Part 2: Learning from Success, Learning from Failure
This is a 3-part series. Click here to read part 1.
In my last post, I described how brands are racing to stay relevant, and how TrenDemon recognized their pain point and set out to try to solve it.
Maybe now you’d expect to see some example of some big brand’s huge content marketing success story and how we used them as a benchmark to define our product. But in reality, it’s just not that simple. So maybe a success story isn’t a good place to start.
Instead, let’s focus on a spectacular failure.
How Casper Bet Big, and Lost Even Bigger
In 2015 Casper, a disruptive mattress brand launched its own publication called Van Winkle. When it launched, content marketers rejoiced and held it up as a beacon for the future of branded content
But alas, Van Winkle’s future became grim, and after about a year, it was shut down. When asked why they pulled the plug, the head of the publication stated:
“It goes back to the marketing problem that you can’t measure brand [awareness]. If you read an article on Pineapple and then book a room on Airbnb, I can’t prove that.”
The fact of the matter is that there are many reasons brands can fail at content. One of the main reasons is the dual challenge of measuring content’s impact on attention and attributing that impact to people’s actions.
Attention as a Proxy for Action
As opposed to publishers who monetize attention, brands usually look for actions to be carried out by their target audience. This is true even if that action happens at a physical point of sale, a car dealership, or via call with a sales rep.
What we’ve learned through our B2B-focused product is that certain behaviors are excellent for predicting an eventual business-related action like purchasing a product.
In our latest research around B2B benchmarks, we’ve witnessed a clear correlation between the read ratio of certain audiences and the likelihood that they will engage with the company’s sales organization:
So it was clear that this needed to be our roadmap. But how can this data be used to truly measure impact without goals? That seemed like the million-dollar question…
This is part 2 of a 3-part story. Click here for part 3.