SaaS & Software
Two brands, one site, no traffic lost. Two brands became one, and Google traffic did not drop
Visits from Google held steady through the switch.
The client
A growing software company combining two brands into one.
- Sector
- SaaS & Software
- Published
- Anonymised at the client’s request.
Case 01 / 01 · SaaS & Software
01 · Who they are
A growing software company combining two brands into one.
What Growth Systems involves.
- 01See what each channel really did
- 02Decide what success is before launch
- 03Onboarding, win-back and upsell
- 04AI only where it beats a simple rule
- 05Trace every result to a decision
- 06Wait for a real trend
See what each channel really did
Build attribution infrastructure that survives real-world messiness — multiple touchpoints, delayed conversions, and channels that don't share data cleanly by default
Decide what success is before launch
Design and instrument acquisition experiments with a defined success metric before launch, not a metric chosen afterward to justify the spend
Onboarding, win-back and upsell
Build lifecycle and retention flows — onboarding, win-back, upsell — with the segmentation logic and triggers behind them made explicit
AI only where it beats a simple rule
Apply AI to personalization or prediction specifically where it outperforms a simpler rule, and use the simpler rule where it doesn't
Trace every result to a decision
Set up the reporting layer so a result is traceable back to the specific decision that produced it, not just to a channel
Wait for a real trend
Run the system long enough to separate a real trend from noise before recommending a change based on it
Questions people ask before buying
01 / 06
Does it cost anything to ask?
No. You describe one problem, plainly, in a few sentences, and we tell you if it is worth building. That answer is free. No discovery invoice, no proposal deck.
02 / 06
What if AI is the wrong tool?
We tell you. A simpler rule, or no change at all, is sometimes the honest recommendation, and we would rather say so than build something that should not exist.
03 / 06
How will we know it works?
Where an engagement carries a measurable target, that target is written into the contract with a defined test, not implied by a case study.
04 / 06
Who can see our data?
Client data is processed only for the engagement it was provided for, and only by the people working on it. Access is granted per project and removed when the engagement ends.
05 / 06
Do we own what you build?
Documentation and runbooks are written for the engineers who take it over. We would rather leave cleanly than become a dependency you cannot remove.
06 / 06
Can you guarantee the result?
No, and you should treat any firm that does with suspicion. The figures on this site are real, but each one came from one specific client. What we can do is write your target down and test against it.
Your problem
Describe it plainly. We will tell you if it is worth building.
Next case study · +210%
We wrote about the real problems their buyers search for. Demo requests from Google tripled.