This month’s Harvard Business Review features an interesting article on the value of conducting business experiments (A Step-by-Step Guide to Smart Business Experiments). It’s a topic that hits close to home for research and analytics firms like us. Be it experimentation or analytics, the objectives are the same — “to gather accurate data, analyze it for insights, and use those insights to make better decisions.”
That’s a decent mission statement for market research.
Analytics is a wonderful tool when you have access to a lot of data, the resources to organize and analyze it, and the skill to communicate and exploit the results. It’s a highly technical discipline that can yield useful results. But, in our experience, comparatively few small to mid-sized companies can pull that off consistently.
Experimentation is an excellent alternative to analytics. Rather than focusing on the past by analyzing historical data, the experiments happen in real time, with real customers and often with immediate feedback. At the end, as with analytics, you will have data instead of intuition to guide your decision making.
Experimental designs can be quite basic. All that you need are test and control groups, plus a way to measure all the results. Then, it’s a matter of doing one thing with the test group, another thing (or nothing) with the control group, and comparing the results. Retailers, advertising agencies, and direct marketers have relied on experiments for decades, using them to set prices, optimize product mixes, test copy, and to determine size and type of offers.
Whether you rely on experiments, analytics, or both to feed your decision making process, you’re ahead of those who don’t.