CONVERSION ENGINEERING
CRO — Conversion Rate Optimization
Research-driven hypotheses, Bayesian + sequential A/B testing and segment-level analysis for measurable conversion lift; test discipline, not guesswork.
CRO is not a design change; it is a decision system where hypotheses are validated through test discipline.
Most teams burn through CRO with random variants like 'button color' or 'icon swap'. Winning teams start with customer research, frame every test around a problem, pre-calculate sample size with power analysis, and analyze the winner segment by segment before shipping it permanently into the product. Roibase's CRO operation is built on six principles, and each one is measured individually on your end-of-month scorecard.
METHODOLOGY
RESEARCH → HYPOTHESIZE → DESIGN → TEST → ANALYZE → SHIP
Not guesses but hypotheses; not hypotheses but business impact. A six-layer workflow secures every test decision inside a statistical + business-metric frame.
RESEARCH
Data + user research
A 'pain map' is built from GA4 funnel, heatmap, session replay, 6-10 customer interviews, on-site survey and NPS verbatim analysis.
HYPOTHESIZE
Hypothesis canvas + ICE scoring
Every hypothesis on a single page: problem, target audience, expected behavior change, lift, sample size, success metric, risk scenario.
DESIGN
Wireframe + high-fidelity + copy
Variant design is derived from research; copy clarifies the hypothesis promise, design system tokens are preserved.
TEST
Deploy + QA + traffic allocation
Deploy with VWO / Optimizely / GrowthBook; flicker check, analytics validation, cross-device QA, traffic split audit.
ANALYZE
Bayesian + segment deep-dive
Probability to beat baseline, expected loss, segment-level effect size; separate action plans for winners, losers and inconclusive tests.
SHIP
Productize + codify the learning
The winning variant is committed to the design system, added to regression tests; learnings enter the learning database and feed the next sprint.
— COMPARISON
Where we differ: classic approach vs. Roibase test discipline
The gap between teams that treat CRO as a design exercise and teams that run it as a test discipline shows up directly on the average CR curve within a year.
| Dimension | In-house trial & error | Classic design agency | Roibase test discipline |
|---|---|---|---|
| Test framework | Frequentist, checked every week | None or gut-feel | Sequential + Bayesian, peeking safe |
| Hypothesis quality | Button color, icon change | Design opinion | Problem-focused, derived from customer research |
| Power & sample calc | Mostly missing | Not applied | Mandatory and documented before every test |
| Segment analysis | Average-focused | None | Device x audience x source on every test |
| Research ops | Ad-hoc, one interview every 6 months | Limited to UX discovery | 6-10 interviews + continuous surveys per month |
| Win productization | Winner is forgotten | Kept only in the design doc | Design system + regression test mandatory |
| Learning culture | Results get lost | Limited to case studies | Learning database — 80+ learnings in 12 months |
| Reporting | One-off test report | Quarterly review | Weekly dashboard + monthly executive summary |
PROOF
Outcomes, measured
12-month portfolio of winning tests (weighted average).
Every test runs with a minimum of 85% statistical power.
Annualized incremental revenue / test investment.
Industry average is 14-20%; Roibase runs 2x above that.
Prioritized, scored ideas in the backlog pool.
Days until the first test deploy (kick-off included).
WHAT WE DO
Engagement scope
Every offering is an outcome-based work package. Roibase blends strategy and execution inside a single team — no hand-offs.
Sequential + Bayesian testing
A Bayesian framework that enables early decisions without the peeking problem; faster decisions and sample-efficient test infrastructure instead of classic frequentist methods.
Funnel + heatmap + replay triangulation
GA4 / PostHog funnel + Hotjar / Clarity heatmap + session replay — three data sources tied to a single hypothesis; we see the 'what' and the 'why' together.
Research-first backlog
6-10 user interviews, surveys and on-site polls per month; every test is born from the answer to 'why are they leaving?' — no random variants.
ICE x PIE backlog scoring
With Impact, Confidence and Ease scores, 4-8 high-quality tests are filtered monthly from 50+ hypotheses; prioritization by score, not by opinion.
Segment-level winner analysis
Device x audience x source x new vs. returning breakdown; a winner that is '+4% on average' can actually be +22% on mobile new.
Win productization
The winning variant is committed to the design system, added to Storybook, and wired into regression tests; no 'test's done, we forgot about it'.
Personalization & segment targeting
Ship a winning test to the segment where it performs best, not to every user; the logic of running 3-5 parallel experiences on the same page.
