing page each campaign fed into, rather than run as a generic top-of-funnel channel.
Rather than routing paid traffic to a single generic destination page, landing pages were built per campaign and offer, with page structure and forms designed to qualify visitors and feed structured data into the lead-scoring system — improving both conversion rate and the quality of information available downstream in GoHighLevel.
ROAS
Cost per lead
Technology used
Key learnings
This engagement is a reminder that paid acquisition problems in SaaS are rarely fixed by adjusting bids or creative in isolation. The client's core issue wasn't that Google Ads and Meta Ads were badly run — it was that the ad platforms, landing pages, and CRM were three disconnected systems, each reporting a partial and misleading picture of performance. Clicks looked fine. Cost per click looked fine. None of that told anyone whether the business was actually making money on its spend. Fixing that required treating the funnel as a single system: campaign structure, landing page design, and CRM lead scoring all had to be rebuilt together and wired to a common source of truth, rather than optimized independently against whatever metric each platform happened to surface. The results — a 3.1x ROAS and a 42% drop in cost per lead — came less from any single tactical change and more from being able to see, for the first time, which parts of the funnel were actually converting. Once spend, leads, and revenue were tied together in one view, reallocating budget became a straightforward exercise in cutting what didn't convert and reinforcing what did, rather than a guessing game based on last month's platform dashboards. For any SaaS business running paid acquisition at meaningful scale, the lesson generalizes: attribution infrastructure isn't an optional add-on to a paid media program — it's the mechanism that makes every other optimization decision defensible.
The usual cause is a disconnected funnel: ad platforms report on clicks and impressions, but nothing connects those clicks to what happens next — lead quality, CRM stage, or closed revenue. The fix is to rebuild the funnel end-to-end (targeting, landing pages, and CRM-based lead tracking) so spend can be evaluated against actual conversion and revenue data rather than platform-reported proxy metrics. In this engagement, Arcetis did exactly that using Google Ads, Meta Ads, GoHighLevel, and GA4, and the client's cost per lead dropped 42% as a result.
Typically it means applying consistent UTM tracking across every campaign, configuring GA4 to capture the visitor journey from click to conversion, and integrating landing page forms directly into the CRM so every lead is tagged with its originating campaign, ad, and keyword. Inside the CRM, lead scoring and pipeline-stage tracking then let a business follow that lead through to a closed-revenue outcome instead of losing visibility once the form is submitted.
Once ad spend, GA4 tracking, and CRM revenue data are connected, return on ad spend can be calculated against actual closed revenue rather than lead volume or cost-per-click alone. In this engagement, that full-funnel tracking produced a measured 3.1x ROAS alongside a 42% reduction in cost per lead, giving the client a defensible basis for budget decisions.
Both, when pages are built around a specific campaign's intent rather than serving as a generic catch-all. Matching landing page offer, content, and form fields to what the ad promised — and to what the downstream lead-scoring system needs to evaluate the lead — tends to improve conversion rate and lead quality together, since visitors who convert are more likely to be a genuine fit.