Case Studies
About anonymity: Client data is confidential. These case studies are anonymised and shown as ranges to respect NDAs and competitive sensitivity.
About credibility: Many published case studies overstate impact. To avoid that, I only publish outcomes I can verify from source systems (GA4, Ads, CRM) and I label the source under each result. Detailed evidence is available under NDA.
Complex problems → profitable systems. Below are four real-world engagements where I helped e-commerce brands, SaaS companies, and agencies turn messy data and underperforming campaigns into measurable revenue growth. Each case study follows the same structure: the business problem, the technical fix, and the verified outcome. I lead with results because that is what matters — but the detail behind each fix is where the value actually sits.
Google Ads (e-com): ditch 90-day ROAS, scale on LTV
Outcome: The business shifted from acquiring cheap, low-margin customers to attracting high-LTV buyers. New customer acquisition cost (nCAC) dropped while total ad spend scaled at a constant payback period. Source: Google Ads + CRM revenue data, verified in Looker.
- Problem: The brand was optimising Google Ads to a 90-day ROAS target. That sounds reasonable — until you look at what it actually did. Campaigns with longer payback windows (which often brought in the most valuable repeat buyers) were automatically paused because they failed the 90-day cutoff. Meanwhile, cheap one-time purchases looked great on the dashboard but contributed almost nothing to lifetime revenue. The bidding strategy was rewarding the wrong customers.
- Fix: I connected the CRM and payment platform directly to Google Ads so we could track actual revenue per customer over 12 months, not just the initial purchase. I built a Looker dashboard that surfaced 1-year value by campaign, giving the team clear visibility into which ad groups produced the best long-term buyers. From there, I restructured the account around CPA-based bidding targets calibrated to real payback data, and reorganised campaigns to push budget toward the highest-profit cohorts.
- Result: The team could finally scale spend with confidence because they could see exactly which campaigns drove profitable repeat customers. Bottom-line revenue improved as the ad account stopped wasting budget on low-value one-time buyers and started compounding returns from high-LTV cohorts. The Looker dashboard became a decision-making tool the team used weekly.
“Ben is a pro! … cleaned up Google Ads and GA4, fixed tracking, and showed us the next steps.” — E-commerce Marketing Manager
GA4 (SaaS): broken tracking → trusted, team-owned data
Outcome: Cross-channel attribution was fully restored across Google and Meta, consent-related data loss was resolved, and the team's time-to-insight dropped from days to minutes. The marketing team went from not trusting their data to self-serving reports with confidence. Source: GA4 real-time and historical event data, GTM audit log.
- Problem: The company had migrated to GA4 but the implementation was a mess. Events were misconfigured or missing entirely, the Meta Pixel was firing incorrectly, and the consent banner was stripping out key events — meaning a significant chunk of user interactions simply never got recorded. The marketing team had no reliable way to attribute conversions across channels, so they were essentially flying blind on ad spend allocation.
- Fix: In one focused session, I ran a full audit across GA4, Google Tag Manager, the Meta Pixel, and the consent management platform. I identified exactly where events were dropping, fixed the consent banner configuration so it stopped blocking legitimate tracking, and rebuilt the entire event and conversion schema end-to-end. I also documented the setup with clear SOPs so the in-house team could maintain and extend the tracking going forward without outside help.
- Result: The marketing team gained reliable ROI visibility across both Google and Meta for the first time since migrating to GA4. They could see which channels and campaigns drove signups and revenue, and they no longer needed external consultants for basic reporting. The team now self-serves data confidently using GA4 Explorations and Looker Studio dashboards I set up during the engagement.
“We solved in hours what we’d stalled on for weeks.” — SaaS Marketing Lead
AI Training (agency): ad-hoc dabbling → repeatable workflow
Outcome: The agency cut client reporting time from hours to minutes, increased creative output by 5–10× without additional headcount, and produced higher-quality campaign commentary. AI went from a buzzword to a daily operational tool embedded across the team. Source: internal time tracking, creative output logs.
