Insights
What growth actually looks like
Guides to the metrics that matter, real diagnostics, and the product thinking that ties them together.
Our product podcast
Datadrivet
55 episodes on building product with data, in one place. Years of it, where a lot of this thinking started.
- growth "Book a Demo" only is costing you the deal Read →
- discovery A PM's first job is to test the business assumption Read →
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Benchmarks B2B SaaS Growth Benchmarks 2026: Metrics That Matter Read → -
Benchmarks B2B vs Consumer Growth: Why Benchmarks Differ Read → - Benchmarks Benchmark Watch: July 2026 Read →
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Concepts Benchmarks Are Context, Not Targets Read → -
Benchmarks Consumer App Benchmarks 2026 (Retention, K-Factor, CAC) Read → - experimentation Do you know your product team's win rate? Read →
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Guides Free Product Growth Benchmark Calculator (B2B & Consumer) Read → -
Guides How to Benchmark Startup Growth Without a Data Team Read → -
Retention How to Read a Retention Curve: Plateau & Slope Read → -
Diagnostics Improve K-Factor Without a Referral Program Read → -
Retention Is My Churn Normal? Leaky Bucket vs Dead Product Read → -
Diagnostics LTV:CAC Too High? Why You're Not Growing Read → - outcomes Most people aren't actually outcome-driven Read →
- ways of working My AI Setup: How a Product Person Runs Claude Code Read →
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Concepts The Cohort-Based Growth Model, Explained Read → - Concepts What 'Product' Really Means Read →
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Retention What Is a Good 90-Day Retention Rate? Read → -
Metrics What Is a Good Activation Rate? (How to Define It) Read → -
Metrics What Is a Good CAC Payback Period? (Benchmarks) Read → -
Retention What Is a Good Day-1, Day-7 and Day-90 Retention Rate? (2026 Benchmarks, B2B vs Consumer) Read → -
Metrics What Is a Good LTV:CAC Ratio? (Benchmarks) Read → -
Metrics What Is a North Star Metric (and How to Pick One) Read → - Metrics What Is K-Factor? The Growth Multiplier Explained Read →
- Concepts What Is PLG (Product-Led Growth)? (2026 Guide) Read →
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Concepts What Is Product-Market Fit, Really? Read → -
Metrics What's a Good MAU Growth Rate? MoM Benchmarks & Model Read → - startups Why Consultancies Struggle to Become Product Companies Read →
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Diagnostics Why Is My CAC Payback Too Long? (And How to Fix It) Read → -
Retention Why Is My Retention Dropping After Day 1? (Diagnosis) Read → -
Concepts Why You Can't Fix One Metric in Isolation Read → - growth Your growth loop is just a drawing until you measure it Read →
- onboarding Your onboarding is your most honest conversion metric Read →
- Episode 6 questions users need answered to convert Datadrivet with Storytel's Seif Fendulky on conversion: the six questions a user needs answered before they buy, plus a classic A/B testing mistake to avoid.
- Episode 7-day retention: where most new users disappear Datadrivet on 7-day retention: why a company losing 80% of new users was wasting acquisition spend, and three practical steps to make users come back.
- Episode 9 Chrome extensions for product managers Datadrivet runs through nine practical Chrome extensions for product managers, from full-page screenshots and tech-stack detection to load-time checks and Loom.
- Episode A process for generating and prioritizing ideas Datadrivet on how a team gathers test ideas, clusters them into tracks, votes, and ranks the hypotheses with a modified ICE score so the best bets rise.
- Episode A year since last time, what we've learned Datadrivet returns after a year away. Joni, Jasmin and Linda from scilla.studio on building the studio through client work, hiring and testing their own ideas.
- Episode Active vs passive churn, and why the split matters Datadrivet on the two kinds of churn: the customers who decide to leave versus the ones who leave by accident, and why each group needs its own kind of fix.
- Episode Amanda AI, from idea to growth Datadrivet talks to Amanda AI CTO Torkel Ohman about automating ad creation for Google, Meta, and Bing, and growing from a drop-shipping test to a team of 30.
- Episode App Store Optimization, with Jimmy Hagelfors Datadrivet with Jimmy Hagelfors (Brick) on App Store Optimization: what to optimize, when to ask for reviews, A/B testing in the stores, plus five tips.
