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Impact reports show clients what each change did.
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Show clients what changed
A simulated impact report. Pick a change to see its before and after.
rookon · acme-cloud · impact of changes
Simulated dataEach change: 14 days before vs. 14 days after.
12 NovLive
Conversion rate · pages ROOKON changed
4.67% → 5.85%
+1.2 pp since the first ROOKON change
Bounce rate · same pages
41.4% → 38.5%
−2.9 pp since the first ROOKON change
ROOKON changes
2 improved of 3 measured
1 no significant change · 0 worse · 1 collecting
Conversion rate · /billing · 7-day rolling
| Time | conversion rate |
|---|---|
| 14 Sept | 3.1% |
| 15 Sept | 3.1% |
| 16 Sept | 2.7% |
| 17 Sept | 2.5% |
| 18 Sept | 2.5% |
| 19 Sept | 2.4% |
| 20 Sept | 2.5% |
| 21 Sept | 2.8% |
| 22 Sept | 2.7% |
| 23 Sept | 2.7% |
| 24 Sept | 2.9% |
| 25 Sept | 2.9% |
| 26 Sept | 2.9% |
| 27 Sept | 3.0% |
| 28 Sept | 2.9% |
| 29 Sept | 3.2% |
| 30 Sept | 3.5% |
| 1 Oct | 3.4% |
| 2 Oct | 3.6% |
| 3 Oct | 3.7% |
| 4 Oct | 3.5% |
| 5 Oct | 3.6% |
| 6 Oct | 3.5% |
| 7 Oct | 3.4% |
| 8 Oct | 3.7% |
| 9 Oct | 3.3% |
| 10 Oct | 3.1% |
| 11 Oct | 3.5% |
| 12 Oct | 3.8% |
| 13 Oct | 3.9% |
| 14 Oct | 3.7% |
| 15 Oct | 3.2% |
| 16 Oct | 3.6% |
| 17 Oct | 3.9% |
| 18 Oct | 3.9% |
| 19 Oct | 3.7% |
| 20 Oct | 3.7% |
| 21 Oct | 3.8% |
| 22 Oct | 4.4% |
| 23 Oct | 4.6% |
| 24 Oct | 4.5% |
| 25 Oct | 4.3% |
| 26 Oct | 4.3% |
| 27 Oct | 4.3% |
| 28 Oct | 4.4% |
| 29 Oct | 3.9% |
| 30 Oct | 3.7% |
| 31 Oct | 3.6% |
| 1 Nov | 3.7% |
| 2 Nov | 3.8% |
| 3 Nov | 3.7% |
| 4 Nov | 3.7% |
| 5 Nov | 3.8% |
| 6 Nov | 3.7% |
| 7 Nov | 3.7% |
| 8 Nov | 3.6% |
| 9 Nov | 3.7% |
| 10 Nov | 3.6% |
| 11 Nov | 3.7% |
| 12 Nov | 4.1% |
Shaded: baseline and after windows of the selected change.
It was better before
“Release v2.15.0: new onboarding checklist”
Bounce rate +2.6 pp (32.9% → 35.5%)
p < 0.001 (Holm-adjusted) · 14 days before vs. after
Either way, ROOKON won’t propose this exact change again. A different approach to the same page is still allowed.
Overlaps with “Release v2.15.0: new onboarding checklist”, so part of the difference may come from that change.
Observed changes between equal windows before and after each change, tested for significance (two-proportion z-test for rates, Welch’s test for durations, Holm-adjusted, p < 0.05). This shows association, not proof of cause: seasonality, campaigns and other releases can contribute, so overlapping changes are flagged.
Every day
What Rooky looks after.
- Errors and outages across all client sites
- Conversion drops after a client’s release
- Broken pages and redirects after a redesign
- SEO opportunities with the Marketing Engine add-on
- Alerts to each client’s own Slack or email
- Before-and-after reports for every change
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FAQ
Questions, answered.
How do I keep clients apart?
Create one workspace per client. Data, team members and settings are fully separated, and you can invite the client into their own workspace.
Can my clients see the results?
Yes. Invite them as viewers, share the impact report, or give them a public status page with their uptime.
Is there something in it for agencies?
Yes. Through the partner program you earn a commission when clients you refer become paying customers.
Let Rooky look after your clients.
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