Find the leak first
CRO starts with diagnosis, not button colours. Ash et al. (2012) advise fixing the biggest drop-off in the marketing funnel first. Under Fogg's (2009) model behaviour needs motivation, ability and a prompt together; on mobile, ability barriers such as tedious input, slow loading and small buttons dominate. With impressions formed in 50 ms (Lindgaard et al., 2006), first-screen speed and message matter most.
Hypotheses and experiments
Kohavi et al. (2009) present online controlled experiments, A/B tests, as the most reliable way to establish causation. Good hypotheses state evidence and prediction. Kohavi, Tang and Xu (2020) warn about sample ratio mismatch and recommend guardrail metrics such as refunds. Reducing options, as in Iyengar and Lepper's (2000) jam study, is a frequent hypothesis.
Mobile checkout friction and dark patterns
Guest checkout, wallets, address autocomplete and numeric keypads sharply cut friction. Fake timers and sneak-into-basket dark patterns, found by Mathur et al. (2019) across 11,000 shops, may lift short-term conversion but damage trust, repeat purchase and legal safety. Sustainable CRO helps users finish what they came to do.
FAQ
- Where does CRO start?
- Find the biggest drop-off with funnel data and research, then hypothesise about it.
- Should small sites run A/B tests?
- With low traffic, rely mainly on usability testing and qualitative research.
Sources reviewed: 2026-10-27
References
- Kohavi, R., Longbotham, R., Sommerfield, D., & Henne, R. M. (2009). Controlled experiments on the web: Survey and practical guide. Data Mining and Knowledge Discovery, 18(1), 140–181. Survey of web experiment design and common pitfalls.
- Kohavi, R., Tang, D., & Xu, Y. (2020). Trustworthy online controlled experiments: A practical guide to A/B testing. Cambridge University Press. Covers trustworthy experimentation such as sample ratio mismatch and guardrails.
- Ash, T., Ginty, M., & Page, R. (2012). Landing page optimization: The definitive guide to testing and tuning for conversions (2nd ed.). Wiley. Practical guide to diagnosing and prioritising landing page tests.
- Fogg, B. J. (2009). A behavior model for persuasive design. In Proceedings of the 4th International Conference on Persuasive Technology (Article 40, pp. 1–7). ACM. Behaviour occurs when motivation, ability and a prompt converge.
- Mathur, A., Acar, G., Friedman, M. J., Lucherini, E., Mayer, J., Chetty, M., & Narayanan, A. (2019). Dark patterns at scale: Findings from a crawl of 11K shopping websites. Proceedings of the ACM on Human-Computer Interaction, 3(CSCW), 1–32. Crawl of 11,000 shopping sites documenting dark patterns.
- Iyengar, S. S., & Lepper, M. R. (2000). When choice is demotivating: Can one desire too much of a good thing? Journal of Personality and Social Psychology, 79(6), 995–1006. The jam study: fewer options led to more purchases.
- Lindgaard, G., Fernandes, G., Dudek, C., & Brown, J. (2006). Attention web designers: You have 50 milliseconds to make a good first impression! Behaviour & Information Technology, 25(2), 115–126. First impressions form in 50 ms.