Henkan Insights

Ideas, conversations and signals.

Henkan Insights publishes independent market reports, practical guides and podcast conversations on experimentation, conversion rate optimisation, personalisation, voice of customer and digital analytics, written for e-commerce, product and customer-experience leaders.

Research & guides

GA4 for Developers: The Event Data Model, Limits and Gotchas You Need Before Writing a Line of Tracking
GA4 for developers: the event data model, scopes, naming rules, collection limits, user_id, (not set) causes and the mistakes you cannot fix later.
How Designers Should Ask for GA4 Tracking: Forms, Filters, Errors and Interactions Annotated in Figma
How UX designers should ask for GA4 tracking: form errors, filters, site search, modals and empty states, annotated in Figma with event specs and no PII.
From Tracking Request to dataLayer Spec: How Developers Should Implement GA4 Events
How developers turn GA4 tracking requests into a dataLayer spec: event-driven pushes, gtag.js vs GTM, single-page apps, ecommerce schema and Consent Mode v2.
GA4 E-commerce Reports for Marketers and Merchandisers: Products, Promotions, Audiences and Revenue
GA4 e-commerce reports for marketers: where the Monetization reports are, item ratios, promotion tracking, cart-abandoner audiences and a weekly trading review.
The GA4 Tracking Plan: How Product, Design, Engineering and Marketing Request, Build and Check Tracking Together
How to run a GA4 tracking plan across product, design, engineering and marketing: request lifecycle, sheet columns, RACI, naming rules, change log and AI.
GA4 for UX and Product Designers: What the Numbers Can (and Can't) Tell You About Your Design
GA4 for UX designers: the design questions GA4 answers, what enhanced measurement misses, and how to read engagement and search data without being fooled.
How to Measure a Product Launch in GA4: Before/After, Annotations and When You Need an A/B Test
How to measure a product launch in GA4: before/after traps, a launch measurement plan, annotations, guardrails, holdouts and when you need an A/B test.
GA4 BigQuery Export and Measurement Protocol for Developers: Schema, First Queries and Server-Side Events
GA4 BigQuery export for developers: linking, daily vs streaming, the nested schema, 5 starter SQL queries, cost control and Measurement Protocol server events.
GA4 for Marketers: The Acquisition Questions It Answers and Why Its Numbers Never Match Your Ad Platforms
GA4 for marketers: user vs traffic acquisition, default channel rules, key events, why GA4 never matches Google Ads or Meta, and 10 standard questions.
Combining GA4 with Qualitative Research and Measuring a Redesign
How to combine GA4 with qualitative research (replays, surveys, usability tests) and measure a redesign: before/after traps, A/B tests, guardrails, one-pager.
Finding UX Friction in GA4: Drop-offs, Devices, Landing Pages and Site Search Step by Step
UX friction analysis in GA4, step by step: funnel drop-offs, backward paths, device and browser splits, landing pages, site search, forms and an impact score.
How Product Managers Should Ask for GA4 Tracking: From User Story to Event Spec
How product managers should write a GA4 tracking request: questions first, event specs, naming rules, custom dimensions, Jira templates and a worked example.
GA4 for Product Managers: The Questions It Answers, the Ones It Can't, and How Not to Be Fooled by the Numbers
GA4 for product managers: the 10 product questions GA4 answers and where, where it stops, and the reading traps (users, key events, sampling, consent) to avoid.
Attribution in GA4 for Marketers: Models, Conversion Paths and How to Judge Channels Fairly
GA4 attribution for marketers: the three models left, lookback windows, the attribution reports, and how lift tests and MMM judge channels fairly.
Debugging and QA for GA4: DebugView, Tag Assistant, Network Requests and Automated dataLayer Tests
GA4 debugging and QA for developers: DebugView, Tag Assistant, reading /g/collect requests, common bugs, a release checklist and automated dataLayer tests.
How Marketers Should Ask for GA4 Tracking: UTM Conventions, Key Events and Ad Platform Links
GA4 UTM campaign tracking for marketers: a naming convention and governance sheet, channel groups, key events, Google Ads links, audiences and consent.
Measuring Feature Adoption in GA4: Funnel, Path, Segment Overlap and Cohort Explorations Step by Step
Measure feature adoption in GA4 step by step: funnel, path, segment overlap and cohort explorations, reusable segments, and adopters vs non-adopters done right.
How Booking.com, Amazon, Microsoft, Google, Netflix and Airbnb Experiment at Scale (and What You Can Copy)
Experimentation at scale at Booking.com, Microsoft, Google, LinkedIn and Netflix: tests per year, win rates, platforms, and the habits you can copy.
Who Owns Experimentation? Choosing an Operating Model: Centralised, Centre of Excellence, Hub-and-Spoke or Federated
