Experiment-led growth has been quickly absorbed into the SaaS vernacular. The approach complements product-led growth and puts systematic experimentation at the core of decision-making and growth initiatives.<\/p>\n\n\n\n
Product leaders have seen firsthand how testing changes with real users before full implementation can minimize risk and maximize ROI. Booking.com, Netflix, and Amazon have made experiment-led growth central to their success by running thousands of experiments annually to optimize UX.<\/p>\n\n\n\n
But, teams that don\u2019t have the time, resources, or traffic of the industry leaders might find it difficult to take on the practice effectively.<\/p>\n\n\n\n
In this article, we\u2019re sharing how SaaS companies between product-market fit and scale can cut down on test cycle time to make adoption of experiment-led growth practices more accessible.<\/p>\n\n\n\n
In optimization, test cycle time is the full length of time taken to complete an experiment. It includes all phases, from ideation to planning, through execution, and analysis. It\u2019s an important metric for measuring the efficiency of testing programs and identifying bottlenecks in the experimentation workflow.<\/p>\n\n\n\n
Slow testing cycles aren\u2019t just annoying, they can create real problems for your business and, as we mentioned, hold you back from the benefits of experiment-led growth.<\/p>\n\n\n\n
We\u2019ve seen firsthand with clients how test cycle delays can mean months between identifying an issue and implementing a solution. That’s simply too long in today’s market.<\/p>\n\n\n\n
Here are a few of the high costs you might be paying for a slow test cycle:<\/p>\n\n\n\n
So, what should you do about it? We reached into our tool chest and pulled together the strategies that have worked for our clients and trusted partners to reduce test cycle time.<\/p>\n\n\n\n
A\/B testing has its place in product optimization, but there are plenty of ways it fails.<\/p>\n\n\n\n
Regulatory challenges, low traffic, time constraints, and other issues make A\/B testing an at times untenable solution for validating changes to their website or app.<\/p>\n\n\n\n
In some companies, by the time a test idea passes through all the bureaucratic loopholes and oversight at an organization, it\u2019s no longer lean enough to justify testing. Without an alternative testing method, teams are left without any data at all. In these instances, A\/B testing is just too clunky to make sense.<\/p>\n\n\n\n
But, there is a great alternative solution that can provide insights when A\/B testing isn\u2019t an option. Using targeted qualitative methods like rapid testing helps overcome the challenges mentioned and builds confidence in changes within days instead of weeks.<\/p>\n\n\n\n
Software Director of Product Marketing Gabrielle Nouhra, who leverages The Good for research and experimentation support, says this about rapid testing:<\/p>\n\n\n\n
\n\u201cThe speed at which we obtain actionable findings has been impressive. We are receiving rapid results within weeks and taking immediate action based on the findings.\u201d<\/em><\/p>\n<\/blockquote>\n\n\n\n
How it works:<\/p>\n\n\n\n
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- Recruit users from your target segment<\/li>\n\n\n\n
- Choose the right rapid testing method<\/a> and conduct tests on specific features or flows<\/li>\n\n\n\n
- Analyze patterns immediately rather than waiting for statistical significance<\/li>\n\n\n\n
- Implement clear findings quickly while planning more extensive testing only where truly needed<\/li>\n<\/ul>\n\n\n\n
In addition to the efficiency of rapid testing and its ability to overcome regulatory challenges, it also has the cool added benefits of adding some qualitative feedback and the voice of the consumer to your work.<\/p>\n\n\n\n
For more on rapid testing and how it differs from A\/B testing, check out this deep dive<\/a>.<\/p>\n\n\n\n