Case Studies

Data that
delivers results

Three projects. Three challenges. Measurable results. An insight into our approach — from problem analysis to completed tracking setup.

01
E-Commerce / Fashion From data chaos to tripled ROAS in 12 weeks
02
B2B SaaS Track lead pipeline completely — CPL reduced by 35%
03
Performance Agency Unified tracking infrastructure for 12 client accounts
Case Study 01
E-Commerce Server-Side Tracking GA4 12 weeks

From Data Chaos to Tripled ROAS

How an established e-commerce company significantly improved its ad spend efficiency (measured ROAS increase: approx. 3×) through server-side tracking — and reduced data loss from 42% to under 5%.

IndustryE-Commerce / Fashion
Duration12 weeks
Team2 people
TechnologyGTM Server-Side + GA4 + Meta CAPI

Starting Point & Challenge

The client operates an established online shop in the premium fashion segment with a five-figure monthly advertising budget. Despite years of tracking, the data situation was alarming: the measured conversions in Google Analytics and the actual sales in the shop diverged by over 40%. Paid campaigns were being optimised on the basis of false signals — with correspondingly poor ROAS values.

The causes lay on multiple levels: widespread ad blocker use among the target audience, Safari ITP restrictions, a fragmented tag structure in a GTM container that had grown over years, and a missing first-party cookie structure. The result: the company was burning ad budget without knowing it.

Our Approach

We started with a complete audit of the existing setup — before a single line of code was written. From this emerged a measurement plan that precisely defined what should be measured, why, and what data quality was required.

1

Audit & Measurement Plan (Weeks 1–2)

Complete analysis of the GTM container: 64 tags reviewed, 38 removed or deactivated. Identification of all data gaps in the e-commerce funnel. Definition of a precise measurement plan with 12 critical events and clear priority.

2

Server-Side GTM Build (Weeks 3–5)

Deployment of a GTM Server Container on Google Cloud. Building the first-party cookie infrastructure with 400-day lifetime under own subdomain. Migration of critical events from client-side to server-side. Configuration of the GA4 server-side endpoint.

3

Ad Platform Integration (Weeks 6–8)

Implementation of Meta Conversions API (CAPI) via the server container. Enhanced Conversions for Google Ads with hashed customer data. Synchronisation of offline conversions from the shop backend. Deduplication of all events to avoid double counting.

4

Attribution & Dashboard (Weeks 9–11)

Migration from last-click to data-driven attribution model in Google Ads. Building a Data Studio dashboard with complete channel mix, ROAS development and contribution analysis. Automated weekly performance report.

5

Validation & Handover (Week 12)

Complete cross-validation of all tracking data against the shop backend. Alignment of GA4 vs. Ads vs. Meta to under 3% divergence. Handover with full documentation, team training for marketing and IT, handover protocol.

Results after 12 weeks

ROAS increase
-42%
data loss reduced
<3%
divergence GA4 & Ads
-15%
CPA reduced

"rhyn.digital showed us how much money we had been wasting due to faulty data. After the implementation we were finally able to optimise our campaigns on real signals."

Sonam W.
Marketing Lead, E-Commerce

Key Learnings

  • Server-side tracking is effectively mandatory for e-commerce with >20% Safari traffic
  • First-party cookies on own subdomain massively extend tracking quality
  • GTM audits almost always reveal significant hidden tracking errors
  • Attribution models determine budget allocation — last-click is almost always wrong
Case Study 02
B2B SaaS Lead Tracking CRM Integration 8 weeks

Making the Lead Pipeline Visible

A Swiss B2B SaaS provider didn't know which marketing channels were truly bringing in customers. After 8 weeks they had a complete picture of their lead journey — and halved their CPL.

IndustryB2B SaaS
Duration8 weeks
Team2 people
TechnologyGA4 + GTM + HubSpot Integration

Starting Point & Challenge

The company offers a B2B software solution for mid-sized companies. The sales cycle is long (4–12 weeks), leads come through various channels — SEO, LinkedIn Ads, Google Ads, webinars, direct contact. The problem: which channel was actually delivering qualified leads was completely unclear.

The existing analytics setup tracked website visits and demo requests — but the further journey in the CRM (HubSpot) was completely separate from the marketing data. The marketing team was investing based on gut feeling rather than data.

Our Approach

1

Tracking Audit & Measurement Plan (Week 1)

Complete analysis of all 7 forms, lead magnets and conversion points. Identification of the 3 faulty form trackings. Definition of a measurement plan with 18 lead events, prioritised by sales relevance. Audit of the LinkedIn Insight Tag and configuration errors documented.

