Conversion Rate Optimisation
YOUR ADS AREN'T THE PROBLEM. YOUR FUNNEL MIGHT BE.
How we approach Conversion Rate Optimisation
Before buying more traffic, make the traffic you have convert. We map the funnel step by step, find the biggest drop, watch real sessions, and run structured tests on offers, page structure and forms. Fixing one leak is often cheaper than doubling ad spend, in any market.
The problem
Traffic grows, conversions do not. Decisions are made on opinion, and 'tests' end before anything is learned.
What we do
- Analytics review to find where people leave
- Hypotheses ranked by impact and effort
- UX friction review on key pages and forms
- Experiments where traffic allows; structured iterations where it does not
- Clear measurement plans before any change
- Honest reporting: no significance claimed without the data
Our process
Discover → Diagnose → Strategize → Build → Launch → Optimize. Every step has an approval and a measure, so you always know what is being done, why, and how it will be judged. See the Growth System.
What we track
- Step-by-step funnel conversion
- Form abandonment points
- Revenue or leads per visitor
- Experiment learning log
Channels / platforms
Website · Landing pages · Checkout · Lead forms
Deliverables
- Funnel diagnosis
- Hypothesis backlog
- Experiment plans
- Learning reports
CRO (Conversion Rate Optimisation), explained simply
CRO is improving your site/page so more of the visitors you already have take action.
Example: Moving reviews next to the form, cutting fields from 7 to 3 and adding WhatsApp can lift enquiries without spending more on ads.
Diagnose with data (analytics, heatmaps, recordings, customer questions), then test changes one at a time.
- Framework: clarity → relevance → trust → friction → urgency/incentive.
- Prioritise by impact × confidence × ease (ICE).
- Low traffic? Use qualitative research (5 customer interviews, session recordings) instead of A/B tests.
Common mistake: Redesigning everything at once on opinion, or 'testing' with too little traffic to know anything.
Experimentation, explained simply
An experiment is a structured test: one change, one metric, a decision rule, so you learn instead of guessing.
Example: Hypothesis: showing prices on the landing page will raise qualified enquiries. Change: add 'starting from ₹X'. Metric: qualified enquiry rate. Duration: 2–4 weeks. Decision: keep if qualified rate rises without lead volume collapsing.
Write the decision rule before the test so results can't be cherry-picked.
- Prioritise with ICE (impact, confidence, ease).
- Low traffic? Test bigger changes and use qualitative signals.
Common mistake: Changing three things at once or stopping when the first day looks good.
Who it is for
Sites with meaningful traffic and unclear results.
Expected business outcomes
Fewer leaks, better decisions, and a record of what you learned. Outcomes are not guaranteed and depend on your offer, market, budget and execution.
Where we work
FODO is remote-first and headquartered in New Delhi, India. We work with brands in India and around the world, the UK, US, UAE and the Gulf, Europe, Australia and beyond. Work runs on video calls, WhatsApp, email and shared dashboards, so your location never limits the service.
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Related services
Landing Pages · Analytics & Measurement · Web Design · Paid Advertising