Curate your comparison pool deliberately

Choose who you regularly compare yourself to — peers at a similar stage, not outliers at the peak.

Why it works

Festinger’s original theory held that people prefer to compare with similar others when evaluating ability. Algorithmic social media violates this preference by surfacing outliers — the best-performing, most aesthetically curated, most successful examples. Actively curating a comparison pool of genuinely similar peers restores the validity of the comparison and produces accurate, useful data.

How to do it

1. Identify people at a similar stage of your journey — not the top 1% but people who started where you are and are six months to two years ahead.
2. Seek out communities, forums, or relationships where the population is similar rather than aspirational outliers.
3. Use genuinely outstanding people as inspiration ("this is achievable") rather than as benchmarks ("I should already be here").
4. Regularly audit who you’re comparing to and recalibrate when the pool drifts toward outliers.

Evidence

Festinger (1954) established the original theory: comparison is most informative and least distorting when done against similar others. This principle underpins the harm of algorithmic feeds that surface dissimilar outliers. (observational)

Practical pool-curation advice extrapolates from the original theory; direct RCTs on curated comparison pools are limited.

Sources

• Festinger (1954), "A theory of social comparison processes," Human Relations

Common mistake

Choosing a comparison pool of people slightly behind you — which produces false reassurance but no useful calibration for where to grow next.