2

GA4 & GTM Implementation (Weeks 2–4)

Complete form tracking across all 7 forms with event parameters (form name, lead score, source). Engagement events: scroll depth, video completion, whitepaper download, demo page dwell time. LinkedIn Insight Tag reconfiguration and conversion setup. Correct UTM parameter capture for all campaign channels.

3

HubSpot CRM Integration (Weeks 5–6)

Integration of HubSpot as data source in GA4 via offline conversion import. Transfer of GA4 Client ID to HubSpot for every lead for complete attribution. Setup of webhook-based offline conversion at deal close back to Google Ads. Audience building based on qualified HubSpot contacts for lookalike targeting.

4

Reporting & Attribution (Weeks 7–8)

Building a Data Studio dashboard with complete lead pipeline visualisation — from first click to deal close. Channel performance comparison with real offline conversions. Automated weekly report for marketing and C-level. Training of the marketing team on the new data situation.

Results after 8 weeks

more attributed leads
-35%
cost-per-lead
100%
form capture
1
unified dashboard

"Before we had three different tools giving us three different numbers. Now we have a single source of truth — and for the first time we know exactly what our marketing investments deliver."

Raphael O.
Managing Director, B2B SaaS

Key Learnings

  • B2B attribution without CRM integration is structurally impossible
  • Engagement events (scroll, video, download) are strong signals for lead quality
  • UTM parameter discipline across the entire team is a prerequisite for valid attribution
  • Offline conversion import transforms the quality of campaign optimisation
Case Study 03
Performance Agency White-Label Tracking GTM Templates 16 weeks

Scalable Tracking Infrastructure for an Agency

How a Swiss performance agency standardised and automated its tracking quality across 12 client accounts — with a white-label tracking stack that can be rolled out in hours rather than weeks.

IndustryPerformance Agency
Duration16 weeks
Team3 people
TechnologyJentis + Data Studio

Starting Point & Challenge

The agency manages 12 clients in e-commerce and B2B with a small performance team. Tracking was built individually for each client — what worked for the first client was reinvented for the next. The result: high quality variation, long onboarding times, difficult maintenance.

With a growing client portfolio the problem became more acute: the team was spending 40% of its time on tracking maintenance rather than campaign optimisation. Errors in one client setup were often only discovered weeks later. And clients received varying quality of data depending on which account manager was responsible for their setup.

Our Approach

Together with the agency team we developed a standardised tracking stack that can be rolled out as a reusable template system for all existing and new clients. The goal: maximum consistency, minimal maintenance effort, highest data quality.

1

Analysis & Standardisation (Weeks 1–3)

Audit of all 12 existing GTM containers. Identification of commonalities and best practice elements. Definition of a standard measurement plan with mandatory events and optional extension modules. Naming convention for tags, triggers and variables — binding for all accounts.

2

Jentis Infrastructure & Tracking Architecture (Weeks 4–8)

Building a multi-tenant Jentis instance as the central server-side infrastructure for all 12 client accounts. Definition of a unified Jentis data layer standard with mandatory events and optional extension modules. Subdomain structure and first-party cookie configuration set up individually for each client.

3

Jentis Rollout & Account Migration (Weeks 9–12)

Stepwise migration of all 12 client accounts to the new Jentis infrastructure. Full validation of each account before go-live: event matching, Consent Mode v2 compliance and first-party cookie verification. Two-week parallel operation with the previous tracking to verify data consistency.

4

Unified Reporting System (Weeks 13–16)

Development of Data Studio report templates in 3 variants: e-commerce, lead generation, branding. Automated daily data refresh. Each new client receives a complete, customised dashboard within 2 hours. Team training on the new system.

Results after 16 weeks

-70%
tracking maintenance effort
2h
onboarding new clients (instead of 3–4 weeks)
12/12
accounts migrated to server-side
100%
standardised data quality

"The tracking infrastructure that rhyn.digital built has completely relieved our team. We onboard new clients in hours instead of weeks — and at higher data quality than ever before."

Lena B.
Head of Digital, Performance Agency

Key Learnings

  • Standardisation pays off massively for agencies with 5+ client accounts
  • Jentis is ideal for agencies with multiple clients as a multi-tenant infrastructure
  • A unified reporting system considerably increases perceived quality with clients
Our Methodology

What all three projects have in common

Despite different industries and challenges, all our projects follow the same core principles.

01

Audit before implementation

We build nothing before we understand what is already in place and why it isn't working. A thorough audit saves time and prevents repeating old mistakes in a new form.

02

Measurement plan first

What should be measured? Why? And what decisions should the data enable? These questions we answer together — in writing, before the first tag is set.

03

Validation after every step

Every implementation is fully validated before going live. No assumptions, no "should work" — but measurable confirmation that the data is correct.

04

Handover & documentation

Every project ends with complete documentation and a handover training. The team should understand, maintain and further develop the implementation.

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