- Episode Are you stuck in the Product Death Cycle? Datadrivet on the Product Death Cycle: why shipping the features users request rarely lifts adoption, and why the users who already left hold the real learning.
- Episode Concrete examples of product-led growth Datadrivet explains product-led growth with two examples, Slack and Neo4j, where bottom-up adoption spread inside companies until buying became inevitable.
- Episode Customer Health Score: a B2B tool for retention Datadrivet with Avinode's Alexandra MacRae on the Customer Health Score: NPS, CES, CSAT and activity in one red-yellow-green matrix that drives action.
- Episode Data-driven is a change the whole org has to make Datadrivet with Valtech's Zarko Lindqvist on why being data-driven is a whole-org mindset, with lessons from Kivra's two-tests-a-week and Cancerfonden.
- Episode Don't call it a Growth team Datadrivet on how to start a growth team: why the name can work against you, where the team belongs in the org, and where to point the first experiments.
- Episode Faster product discovery without code Datadrivet with Isa Cederberg (Birds Relations) on no-code product discovery: testing a prototype, Typeform and Bubble.io, a testable build in 3 to 4 weeks.
- Episode Five questions to ask your users Datadrivet talks to Loop54's Adam Hjort about a five-question survey he sends users every six months, plus why churned customers are worth a phone call.
- Episode Focus on user problems before sales or funding Datadrivet with Theresia Silander, founder of Eatit, on the mistakes the healthtech startup made and the fixes that came from starting with the user's problem.
- Episode How a team experiments matters as much as what Datadrivet on why experiment throughput stalls: a workshop with a team that scaled from zero to five experiments a month and wants ten, and what held them back.
- Episode How do you recruit for a growth team? Datadrivet goes behind the scenes on growth-team hiring: why a standard job ad boxes in the role, and what the Growth Hackers Sweden community suggested.
- Episode How Dreams spreads insights across the org Datadrivet with Kathleen Asjes, Head of Research and Insights at Dreams, on a shared customer journey and weekly sessions that get insights to every team.
- Episode How Gardenize got direct ROI from data-driven work Datadrivet talks to Gardenize CEO Jenny Rydebrink about app store optimization, cleaning up event tracking, and an onboarding change that doubled upgrades.
- Episode How Heja grew to 130,000+ teams with 13 people Andreas Quensel on how Heja grew past 130,000 teams with 13 people: one clear activation metric, an end-to-end growth model, and data as the team's language.
- Episode How Madden Analytics works with customer feedback Datadrivet talks to Petter Flordal of Madden Analytics about asking customers for feedback continuously and building inventory forecasting around real needs.
- Episode How many experiments should we run? Datadrivet on experiment volume: why teams run from a handful a month to a thousand a year, the 10 to 20 percent hit rate, and the roles you need to do it.
- Episode How Polestar measures the customer experience Datadrivet with Polestar's Fredrik Sterner Cederlof on mapping the full customer journey, NPS and CES across 45 digital touchpoints, and feedback in Slack.
- Episode How the analytics team works at TV4 and C More Datadrivet talks to David Jurelius about the five roles a streaming analytics team needs to keep data clean across many platforms before any test runs.
- Episode How throwing away a million lines of code helps Datadrivet talks with Robert Ingemarsson of TimeWave on deleting unused features, why customers never complained, and the loss aversion behind dead code.
- Episode How to bring user feedback into product development Datadrivet talks to Maria Petrova, VP of Product at Supermetrics, about a regular process for voice of the customer and reviewing user feedback every Friday.
- Episode How to get started with experiments Datadrivet on getting started with experiments: the three test types, real win rates from Google, Facebook and Microsoft, and a weekly loop to start testing.
- Episode How to get the most out of your analyst Datadrivet on working with analysts: why dashboards only show the past, why analysts are best placed to ask the business questions, and how to free their time.
- Episode How to grow with product-led growth Datadrivet on product-led growth: how it differs from marketing-led and sales-led growth, why it weighs retention, plus growth loops, experiments, and examples.
- Episode How to set up your analyst to do their best work Datadrivet talks to Johan Johansson of Carat about senior versus junior analysts and the three conditions an organization needs to keep good analysts.
- Episode Product discovery at Hemnet, with Francesca Cortesi Datadrivet with Hemnet CPO Francesca Cortesi on continuous discovery, a strong A/B-testing culture, and smoke-testing a service against global benchmarks.