Mobile-first experimentation
If 65-80% of traffic comes from mobile, test infrastructure and hypotheses are built for mobile first — viewport-based variant flow.
Server-side + edge testing
Flicker-free, SEO-safe server-side test infrastructure (Edge Functions / Cloudflare Workers / custom); no client-side flicker on critical flows.
Learning database
Every test (winner + loser + inconclusive) is documented; after 12 months, an institutional memory of 80+ learnings.
— OUTCOMES
The measurable business value of CRO
Conversion optimization is not 'making the site prettier'; it is incremental revenue on the P&L, faster decision cycles and institutional learning.
Measured growth, not guesses
Every change is statistically validated; +18% average CR lift shows up on the P&L as revenue growth.
Data-informed decisions
Data instead of HiPPO (highest paid person's opinion); debates reference hypotheses and results tables.
Segment-level gains
Behind 'average 4%' there can be a 22% gain on mobile new users; 2-3x impact in the personalization-served segment.
Fast iteration
6-8 tests per month, results in 2 weeks; decision cycle is 6x faster than classic quarterly reviews.
Institutional learning
Winners + losers + inconclusive tests all live in the learning database; 80+ learnings / institutional memory in 12 months.
Stack-ready infrastructure
VWO / Optimizely / GrowthBook / Statsig — whichever fits; hybrid server-side + client-side, flicker-free.
DELIVERABLES
Monthly + quarterly outputs
Concrete, shipped outputs handed to your team every month. Each one feeds the hypothesis for the next test.
Funnel audit report
Step-by-step drop-off map, quick-win opportunities and annualized revenue loss estimate.
Qualitative research insight file
Transcripts, thematic coding, prioritization and quote-based pain map from 6-10 customer interviews per month.
Hypothesis backlog + ICE scores
A living list of 50+ hypotheses; Impact, Confidence, Ease scores and quarterly prioritization.
Quarterly test roadmap
Test plan for the next 12 weeks; capacity, dependencies and expected business impact clarified.
Hypothesis canvas (per test)
Problem, target audience, expected lift, sample size calc, success metric — one-page standard.
Variant design + copy + QA
Design package from wireframe to deploy; design system tokens and cross-device QA checklist included.
Weekly test status dashboard
Live dashboard of probability-to-beat, expected loss and segment trends for in-flight tests.
Monthly executive summary
Winners / losers / inconclusive tests, revenue impact estimate and next-month action list.
Segment deep-dive report
Device x audience x source x new vs. returning breakdown; personalization candidates flagged.
Win productization brief
Design system commit plan for the winning variant, Storybook entry and regression test framework.
Learning database
Winners + losers + inconclusive — every test captured as institutional memory; feeds the next hypotheses.
Tool stack configuration
VWO / Optimizely / GrowthBook / Statsig setup, integration and governance documentation.
— SCOPE
What's in, what's out?
The boundaries of the CRO subscription are clear. Seeing scope upfront removes false expectations, scope creep and 'what are we actually doing?' questions.
What this service covers
- 6-8 live A/B tests per month, in a Sequential + Bayesian framework
- 6-10 customer interviews + transcripts + thematic coding per month
- 50+ hypothesis backlog with monthly ICE score updates
- Hypothesis canvas + wireframe + QA checklist per test
- Segment-level analysis + personalization recommendation document
- VWO / Optimizely / GrowthBook / Statsig setup and management
- GA4 + PostHog + Hotjar / Clarity integration and validation
- Win productization: design system commit + Storybook entry
- Learning database — all winner / loser / inconclusive records
- Weekly status dashboard + monthly executive summary
- Quarterly strategy review and 12-week roadmap update
- Research ops infrastructure: on-site survey, interview recruiting, repo
Out of scope (optional add-ons)
- Full-funnel redesign / site rebuild
- Brand identity and visual identity work
- Custom backend development (API, database schema)
- Deep ERP / CRM integrations
- Paid media campaign management (PPC is a separate service)
- Content / SEO production (SEO is a separate service)
- Native mobile app CRO (separate scope)
- A separate regression QA test team — we handle hypothesis QA
HOW WE WORK
Process: a CRO operation from Week 1 research to Month 5+ iteration
Week 1 — Discovery + funnel audit
GA4 audit, funnel analysis, heatmap setup, session replay analysis; top-level pain points and quick-win opportunities.
Week 2 — Research ops
6-10 customer interviews, on-site survey deploy, NPS verbatim sweep; a problem map in the user's own words.
