# Every NPS dashboard — analysis readout

Deliverable: [Open the static NPS dashboard](./nps_dashboard.html)

## Headline

Every scores **+45.1 NPS** across 195 open-text responses. The score is healthy and top-heavy: 107 promoters (54.9%), 69 passives (35.4%), and 19 detractors (9.7%). The median response is 9 and the mean is 8.38. In total, 176 of 195 responses (90.3%) are 7–10.

## What members value

- Every is most often understood as a combination of an AI newsletter/publication and a suite of AI tools or products.
- The strongest qualitative promise is practical, applied AI: helping people understand and use AI in daily work without hype or overwhelm.
- Promoters especially use language around frontier thinking, high-signal analysis, usefulness, productivity, and “learning how to use AI.”
- The hybrid model is a differentiator: people like that the team builds products and shares what it learns while building them.

## What is holding the score back

- **Product clarity:** some respondents can describe the writing easily but cannot explain the product suite; one passive answer is simply “No idea honestly,” and a detractor calls the products confusing.
- **Access expectations:** Mac-only availability is a repeated concrete complaint in the low-score tail. It is especially damaging when tool availability is discovered after subscribing.
- **Trust, security, and price:** one detractor does not use the apps for security reasons; another describes pricing and monetization as a breach of trust. A high-priced Claude class is also called out as out of touch.
- **Brand evolution:** a few former fans perceive a shift away from the earlier broader tech/business writer bundle toward AI and product building, making Every feel less interesting or less relevant to them.
- **Experience consistency:** the long detractor response criticizes the survey text box itself, suggesting that design-sensitive members notice gaps between Every’s product/design philosophy and the surrounding customer experience.

## Recommended actions

1. Make the subscription promise concrete above the paywall: show the content, product list, supported platforms, eligibility, and what is included today.
2. Add a simple “start here” path for products, with use cases, setup time, security posture, platform support, and a recommended first app.
3. Treat platform coverage and security as conversion/trust content, not footnotes. Make limitations visible before purchase.
4. Explain the evolution from media collective to AI-native product studio in a way that preserves the original editorial value for members who joined for writing.
5. Protect the content moat while improving activation: the comments suggest many members value the writing alone, while the software bundle is the differentiator that needs clearer proof of value.

## Method note

NPS is calculated as the share of 9–10 ratings minus the share of 0–6 ratings. The theme counts in the dashboard are directional, overlapping qualitative coding of the comments; a single response can mention multiple themes. No interactive questions or missing-data assumptions were required because the supplied CSV had a score and description for all 195 rows.