You know the saying “correlation does not equal causation”? Marketers are infamous for equating correlation and causation.
We’ll see an improvement in a marketing campaign and work backwards to find the correlation, then assign causation to the result. We used one designer during the first campaign and it bombed. We brought on a new designer for the next campaign and voila! The campaign exceeded expectations.
It’s easy to say:
“The second campaign’s design was better optimized to attract the click and once we got users to our landing page, the related visuals were better at converting them to leads.”
To which I’d say:
“That’s nice, can you show me the data?”
If the campaign involved the exact same content, promotional copy and audience targeting — and the only difference was the design, then maybe you can start to build an argument about the design.
Acknowledging the Role of Serendipity in Marketing
But even so, you ran the campaigns one after the other, so what about time-of-month or time-of-year variations? This is why an A/B test requires you to change a single variable (e.g., your button label). When everything else is identical and one button label outperforms another, you can make a good case for causation (i.e., it was the button label!)
I believe there’s a certain wildcard factor that’s responsible for some marketing results: serendipity.
Merriam-Webster defines serendipity as “the faculty or phenomenon of finding valuable or agreeable things not sought for.” A related word I’d use here is “randomness.” In other words, some marketing campaigns perform “just because.” Or, they perform based on factors that are unexpected and out of your control.
Here are two examples.
Social Media Marketing
I believe that what makes a tweet go viral is serendipity. A user with 200 followers tweets. An influencer with 250,000 followers happens to see it and retweets it. Now, many others see it and start commenting on it. If the Twitter algorithm could speak, it would say, “Hmm, this burst of activity is interesting. I need to bump this higher in people’s feeds.”
In less than 12 hours, the tweet has 7,500 retweets, 10,200 likes and 1,275 comments. That first retweet set some snow down a hill. The snowball got bigger and bigger as it rolled down. But what if that influencer wasn’t around to retweet to her 250,000 followers? It’s possible no one would have seen it.
I saw something similar happen to me. I tweeted a pun about retargeting. My tweet got virtually no engagement. I decided to take the same tweet and schedule it in a social publishing tool for 2am PT the next day. I was asleep when it auto-tweeted and when I woke up, I saw that it had generated a good amount of likes and retweets.
(Side note: Twitter once allowed you to tweet the exact same thing. It doesn’t allow this anymore.)
Others were awake, saw the tweet and engaged with it. By the end of that day, it had become one of my most-engaged tweets of all time. See the serendipity here? Two identical tweets, one done during normal working hours, the next done in the middle of the night.
Why did the latter do so well?
Related Article: How to Navigate Blind Spots in Marketing Campaigns
Every other Friday, I send out an email newsletter called “Content Corner.” Here are the email open rates for the past several issues: 30.7%, 36.8%, 33.2%, 31.5%, 34.4%, 52.0%, 33.2%, 32.4%, 38.9%.
One number sticks out from the pack: the 52.0% open rate.
Yay! More than half of my list opened the email. Of course, I had to figure out what caused this — you know, find some causation and the correlation to go along with it. I didn’t come up with much. The approach I took with the newsletter didn’t change at all across this sample set.
My “From” line and preview text remained the same. Looking at the Subject lines (i.e., an important factor) didn’t turn up anything meaningful. I used a Subject of “A business idea.” for the email that got a 52.0% open rate. Maybe that piqued the curiosity of some subscribers, but I’m not sure.
I tend to have a core group of “regulars” who read my newsletter and looking at the email with the 52.0% open rate, I did notice subscribers who don’t often open the emails. I chalk it up to serendipity: just like the influencer who happened upon a tweet and retweeted, a bunch of people happened to be in their inbox when my newsletter arrived. They opened that one, but didn’t open subsequent newsletters.
Related Article: 7 Factors That Determine Email Deliverability
The Serendipity in the Room
Chalking things up to serendipity might make marketers nervous. It’s like a boss saying, “Hey, good job on that campaign! How did you do it?” and responding by shrugging your shoulders and saying “Dunno.” But just as it’s important to call out the elephant in the room, I urge marketers to call out the serendipity in the room.
Acknowledging serendipity is better than reverse engineering causation. For example, I could have decided that 2am PT is the best time to tweet and that mysterious three-word subject lines work best. But that might be misguided.
Finally, once you acknowledge serendipity, return to results where the data is more clear, like in an A/B test. When you sleep comfortably that your causation is air-tight, double down on your bets and the world is your oyster the next morning.