In the world of data and analytics, anecdotal evidence is often (and correctly) demonized. Why? People in general and marketers in specific mistake anecdotal evidence for quantitative proof, for statistically representative, reliable, and repeatable evidence.
Anecdotal evidence is none of those things. It’s one person’s experience, so it’s not representative. Depending on that individual’s perspective and biases, it may not be reliable. Its very nature as an anecdote means that collecting similar information under similar circumstances is not repeatable.
Even anecdotal evidence in aggregate is still not reliable. In aggregate, anecdotes do not necessarily have the statistical rigor to be proof of anything, especially if there was any kind of bias in the collection of the anecdotes.
So, should we just toss away all our anecdotal evidence? Of course not.
The Value of Anecdotal Evidence
Let’s be clear what anecdotal evidence is. It’s a story, literally meaning “something unpublished” from ancient Greek. Anecdotal evidence is qualitative data. It doesn’t measure anything, but it does describe one person’s experience with something, their story.
And in every story lies the potential for rich data to investigate, for questions to ask.
For example, let’s say we’re working on market research for the next great cup of coffee at our coffee shop. While sitting in the shop with a cup of coffee, the guy next to us makes an offhand remark about how he’ll never drink kopi luwak even though it’s one of those trendy coffee things. If we’d never heard of kopi luwak, this anecdote, this piece of qualitative data, is a new starting point for us to investigate. Perhaps our coffee shop companion might never drink kopi luwak, but that doesn’t mean our other customers wouldn’t.
Every time we commission some interviews, some focus groups, read our customer service inboxes, or listen and watch our customers as they go about their lives, we’re collecting qualitative data. We’re collecting stories, anecdotes – and inside those stories may be critical details we won’t and can’t collect from quantitative data.
Imagine for a moment how much data you’d need to collect and process to see how a million customers use your products. You could not reasonably and rationally collect that much information, have a million employees shadow customers throughout their days. Could you reasonably do that with ten customers? Yes – and those observations could be very valuable.
Suppose you make an LED desk lamp. What assumptions would you have made in its design? You would have assumed people kept it on their desks and used it to light the desk and read with. Now suppose you visited my house and you saw this:
I’m using these desk lamps, inverted, as indirect light for an entire room. This is a harmless but unintended use of these lamps – it’s an observation, an anecdote. Now suppose you went to 10 customers’ homes and in 4 of them, you saw similar uses. Would this change how you think of your product? It should. It should make you ask, just how many of our customers use our product in a manner different than we designed it for? If enough did, you could offer different models and variations of the product that would fulfill these new, unintended uses even better, increasing the sales of the product.
Without these anecdotes, without this qualitative information, you would not have known this. You would not have thought to ask this, but with just a handful of customer stories, you have a starting point to ask better questions and collect more statistically relevant data.
The value of anecdotal evidence is to help us ask better questions. Don’t misuse it or mistake it to be quantitative data, but don’t throw it away, either. Use it to explore, to widen your perspectives, and ask better questions to earn better answers.
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