...
Split traffic | Page trigger | Segment | Goal A: User conversion rate (sales per user) | Goal B: Sessions per user | Goal C: Bounce rate |
|---|---|---|---|---|---|
50% Test | myhomepage.com | 40% non-preezie users | 3.2% | 2.4 | 23% |
10% preezie users | 4.5% | 3.2 | 0% (preezie counts as a significant event) | ||
50% non/preezie users | |||||
50% Control | 50% non-preezie users | 3.1% | 2.6 | 25% |
Once you can see these the buckets are gaining a good level of traffic (e.g. use a an A/A test to understand how long your website traffic needs to acheive achieve even conversion rates), you can start to compare the preezie 10% against the 50% who never saw it and the 40% who did see it but didn’t engage. This .
Control
1000 users / 31 sales = 3.1% conv rate
Test
1000 users / 37 sales = 3.5% (+12% against control)
non-preezie @3.2% conversion (+3% against control) = 26 sales
preezie @4.5% conversion (+45% against control) = 9 sales
Even if you account for the +3% increased in non-preezie conversion, the preezie bucket although smaller shows at least a +40% increase.
Tracking user conversion will tell you the user level impact of preezie across sessions, so you can compare the influence of these preezie engaged users, e.g. sessions per user increases.
...
| Tip |
|---|
Tip: If your primary goal is something more reflrective reflective of impact to users who need help (e.g. nexw user bounce rate) then you should probably can analyse the 50/50% on the total results as usual. |
...