Tivalio
Correlation is Not Causation: Interpreting TTV Data Safely
We all know the mantra: "Correlation is not Causation." But in the heat of a product launch, when we are desperate for a win, we often forget it.
The Classic Trap: The "Power User" Correlation
Let's say you look at your activated users and find a strong correlation:
"Users who upload a profile avatar activate 2x faster and retain 3x longer."
Your instinct might be:
"Great! Let's force everyone to upload an avatar during onboarding! We'll double our retention!"
What happens? Activation drops. Retention stays flat. Why? The users who uploaded an avatar were already highly motivated. They were "Power Users" by nature. Uploading the avatar didn't cause them to succeed; it was a symptom of their desire to succeed. By forcing low-motivation users to do it, you just added friction without adding motivation.
The Selection Effect
In PLG analytics, your best users will naturally do "more stuff."
- They read the docs.
- They join the webinar.
- They customize their settings.
These actions correlate with success, but they are often Results of Success, not drivers of it.
Descriptive vs. Causal AI
This is why Tivalio's AI is built to be strictly Descriptive.
We will tell you:
"Users who skip the product tour have a higher TTV spread."
We will NOT tell you:
"Skipping the tour CAUSED the high spread."
Maybe the users who skipped the tour are impatient. Maybe the tour is actually helpful. The data describes the reality, but you provide the "Why."
How to Act on Correlations Safely
So if correlation isn't causation, is it useless? No. Correlation is a Hypothesis Generator.
- Stage 1 (Correlation): You see that "Users who invite a colleague activate faster."
- Stage 2 (Hypothesis): "I believe that if we encourage invites earlier, more users will activate."
- Stage 3 (Experiment): Run an A/B test. Group A gets the normal flow. Group B gets a "Invite your Team" prompt on Step 2.
- If Group B works better -> Causation Confirmed.
- If Group B churns -> Selection Effect Confirmed.
Conclusion
Be humble with your data. It tells you what happened. It tells you who it happened to. But the cause is usually hidden in human psychology, not in the database rows. Use Tivalio to find the clues, but use your brain to solve the crime.