Week 3 — Hypothesis backlog + prioritization
50+ hypotheses, ICE scores, quarterly roadmap; hypothesis canvases for the first 4 tests approved.
Week 4 — First test deploy
Tooling fully set up, QA + flicker check + analytics validation complete, traffic flowing.
Weeks 5-8 — Test cycle 1 (4 tests)
Two-week average test duration; 2-3 parallel tests, segment-level analysis, actionable result reports.
Month 3 — Segment deep-dive + personalization
We convert winning tests into segment-based personalization; mobile, new visitor and high-intent experiences diverge.
Month 4 — Win productization + design system
Winning variants are committed to the design system and added to Storybook; the regression test suite expands.
Month 5+ — Iteration + learning
Weekly dashboard + monthly executive review; the learning database sources the next quarter's roadmap.
— TOOL STACK
Testing, analytics, qualitative and reporting
Every team's stack is different; one-size-fits-all doesn't work. Picking the right tool across four layers is the prerequisite for testing the right hypothesis fast.
TEST & PERSONALIZATION
ANALYTICS & DATA
QUALITATIVE & RESEARCH
REPORTING & WORKFLOW
QUESTIONS
Frequently asked
— GLOSSARY
CRO terminology
Your team's shared language. When the same term means the same thing, debates move closer to hypotheses and away from opinions.
- Conversion Rate (CR)
- The share of users who complete a defined goal; calculated with formulas like transactions / sessions or signups / visits.
- A/B Test
- An experiment that randomly splits traffic between control (A) and variant (B) for a statistical comparison.
- MVT (Multivariate Test)
- An experiment that tests combinations of multiple elements simultaneously; requires high traffic.
- Sequential Testing
- A testing framework where results can be monitored continuously and early stopping is statistically safe.
- Bayesian Testing
- A testing approach that makes decisions over probability distributions; produces intuitive outputs like 'probability the variant wins'.
- Statistical Power
- The probability that an A/B test detects an effect (lift) that actually exists. Standard target is 80% power; smaller effects need either a larger sample size or a redefined minimum detectable effect (MDE). A pre-test power calculation is non-negotiable for sound experiment design.
- Sample Size
- The minimum number of users required per variant for an A/B test to reach a statistically reliable conclusion. Computed from power, alpha (usually 0.05), baseline conversion and MDE; an undersized sample inflates both false-positive and false-negative risk.
- Funnel
- The sequential representation of the steps a user takes toward a goal; each step is measured by its drop-off rate.
- Heatmap
- A tool that visualises the intensity of user interactions on a page (clicks, scrolls, hovers, attention) with a colour palette. Generated by Hotjar, Microsoft Clarity, Mouseflow and similar; in CRO it sources hypotheses, never on its own a decision — must be validated with an A/B test.
- Session Replay
- A tool that anonymously records a user's site session (mouse movement, clicks, scroll, form input) and lets you replay it like a video. Hotjar, FullStory and Microsoft Clarity lead the space; PII masking and consent are critical concerns — invaluable for CRO debugging.
- ICE / PIE Scoring
- A hypothesis prioritization framework using Impact-Confidence-Ease or Potential-Importance-Ease criteria.
- Feature Flag
- A mechanism that allows a feature to be turned on/off without code changes; the backbone of testing and continuous delivery infrastructure.
- Multi-armed Bandit
- An adaptive testing approach that dynamically shifts traffic to the winning variant during the experiment, instead of a classical A/B split. Minimises total regret; ideal for design/recommendation/banner tests with quick wins, less so for precise effect measurement.
- SRM (Sample Ratio Mismatch)
- A meaningful drift between the actual traffic split (e.g. 49.2/50.8) and the expected 50/50 in an A/B test — usually a sign of a technical bug. If a chi-square test gives p<0.001, the results are unreliable; root causes include bots, redirect loss and cookie leakage.
— QUICK DIAGNOSTIC
Is a CRO program right for me?
An interactive guide that reveals the right program tier in four questions. Yes / no answers give you a result in 30 seconds.
01 / 04
Do you have more than 30,000 monthly unique users?
GA4 → Reports → Acquisition → User acquisition panel, last 28 days.
— LET'S BEGIN
Let's uncover the hidden conversion potential on your site.
A free 48-hour funnel audit: on GA4 + heatmap + session replay data, we map the top 3 leak points, estimated annual revenue loss and a first-quarter hypothesis backlog draft.