Conversion Rate Optimization (CRO) FAQs
Why is Conversion Rate Optimization (CRO) Essential?
CRO plays a vital role for several reasons:
- It’s a scientific, data-driven process for boosting revenue.
- It prevents actions that could negatively impact conversions or waste resources.
- It allows for a deeper understanding of your customers’ behavior and preferences.
- CRO fosters informed, data-backed decisions, reducing the reliance on instinct alone.
This systematic approach ensures more predictable, sustainable business growth.
What is an Achievable Conversion Rate?
A realistic conversion rate depends on factors such as your industry, product or service type, pricing, brand recognition, traffic sources, and user experience. There isn’t a universal benchmark, as it varies widely. The key is to focus on continuous improvement.
It’s also important to recognize that conversion rate is just one metric—higher conversions don’t always translate into more revenue. That’s why it’s essential to also track metrics like average order value (AOV), profit, and total revenue for a fuller picture of success.
How long should an A/B test run?
Typically, A/B tests last for one to two business cycles, often 7, 14, or 21 days, depending on the specific test and client needs. The duration is customized based on factors like traffic and business context.
Before launching, we calculate the Minimum Detectable Effect (MDE), which determines the smallest measurable change with statistical significance—usually at a 95% confidence level. This ensures we have enough traffic and conversions for each variation to produce accurate, reliable results.
What kind of ROI can you expect?
At 9 Catalyst, our goal is to ensure your customers are satisfied and deliver the highest possible return on your investment. We typically aim to generate 2-5 times the ROI from your investment in our services. Our track record speaks for itself, with clients seeing long-term ROI, even after working with us for over six years.
What areas can you experiment on?
Nearly everything! We specialize in running experiments across various touchpoints, collaborating with your marketing and product teams. From testing web pages, landing pages, onboarding flows, and in-app experiences, we focus on key revenue metrics like customer acquisition, onboarding, engagement, retention, and monetization. These experiments are designed to drive exponential revenue growth. While the tools and metrics may vary across different areas, our approach to testing, learning, and optimizing remains consistent and results-driven.
What metrics should be tracked during conversion rate optimization?
At 9 Catalyst, conversion rate optimization isn’t just about conversions alone. Focusing only on conversions could inadvertently reduce average order value (AOV) or increase returns, impacting overall revenue and profit.
To ensure a holistic approach, we track multiple metrics alongside conversion rates, including AOV, customer lifetime value (CLTV), revenue per visitor, trial to paid ratio, average time spent and many more customised metrics based on your business model. This comprehensive tracking ensures that all aspects of performance are optimized for sustainable growth.
Should CRO be a one-time or ongoing effort?
Conversion rate optimization (CRO) should always be an ongoing process, not a one-time effort. Continuous CRO ensures that your business keeps evolving, unlocking exponential revenue growth by consistently improving user experience and conversion metrics.
As markets and customer behaviors change, ongoing CRO helps you stay ahead of the competition and overcome any plateaus in growth. By pushing past your local maximum, you can continue to scale and achieve long-term success.
What is a test hypothesis or experimentation ?
A hypothesis or an experiment is an testable assumption.
It typically follows a structure like: If we do [X], then we expect [this result] because [rationale based on research or data].
This format allows for measurable outcomes, ensuring that the hypothesis can be validated or refuted based on the experiment’s results.