- Problem: The agency had been hearing about AI for months and individual team members were experimenting with ChatGPT and image tools in ad-hoc ways, but nothing had been formalised. There was no shared workflow, no quality standard, and no integration with the tools the team already used daily. AI was creating excitement but not delivering consistent value, and leadership had no way to measure whether it was actually saving time or improving output.
- Fix: I built three concrete AI workflows the team could use immediately. First, I live-wired Google Ads data into Claude so account managers could generate full client performance reports with a single prompt. Second, I created a Canva-to-AI pipeline for on-brand, editable creative assets — the team could go from brief to finished ad variants in minutes instead of hours. Third, I ran hands-on training sessions covering advanced image editing and generation using GPT-4o and Google Imagen, giving the creative team the skills to produce high-quality visuals independently.
- Result: Account managers now ship polished client reports in minutes instead of spending half a day pulling data manually. The creative team produces 5–10× more on-brand assets per week, and client commentary improved because the AI workflows freed up time for strategic thinking. The agency embedded these processes into their SOPs, meaning the productivity gains compound as new team members are onboarded.
“Brilliant. We actually changed how we work.” — Agency Director
SEO (my site): rank for “Google Analytics 4 consultant”
Outcome: This site now ranks on page one for competitive GA4 consulting terms, generating a steady flow of qualified inbound leads from organic search. The rankings have held consistently because the approach is built on technical fundamentals, not tricks. Source: Google Search Console, CrUX field data, third-party rank tracking.
- Problem: As an independent consultant, I needed to outrank established agencies with larger teams, bigger budgets, and stronger domain authority for high-intent search terms like “Google Analytics 4 consultant.” These are terms where the searcher is actively looking to hire someone, so ranking on page one directly translates to revenue — but the competition includes well-funded agencies with dedicated SEO teams.
- Fix: I built this site as a lightweight, performance-first platform with Core Web Vitals scoring ‘Good' on real-user field data (not just lab tests). On the content side, I wrote deep, fix-oriented GA4 articles that address specific problems practitioners actually search for — not generic overviews. The SEO methodology I used here is the same approach I refined over years in hyper-competitive affiliate niches, where thin content gets nowhere and only genuine technical depth earns and holds rankings.
- Result: The site consistently ranks on page one for target terms and generates a steady stream of qualified inbound leads — people who have already read my content, understand my approach, and are ready to engage. These organic leads convert at a significantly higher rate than any paid channel because the content pre-qualifies them before they ever reach out.
How I work: Every engagement starts with a focused diagnostic — I look at your data, your tracking setup, and your current performance before recommending anything. I am results-oriented and I only take on work where I am confident I can move the numbers that matter to your business. If the fit is not right, I will tell you upfront rather than waste your time or budget.
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Ben helped us successfully migrate from UA to GA4 in a matter of minutes. We had a great experience and highly recommend him to anyone struggling with the technical aspects of Analytics.
Klara Nilsson
February 7, 2023Ben's amazing. He responded almost right away to my request, sat with us (virtually) and showed us just how to proceed with understanding Google Analytics using Looker, and answered follow up questions promptly. We were lucky to have found him to help us.
Alice Lankester
February 24, 2025Ben was an absolute lifesaver in helping us set up event and conversion tracking for our website, and ads platforms such as Google, Reddit and LinkedIn. Not only did he solve many of our tracking issues, but he also went above and beyond and helped us build dashboards on Looker with details on a lot more website activity than we initially asked for. On top of that, he took the time to train me on how to use Google Tag Manager, build dashboards on Looker, and use AI tools. He's been so patient with me and I now feel much more confident managing our tracking and analytics. He didn't only make the process educational, but also fun (I'm not a very technical person, and it overwhelmed me so much to have to handle this, but now I feel capable and learnt a new avenue of growth marketing). Highly recommend working with Ben—he truly knows his stuff! Thank you Ben, I truly appreciate everything you've done.
Piumi Rajapaksha
February 18, 2025
