When ManyChat’s growth stalled under manual experiment workflows, the engineering team faced duplicated holdout logic and analysts acted as “human microservices.” The bottleneck forced product ideas into later sprints, eroding velocity. Seeking a unified solution, the company opened a vendor search that landed on two modern platforms—Eppo, recently acquired by Datadog, and Statsig, fresh from an OpenAI purchase.

To avoid costly blind trials, the team built a three‑stage vetting process: desk research trimmed the list, focused demos probed required features, and hands‑on proofs‑of‑concept ran real data through each finalist. Interviews with PMs, analysts, engineers and marketers turned anecdotal pain into a concrete requirements matrix, keeping leadership aligned and narrowing the field to the two contenders.

During the final debrief the analyst panel scored Eppo at 4.36 and Statsig at 4.47 on a five‑point scale, a statistical tie that surprised the author. The exercise revealed that modern experimentation tools now deliver baseline rigor, so the decisive factor shifted to subtle workflow preferences and long‑term vendor lock‑in. In the end ManyChat committed to Eppo, citing significantly smoother integration with existing Datadog observability.