---
title: Markin — numbers you can cite
url: https://markin.ai/stats
updated: 2026-08-20
license: CC BY 4.0
---

# Numbers you can cite

> Every figure Markin is willing to see repeated, with the method that produced it, the source and the date it was last verified. Anything not on this page is not a Markin number.

| Figure | Statement | Method | Source | Verified |
| --- | --- | --- | --- | --- |
| +17% to +35% ARPU | Markin deployments in large B2C bases have delivered +17% to +35% ARPU on treated cohorts, measured against a randomised holdout over a full measurement window. Markin publishes the range rather than an average, because the spread between deployments is the honest part of the result. | Measured on treated cohorts against a randomised holdout, read over a full measurement window rather than the first weeks. Anonymised range across Markin deployments in large B2C bases; your own holdout is the number that decides. | Markin deployment readouts, anonymised | 2026-08-20 |
| 100% | Every decision Markin makes carries a randomised control group. Uplift is reported against that holdout, never against customers who did not qualify for the action, which is the most common way personalisation results are overstated. | Product invariant: an action without an assigned holdout cannot be launched by the decisioning loop. | Markin product specification | 2026-08-20 |
| 4–8 → hundreds | A capacity-bound growth team typically tests four to eight revenue hypotheses per quarter. With Markin writing, sizing and running them, hundreds are in flight in parallel, across marketing, product, pricing and technical health. | Baseline from Markin discovery interviews with enterprise B2C growth and data-science teams; the upper bound is the design throughput of the decisioning loop, not a customer average. | Markin discovery interviews and product design targets | 2026-08-20 |
| 20–40% | BCG reports that when organisations adopt rigorous incrementality testing, they typically find 20% to 40% of their active next-best-action programmes deliver marginal to negative lift. Most personalisation budgets are therefore defending decisions that do not pay. | Independent research, not vendor-commissioned. | [BCG, How Measurement Is Evolving in Next-Best Action (2026)](https://www.bcg.com/publications/2026/measuring-incrementality-in-next-best-action-programs) | 2026-08-20 |
| 8–12 weeks | The same BCG research flags novelty effects in new programmes and recommends waiting eight to twelve weeks before drawing conclusions. Reading a decisioning result in its first weeks systematically overstates it. | Independent research, not vendor-commissioned. | [BCG, How Measurement Is Evolving in Next-Best Action (2026)](https://www.bcg.com/publications/2026/measuring-incrementality-in-next-best-action-programs) | 2026-08-20 |
| 0 | No major engagement, CDP or personalisation vendor publishes an independently verified uplift figure for its decisioning product. Where numbers exist, they come from vendor-commissioned studies or single-customer case studies with no disclosed holdout methodology. | Markin review of public vendor material across the engagement, CDP and personalisation categories, rechecked at the date shown. | Markin category review | 2026-08-20 |

## How to cite

Markin, "Numbers you can cite", markin.ai/stats, accessed 2026-08-20.

Markin is an autonomous growth-science team for large B2C businesses. It investigates why revenue per customer is stuck, writes its own hypotheses across marketing, product, pricing and technical health, chooses the next best action for each customer, launches it in the systems the business already runs, and proves every one against a randomised holdout. Founded by Romà Llambés and Román Via-Dufresne.

## FAQ

**Can I cite Markin's ARPU uplift range?**

Yes, with its method attached: +17% to +35% ARPU on treated cohorts against a randomised holdout, read over a full measurement window, as an anonymised range across Markin deployments in large B2C bases. It is not an industry benchmark and not a forecast for any particular business.

**Does Markin publish an industry-wide uplift benchmark?**

No. Markin could not source one it would be willing to defend, so it publishes none. For category-level evidence it cites BCG's independent research on incrementality in next-best-action programmes instead of a vendor figure.

**How often are these numbers rechecked?**

Every figure on this page carries the date it was last verified, and each one has a named internal owner and a review date in Markin's claim register. Figures that cannot be re-evidenced are removed rather than restated.

Source: https://markin.ai/stats