--- title: "One metric, three meanings: Niko van Eeghen of Evondos | Skene" description: "Evondos's Niko van Eeghen shows one metric meaning freedom to a patient, budget to a buyer and lost quiet time to a nurse, and why access shapes product data." url: https://www.skene.ai/resources/the-question/niko-van-eeghen doc_version: "c00117dbc7a2" last_updated: 2026-10-30 --- Resources / The Question / Issue 10 # Niko van Eeghen: one metric, three meanings at Evondos Niko van Eeghen. Chief Product and Marketing Officer at Evondos. Issue 10 of The Question, published by A Founder's Friend on 22 August 2026. By [Nicolas Dolenc](https://afoundersfriend.substack.com), author of A Founder's Friend. Skene adapted this page from his published issue. Between home visits, a nurse gets twenty minutes in the car with the radio on. Evondos's medicine-dispensing robot removes most of those visits, which looks like pure gain on a chart. Some nurses told Niko van Eeghen they value that drive, because it is the one calm moment in a hectic day. **The short answer:** The number is rarely the hard part: one metric means different things to different people, and in parts of the economy you cannot or may not collect it. ## What Niko van Eeghen trusts, and for what | Evidence | Trusted for | Not trusted for | | --- | --- | --- | | Engagement data | Spotting opportunities and validating concepts fast | Measuring impact on people | | Dispense moments, the proxy for time given back | The outcome Evondos chases | A single meaning: patient, buyer and nurse read it differently | | AI pattern-finding across 600 feedback points | Patterns at a volume a person cannot read without bias | Nuanced problems, which still need a person | | In-person conversations with nurses | The rare, high-value why | Scale: access goes through customers | ## The same metric, three meanings Evondos chases giving time back, and its proxy is dispense moments. For an elderly person, fewer visits mean not waiting at home three times a day for a nurse who might be late. For the care organisation, they mean money and time to spend on people waiting for care. For the nurse, they can mean losing the quiet drive between clients. Only one of those readings shows up on a dashboard. > The same metric that you’re chasing means very different things and delivers very different types of value depending on the person it’s touching. Niko van Eeghen, in Issue 10 ## Treat AI conclusions like lead scores Evondos uses AI to find patterns across 600 NPS and support feedback points across eight languages. Niko is clear that the machine wins on capacity, not judgment. For bug patterns he will trust it. For anything nuanced he treats its output the way a decade of CRM taught him to treat intent scores: a probability that points at an angle worth exploring. > You can rank people visiting your website on their intent and whether you think they’re going to be a high-quality lead. But that doesn’t mean that they are. It just talks about the probability. Niko van Eeghen, in Issue 10 ## Sometimes the number is not available At Vaadin, an open-source framework shipped into the world and was never observed in use. At Evondos, devices sit in healthcare, where certain data may not be tracked because it is too private to risk. Talking to nurses means asking customers to give up paid time, so it happens in person and is never handed to a bot. He also names a cost nobody prices. Automate the reading of your own feedback and you keep the information but lose the exposure that changes how a team thinks. > So we actually do it all in person, because we can’t afford to throw away that golden moment to speak to somebody through a bot. Niko van Eeghen, in Issue 10 ## What to do with this For your top metric, write down who it touches and what it means to each of them. If one of those meanings would change the decision and no chart shows it, that is the conversation to book this month. For seven checks drawn from across the series, see the [questions to ask before trusting a number](https://www.skene.ai/resources/the-question#before-you-trust-a-number). ## Frameworks this interview tests - [North Star Metric](https://www.skene.ai/resources/frameworks/north-star-metric): A North Star Metric is the one number that captures the value customers get. It is usually built from several events, so a break in any one of them moves every team. - [Product-qualified lead (PQL)](https://www.skene.ai/resources/frameworks/product-qualified-lead): A product-qualified lead is scored on what someone did in the product, not on a form they filled in. That makes the score exactly as accurate as the events behind it. - [Jobs to be done (JTBD)](https://www.skene.ai/resources/frameworks/jobs-to-be-done): Clayton Christensen's jobs to be done says customers hire a product to make progress. The job decides which events matter, so interviews come before the tracking plan. ## Read next in The Question - [AmirBahador Bahadori: product data is three layers, not one](https://www.skene.ai/resources/the-question/amirbahador-bahadori) - [Maria Petrova: data tells you what happened, never why](https://www.skene.ai/resources/the-question/maria-petrova) - [Emad Ghorbaninia: five analytics tools or one five-minute call](https://www.skene.ai/resources/the-question/emad-ghorbaninia) - [What all fourteen interviews add up to](https://www.skene.ai/resources/the-question) ## Source and disclosure [Read Issue 10 on A Founder's Friend](https://afoundersfriend.substack.com/p/aff-the-question-issue-10-making). Quotations on this page are copied from the published issue. Skene sponsored this research and commissioned it on a single question. A Founder's Friend ran the interviews, wrote them up and published them, and the series states that Skene paid for the research and did not direct the questions, the analysis or the conclusions. Each of the thirteen interviews was reviewed and signed off by the person in it, named or anonymous by their choice. Appearing in the series is not an endorsement of Skene, and nobody here is presented as a Skene customer. ## Sitemap - [Markdown sitemap](https://www.skene.ai/sitemap.md): every page on this site, with its markdown counterpart. - [Index for language models](https://www.skene.ai/llms.txt): the same set as a link-dense index. - [Full corpus](https://www.skene.ai/llms-full.txt): reference content concatenated as plain text.