Conversion tracking & analytics
Where data
meets decisions
Most teams collect data but struggle to connect it to what's actually happening in the business. Bonuscircuit works with groups to build the tracking infrastructure and analytical habits that close that gap - practically, not theoretically.
See how it works
The people doing the work
Each facilitator at Bonuscircuit has worked directly inside marketing or product teams before moving into an advisory and training role. That distinction matters - the frameworks taught here were stress-tested in real conditions first.
Callum Drenthe
Lead Analytics Facilitator
Spent eight years running paid acquisition at mid-size e-commerce companies before focusing entirely on measurement infrastructure. Has rebuilt tracking setups for teams across retail, SaaS, and services.
Ingrid Halvorsen
Group Programme Lead
Background in organisational learning and digital strategy. Designs the group formats that make technical content accessible to mixed-skill teams without flattening the depth.
Built from practice
Bonuscircuit, Sydney
Founded when a recurring pattern became clear: teams had access to the same data but reached wildly different conclusions. The group format was chosen deliberately - shared analysis builds shared understanding faster than solo training.
What needs to be in place before this works
Group work on analytics isn't a shortcut for teams that haven't yet decided to take measurement seriously. The sessions are structured, but they require participants who are already willing to question how their current data is collected and interpreted.
There's a baseline that makes the work productive. It isn't about technical skill level - it's about attitude toward uncertainty and willingness to revisit assumptions.
- Access to at least one live tracking environment (GA4, server-side, or tag manager setup)
- A defined business question the team is trying to answer - not just "improve our data"
- At least two people from the same team attending, so the learning transfers into actual working practice
- Openness to finding that current tracking is incomplete or misleading
What the working relationship involves
Sessions are structured around a group's actual tracking setup, not a generic curriculum. The facilitator works through real data problems with the group rather than presenting theory for later application.
Audit
The group maps what is currently being tracked, what is missing, and where data is being misread. This surfaces the actual gaps rather than assumed ones.
Live sessions
Weekly group sessions, two hours each, work through specific problems. Participants bring their own reports and tracking questions. Discussion is the method - not slides.
Between-session work
Each session ends with a small, defined task. Not homework for its own sake - each task tests whether the session's conclusions hold up against the group's real data environment. Results are shared at the next session and reviewed collectively.
What long-term clients consistently describe
After working with groups over several cohorts, certain observations come up repeatedly - not as outcomes we promise, but as patterns participants name themselves when asked to reflect on the experience.
"The first thing that shifted was that we stopped arguing about what the numbers meant. We started asking whether we were measuring the right thing at all."
- Participant, retail marketing team, Melbourne
"Having other teams in the room changed how we thought about our own setup. Seeing someone else's tracking problem made ours easier to articulate."
- Participant, B2B SaaS team, Sydney
"It took about three sessions before the work felt uncomfortable in a useful way. Before that it was clarifying. After that it was actually difficult - which is when it got interesting."
- Participant, media agency, Brisbane
A specific case, in enough detail to be useful
A six-person marketing team at a subscription software company joined a cohort in mid-2023. Their stated problem: their GA4 data showed strong engagement but conversion rates were flat, and they couldn't explain the gap.
In the first session audit, the group identified that the team was tracking page views as conversion events - a misconfiguration that had been in place for eleven months. The data looked healthy because it was measuring the wrong thing entirely.
Fixing the tracking took one sprint. Understanding what the corrected data was actually saying took three more sessions - because the real conversion funnel turned out to be longer and less linear than the team had assumed.
What changed
The team restructured their reporting around the actual conversion path. More importantly, they built a shared internal process for questioning any metric before acting on it - something that persisted after the cohort ended.
The range of situations this addresses
These aren't service categories - they're the kinds of situations that actually bring teams to this work. The common thread is that something in the data isn't adding up, and the team knows it.
Tracking that doesn't match reality
Numbers look reasonable but decisions made from them keep producing unexpected results. The data and the business are describing different things.
Platform migration uncertainty
A move from Universal Analytics to GA4, or from client-side to server-side tagging, has left the team unsure whether the new setup is capturing what the old one did.
Conflicting reports across tools
The CRM, the ad platform, and the analytics tool each show different numbers for the same period. The team spends more time reconciling reports than acting on them.
Attribution that nobody trusts
Last-click, first-click, data-driven - the team has tried different models and each one produces a different channel ranking. Confidence in the attribution data has eroded to the point where it's rarely used.
New team members inheriting old setups
Someone left, someone new arrived, and the tracking documentation either doesn't exist or doesn't match what's actually implemented. The new person is making decisions without knowing what the data is actually measuring.
Scaling pressure on measurement
What worked when the team was small and the budget was modest no longer holds up. More channels, more products, more stakeholders asking for numbers - and the current setup wasn't built for that volume.
