Why Your Best Users Don't Look Like Your Average Users
The users who drive most of your revenue and retention often don't match your "average" user profile. They come from different sources, behave differently, and have different needs. US teams that identify and double down on their best users grow faster than those who optimize for the average.**
You have an "average" user. You've built personas. You've designed for them. You've acquired for them.
But your best users: the ones with highest LTV, best retention, most referrals: might not look like the average at all. They might come from a different channel. They might use different features. They might have a different company size or use case. Optimizing for the average might mean underserving your best users and over-investing in users who don't stick.
Find your best users. Design for them. Acquire more of them.
Defining "Best"
Options
- Highest LTV: Revenue per user over 90 days or lifetime
- Best retention: Still active after 6-12 months
- Most referrals: Invited teammates or referred others
- Power users: Highest engagement, most features used
- Expansion: Upgraded plan or added seats
Pick one or combine. Create a segment. These are your "best" users.
What Best Users Often Look Like
Different Sources
Your average user might come from Google Ads. Your best users might come from organic search, a niche community, or referrals. Volume and quality are often inversely correlated. The channel with the most signups might not be the channel with the best users.
Different Behavior
Best users might:
- Activate faster
- Use more features
- Invite teammates sooner
- Hit the "power user" actions in Week 1
The average user might do one or two things. The best user does five. Behavior differentiates.
Different Demographics
Best users might be a different company size, industry, or role than you assumed. Your persona might say "SMB marketing managers." Your best users might be "solo founders" or "enterprise product teams." Demographics can surprise you.
How to Find Your Best Users
1. Segment by Outcome
Filter users by LTV, retention, or referral. Who's in that segment?
2. Analyze Their Attributes
Source. Behavior. Demographics. What do they have in common? What's different from the average?
3. Compare to Average
Build a comparison: best users vs. everyone else. Source mix. First-week behavior. Feature usage. The differences are your optimization targets.
4. Design and Acquire for Best
- Product: Make the experience that best users have the default for everyone
- Acquisition: Invest in the channels and content that attract best users
- Onboarding: Guide new users toward the behavior that best users exhibit
SingleAnalytics lets you segment by events, properties, and outcomes. Compare best vs. average. Find the pattern. Act on it.
Real Impact
A US B2B tool assumed their best users were "teams of 5-20." They built features for collaboration. When they segmented by LTV, they found: their best users were solo operators and very small teams (2-3 people) who used the product daily. The "team" segment had lower retention and LTV. They shifted roadmap to serve the solo power user. Retention and revenue both grew. The average had misled them.
Ready to find your best users? Segment and compare with SingleAnalytics and design for who actually drives your business.