Luca HBS WP 12-016 — one-star Yelp = 5-9% revenue (regression-discontinuity, the causal anchor)

Claim: Michael Luca, Harvard Business School NOM Unit Working Paper 12-016, "Reviews, Reputation, and Revenue: The Case of Yelp.com" (2011, rev. 2016), using a regression-discontinuity design on Washington State Department of Revenue data (exploiting Yelp's rounding thresholds):

Verbatim: "a one-star increase in Yelp rating leads to a 5-9 percent increase in revenue... this effect is driven by independent restaurants; ratings do not affect restaurants with chain affiliation."

This is one of the few causal — not merely correlational — findings in this whole research domain.

Source: Luca 2011/2016, HBS NOM WP 12-016. Non-vendor / academic.

Confidence: Verified (peer-reviewed-grade causal). Caveat: Seattle restaurants; generalization to other verticals is inference. The paper remained an influential working paper rather than a journal article under this title.

Why this matters for Candid: The single most credible causal datapoint in the entire research domain. The "independent restaurants" finding is especially relevant — most Candid SMB clients ARE independents, not chains. This is the strongest single piece of evidence behind any "invest in your reviews" recommendation.