Compare experimentation operating models: centralised, centre of excellence, hub-and-spoke and federated. When each fits, when to move, a RACI and guardrails.
Building Momentum in an Experimentation Programme: Progress over Perfection
How to build experimentation programme momentum: raise test velocity, balance quick wins and big bets, celebrate losses, tell results well and restart a stall.
Hiring and Training an Experimentation Team: Roles, Skills and an Upskilling Plan
How to build an experimentation team: the seven roles, a skills matrix, team size by maturity, hire vs outsource, an interview exercise and a training plan.
Where to Start: Finding Champions, Securing a Sponsor and Setting the Rituals of an Experimentation Programme
How to start an experimentation programme: secure a sponsor, recruit champions, pick a first area, and copy ritual agendas, a charter and a 90-day plan.
How to Measure an Experimentation Culture: Programme Metrics, a Learning Library and a Maturity Self-Assessment
Measure your experimentation culture: programme health metrics, a learning library for test results and a 5-level experimentation maturity self-assessment.
How to Talk About Experimentation to Every Stakeholder: Executives, Analysts, Designers, Developers and More
Experimentation stakeholder communication: what to say, and avoid, with executives, finance, designers, developers and legal, plus answers to 8 objections.
How to Measure AI Search Visibility: Metrics, Tools and a Monthly Reporting Routine
How to measure AI search visibility: the AI visibility metrics that matter, prompt panels, GA4 AI referral tracking, tools and a monthly reporting routine.
Your First 90 Days in a New CRO Role: What to Audit, Who to Win Over and Which Tests to Run First
A practical CRO 90-day plan for new CRO and experimentation leads: what to audit, which stakeholders to win over, which tests to run first, what to report.
GA4 Audit Checklist for E-commerce: The Checks That Make Your Data Trustworthy
A GA4 audit checklist for e-commerce: settings, consent mode v2, e-commerce events, revenue reconciliation, BigQuery and tag QA, plus a scoring template.
Experimentation ROI: How to Build the Business Case for an A/B Testing Programme
How to calculate experimentation ROI: value sources, a programme model, winner's curse and holdouts, a worked example and how to present the case to a CFO.
How to Choose an A/B Testing Tool and the Rest of Your Optimisation Stack: A Vendor-Neutral Selection Scorecard
A/B testing tool selection guide: a vendor-neutral process, weighted scorecard, pricing models and 3-year TCO for analytics, testing, personalisation and VoC.
Guardrail Metrics in A/B Testing: How to Choose Them and When to Stop a Test
Guardrail metrics in A/B testing: how to pick 3–5 for e-commerce, set non-inferiority margins, and when to stop a test early for harm, not for a win.
10 A/B Testing Mistakes That Fake a Result (and How to Catch Them)
The 10 A/B testing mistakes that make a result look real when it isn't, from peeking and p-values to SRM and outliers, and how to catch each one in a report.
A/B Test Sample Size and Duration: How to Calculate Them and What to Do with Low Traffic
How to calculate A/B test sample size and how long to run an A/B test: the four inputs, a worked example, the lift your traffic can detect, low-traffic fixes.
How to Build an A/B Test with a Prompt: A Step-by-Step Walkthrough
Prompt-based experimentation, step by step: write the prompt, use an AI A/B test builder, review the generated code, iterate, QA and launch your test safely.
A/B Test QA Checklist: What to Check Before, During and After Launch
A practical A/B test QA checklist for marketers and developers: what to check before, at, during and after launch, from SRM and flicker to tracking and consent.
Mobile UX Audit for E-commerce: A Step-by-Step Method to Find What Costs You Sales
Run a mobile UX audit in two weeks: size the mobile conversion gap in GA4, review each journey stage, check speed, tap targets and forms, then prioritise fixes.
From Customer Insight to Test Backlog: Writing and Prioritizing A/B Test Hypotheses
Turn customer research into a strong A/B test hypothesis: triangulate evidence, compare test prioritization frameworks and run a CRO backlog that learns.
Analysing Surveys with LLMs: From Open-Ended Answers to Test Hypotheses
AI survey analysis done right: how LLMs code open-ended answers, where they fail, and an eight-step workflow that turns verbatims into A/B test hypotheses.
Product Page and Checkout Optimisation: A Playbook for E-commerce Teams
Checkout optimization and product page best practices backed by Baymard research: cart abandonment, guest checkout, form fields, payments, tests and EU rules.
E-commerce KPIs and Benchmarks: The Metrics That Matter and What Good Looks Like in 2026
Ecommerce KPIs explained: the 15 metrics that matter, formulas, GA4 names and sourced 2026 benchmarks for conversion rate, AOV, cart abandonment and CLV.