- Episode Product management at Readly with Emelie Ardby Datadrivet talks to Readly's Head of Product, Emelie Ardby, about why working data-driven and prioritizing well are the most important parts of the job.
- Episode Product Owner or Product Manager, the difference Datadrivet talks to Isa Cederberg of Birds Relations about the difference between a Product Owner and a Product Manager, from scrum backlog to product strategy.
- Episode Product-led growth at Epidemic Sound, with Mike Rooseboom Datadrivet with Mike Rooseboom of Epidemic Sound on growth inside product, fixing licensing confusion, Core Web Vitals, and an experiment that hurt conversion.
- Episode Product-led growth: 7 traits successful companies share Datadrivet breaks down seven things product-led companies share, from free trials and onboarding to transparent pricing, virality and self-serve buying.
- Episode Six steps to turn data into actions Datadrivet with Johan Johansson (Carat) on a six-step framework for turning data into action: goals, observations, insights, impact, ownership, follow-up.
- Episode Steep: helping teams understand the business Datadrivet with Johan Baltzar, co-founder of Steep, on democratizing analytics, defining metrics first, mobile-first design, and testing visions with users.
- Episode Test a lot and fast, with Björn Idrén of CDON Datadrivet talks with Björn Idrén of CDON on daily data insights, a high-converting Voi download location, Klarna's coffee corner, and Jasmin's insight days.
- Episode The 4 stages of working data-driven in a startup Datadrivet with Carl Lager (ArK Kapital) on the four stages of a startup, what to measure at each, and why qualitative insight matters before you have data.
- Episode The roles in an experiment team Datadrivet on the competencies that let a team experiment at high speed: a four-step setup and the cross-functional roles that make fast testing actually work.
- Episode The thin line between FOMO and product-market fit Datadrivet talks with Erwan Derlyn of Odepar on why startups fail when they build a key first and then hunt for a lock, and how to find demand before you build.
- Episode Validate your ideas fast and cheap Datadrivet with Tom Airaksinen (PE Accounting) on scrappy mixed methods: cheap prototypes, Hotjar surveys, learning SQL, and a survey question that backfired.
- Episode What does a digital analyst do? Datadrivet on the digital analyst role: reading user behavior from numbers, decoding what it means, and turning patterns into ideas the whole team acts on.
- Episode What is a churn flow, and how to build one Datadrivet on the churn flow: the cancellation form with smart logic that tries to keep customers, keeps it pleasant, and shows you why people are leaving.
- Episode What is actually an experiment? A Datadrivet mini-episode on what counts as an experiment. Why A/B tests are one kind, and why agreeing on the definition changed how a team measured its time.
- Episode What is churn, and why it caps your growth Datadrivet on churn: the two reasons to lower it, three real cancellation stories (Hello Fresh, Netflix, Headspace), and how to find which leak is yours.
- Episode What is data-driven? Lessons from Dreams Datadrivet talks to Kathleen Asjes of fintech Dreams about mixing quantitative and qualitative research to know if you're working on the right things.
- Episode What is Growth? The 3-2-1 model explained Datadrivet defines Growth with a simple 3-2-1 model: three areas of work, two working methods, and the one team setup that makes the whole system run.
- Episode What is NPS, and what does a good score look like Datadrivet on NPS: how the 0 to 10 question splits detractors, neutrals and promoters, what scores count as good, and an honest twist for measuring it.
- Episode What is the Next Feature Fallacy? Datadrivet on the Next Feature Fallacy: why shipping the next feature rarely fixes growth, and why optimizing for learning beats optimizing for speed.
- Episode When one data point reshaped a company Datadrivet on Joni's WOW moment from data: 83% of a landing page's visitors were existing customers, and what that one finding changed about budget and teams.
- Episode Which experiments can we trust the most? Datadrivet walks through a hierarchy of evidence: from expert opinion and user research up through analytics, A/B testing, and A/B testing the A/B test.
- Episode Why experiments matter more in a downturn Datadrivet on growing in a downturn: a three-month payback window, shifting to organic channels, fixing activation, and why measurable ROI beats high burn.
- Episode Why fast answers from Google Analytics are gone Datadrivet talks to David Jurelius about tracking, cookie deprecation, ITP, and the groundwork that has to exist before any A/B testing can be trusted.