The Essential Guide to Generative Engine Optimization (GEO)
Generative engine optimization (GEO) explained: how AI answers cite sources, what the research shows, AI crawler setup, content, tools and e-commerce steps.
The Essential Guide to Conversion Rate Optimisation (CRO)
Conversion rate optimization (CRO) explained: how to calculate it, real benchmarks, the CRO process, where e-commerce sales are lost, ROI and AI.
Funnel and Cohort Analysis: How to Find Where Customers Drop Off and Whether They Come Back
Cohort analysis and funnel analysis, hands-on: GA4 funnel settings, a worked e-commerce funnel, confidence intervals, retention tables, BigQuery SQL and AI.
Segments, Bandits or A/B Tests? How to Personalise E-commerce with Evidence
Multi-armed bandit vs A/B testing for e-commerce personalization: segment with rules, RFM or AI, then prove it with holdouts, bandits and contextual bandits.
Measuring Personalisation ROI: Holdouts, Incrementality and Honest Attribution
How to measure personalization ROI: why attributed revenue overstates impact, how to size a holdout group, test incrementality and build a personalisation P&L.
Synthetic Users in Customer Research: What AI Personas Can and Cannot Replace
Synthetic users in customer research: what the evidence says on AI persona accuracy, where LLM respondents fail, how to validate them and when to use them.
The Essential Guide to Product Analytics
What product analytics is and how to use it: event data model, tracking plans, funnel and cohort analysis, retention, North Star metric, tools and AI in 2026.
The E-commerce Personalisation Playbook: 25 Use Cases by Journey Stage
25 ecommerce personalization use cases by journey stage, with the data each needs, effort, risk and how to test it, plus EU pricing and consent limits.
AI Agents in Experimentation: What They Do at Each Step, What Vendors Ship and Where Humans Stay in Charge
AI agents in experimentation, step by step: research, hypotheses, test builds, QA and analysis, what Optimizely, Kameleoon and VWO ship, MCP and the risks.
How to Find Personalisation Segments in GA4 (and Know Which Ones Are Worth It)
Find personalisation segments in GA4: explorations, audiences, predictive audience thresholds, BigQuery RFM, and a method to rank segments by real opportunity.
AI Search Optimisation for E-commerce Brands: How to Get Your Products Found and Recommended by AI Assistants
AI search optimization for e-commerce: how ChatGPT shopping, Google AI Mode and agentic checkout pick products, the feed checklist and how to track AI sales.
The AI Search Visibility Market, 2023–2026: GEO Tools, Funding, Deals and Where Value Goes Next
GEO tools and the AI search market, 2023–2026: AI visibility tool segments, verified funding rounds, Adobe–Semrush and other deals, pricing and what comes next.
Product Recommendations That Actually Add Revenue: Types, Placement and How to Measure Them
E-commerce product recommendations explained: types, algorithms, placement, merchandising rules and how to measure incremental revenue with a holdout test.
On-Site Survey Design: How to Build Website Surveys People Answer
On-site survey design that gets answers: triggers, question wording, length, sample size, NPS/CSAT/CES placement, mobile, GDPR and turning answers into tests.
The Essential Guide to E-commerce Acquisition and Retention Channels
Every e-commerce acquisition and retention channel explained: paid search, social, marketplaces, SEO, AI, email, SMS, loyalty, and how to measure them.
The Essential Guide to Web Analytics
Web analytics explained: how it works, the e-commerce metrics that matter, measurement plans, attribution, consent and data quality, tools and AI in 2026.
Beyond the Numbers: How GA4 Actually Works
How Google Analytics 4 really works: events, cookies and User-ID, sessions, consent mode, processing delays, HLL++ estimates, attribution and BigQuery.
Understanding the E-commerce Market Equation
The e-commerce equation explained: sessions × conversion × order value, the online share of retail, returns, costs and which lever moves profit most in 2026.
A/B Testing Statistics for Marketers: The Models, When to Use Each, and How AI Can Help
A/B testing statistics explained for marketers: significance, sample size, frequentist, sequential, Bayesian and bandit models, which tools use which, and AI.
The Essential Guide to Web Analytics for Product Owners
Web analytics for product owners: North Star and guardrail metrics, tracking plans, funnels, adoption and retention, opportunity sizing, experiments and AI.
DOM Manipulation for A/B Testing: The Marketer's Guide to Changing Web Pages Safely
How visual-editor A/B tests change web pages: the DOM, selectors, what to change yourself, flicker, speed, accessibility, QA and AI editors, in plain English.
Which Custom Dimensions to Collect in Your E-commerce Analytics
Which custom dimensions to collect in e-commerce analytics: GA4 limits, a shortlist of 16 dimensions, cardinality, naming, data layer and privacy rules.
How to Build a Culture of Experimentation
Why most test programmes stall and how to build an experimentation culture: leadership, safety, operating models, guardrails and a 90-day plan for any team.
Advanced DOM Manipulation for A/B Tests: A Developer's Guide to Robust, Fast and Safe Variations
Write robust A/B test variation code: selectors, MutationObserver, SPAs and React hydration, flicker, Core Web Vitals, XSS and CSP, tracking, QA and Playwright.
The Essential Guide to Web Analytics for Product Designers
Web analytics for product designers: HEART and SUS metrics, heatmaps and session replay, funnels and forms, Core Web Vitals, accessibility, A/B tests and AI.
JavaScript Injection vs Client-Side vs Server-Side A/B Testing: How to Choose
JavaScript injection, client-side SDK, server-side and edge A/B testing compared: flicker, page speed, SPAs, caching, Safari, SEO, vendors and how to choose.
The Essential Guide to Personalisation
What personalisation is and how to do it well: levels, data, methods, a 7-step process, measuring with holdouts, privacy and pricing rules, and common mistakes.
The Essential Guide to Web Personalisation
How to personalise your website: use cases, signals, rules vs bandits, testing with holdouts, flicker and page speed, SEO and accessibility, and a roadmap.
The Tag Management Market, 2007–2026: Free Containers, Server-Side Tagging, Consent and Where Value Goes Next
20 years of tag management: Google Tag Manager, Tealium, Adobe, Ensighten, Commanders Act, server-side hosts and consent. Market size, M&A, pricing, AI and PE plays.
Server-Side Google Tag Manager for E-commerce: What It Fixes, What It Costs
How server-side Google Tag Manager works, what it improves, what it does not fix, hosting costs, Google tag gateway, consent and an 8-step set-up for e-commerce.
The Essential Guide to Tag Management
How tag management works: tags, triggers, data layers, performance, data loss, server-side tagging, Consent Mode v2, PCI DSS script rules and choosing a tool.
The Digital Analytics Market, 1995–2026: Web, Product and Experience Analytics, and Where Value Goes Next
30 years of analytics tools, from Google Analytics and Adobe to Amplitude and Contentsquare: market size, M&A, private equity and where value goes next.
The Essential Guide to Voice of Customer (VoC)
What Voice of Customer is and how to run it: methods, NPS vs CSAT vs CES, 8 steps, survey design, sample sizes, AI analysis and linking VoC to A/B tests.
User Consent in E-commerce: Everything to Know Before 2027
Cookie consent rules in the EU, UK and US, fines, banner design, consent rates, Consent Mode, A/B testing and what changes in 2027 for e-commerce teams.
The Personalisation Market, 2000–2026: Platforms, Deals, AI and How E-commerce Teams Should Choose
Personalisation market map 2026: eight segments, the deals from Omniture to OpenAI–Statsig, AI decisioning, the evidence, and how e-commerce teams should choose.
The Voice of Customer Market, 2000–2026: Platforms, Deals, AI and How E-commerce Teams Should Choose
VoC market map 2026: seven segments, Qualtrics–Press Ganey, Medallia's reset, AI feedback analytics, and how e-commerce directors should pick a tool.
Session Replay in 2026: Why You Need It, How to Choose a Tool, and What Changes with AI
What session replay is, why you need it, how to compare Clarity, Contentsquare, FullStory, PostHog and others on free plans, and how to choose in the AI era.
The A/B Testing Tool Market, 2006–2026: Size, Funding, M&A and What Comes Next
20 years of the A/B testing software market: market size, $4B+ of deals, investors, Optimizely, VWO, AB Tasty, Statsig, Google Optimize, and what comes next.
The Essential Guide to A/B Testing
What A/B testing is and how to run tests you can trust: the 8-step process, sample size, statistical significance, 10 common mistakes, tools and examples.
Why Prompt-Based Experimentation Belongs on the C-Level Agenda
AI now builds A/B test variants from a prompt. Our 19-test study, the 2026 vendor update and a clear ROI scenario show why test velocity is a board issue.
How AI Is Reshaping A/B Testing: What 19 Prompt-Built Tests Tell Us About Speed, Quality and Limits
We rebuilt 19 real A/B tests with AI prompts: 89% less build time, 11 of 19 at 90%+ fidelity. Where prompt-built tests fail, and how to QA them in 2026.
Voice of Customer: The Missing Layer in Every Optimization Strategy
Why CRO teams measure behaviour but miss the why: Voice of Customer methods, Baymard abandonment data, A/B test win rates, AI analysis and a 30-day plan.
The Experimentation Manifesto: Three Values and 16 Principles for a Test-and-Learn Culture
The Experimentation Manifesto: 3 values and 16 principles to build an experimentation culture and CRO program, with win-rate evidence, a maturity model and AI.

Ideas, conversations and signals.

Research & guides

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