My old boss, the CEO of a former employer, was one of the best salespeople I’ve ever known.
He could work a room, listening and knowing just the right thing to say to keep interest piqued and drive value in the conversation. Just as importantly, he knew exactly (and I mean exactly) when to end the meeting and walk out the door. It’s just like show business, “leave them wanting more.”
Anyone who has experienced a bad salesperson has seen the opposite – the classic moment when the rep doesn’t know how to take “yes” for an answer. The customer has usually implied or even overtly said they are interested in the next step, and the rep continues to oversell features, benefits, discounts, and value-added services – all of which are unnecessary.
Two consequences happen when we oversell something. First, we talk the customer out of their decision to purchase. I once witnessed a rep continue to talk and talk and talk after the customer had expressed interest in purchasing. The rep mentioned something about the future development of the product, and it made the customer suddenly question whether that roadmap matched their needs. It killed the sale.
The second effect is almost as bad. The rep wants so badly to ensure there are “no surprises” that they oversell by continuing to offer more and more benefits until the customer finally says, “Stop.” By then, the sales rep has often set such unrealistic expectations that they’re set up to fail.
That’s the situation for marketing and content practitioners selling the use of data to business leadership.#Content marketers often set unrealistic expectations about the value of data, setting up their programs for failure, says @Robert_Rose via @CMIContent @acrolinx. Click To Tweet
Data driven to the wrong destination
“We’re data-driven!” If I had a dollar for every time I heard that when I ask about the measurement strategy to a larger marketing, brand, or demand generation team, I’d be on a beach somewhere sipping a fancy tequila.
Most of the time, once we dive into what’s behind that statement, we find “data-driven” quite literally means the team is driven by data. They have no insight into how (or if) the data is helping.
They are so awash in metrics, analytics, and numbers that they search and find some data that drives every move that they make. Everything they do is driven by data. Every action is supported in retrospect by finding the data.
What these “data-driven” marketers fail to realize is that by doing this, they also build a wall that prevents attempting anything new.
Whenever purely “data-driven” is the starting place, I know what the next challenge will be when someone wants to innovate and do something new. To do that, a “business case” must be made. Someone – usually the person responsible for making the business case – will inevitably ask, “Well, what does the data say?”
But data doesn’t (and can’t) say anything definitively if the idea is truly innovative. What happens? The business-case maker looks at the data they’ve used to justify all previous decisions. When they can’t find helpful data, they look at external best practices to see if the innovative thing matches up to what other people are doing.Data doesn’t and can’t say anything definitively if the idea is truly innovative, says @Robert_Rose via @CMIContent @acrolinx. Click To Tweet
Of course, if many best practices that will point to this innovative thing exist, is the thing really all that innovative?
Do what the data said, not what I said
For the last 10 years, content and marketing practitioners have been sold the magic of data – a way to increase the efficiency and performance of digital experiences. In turn, many marketing teams desperate to show proof-of-life of anything they do with content oversold the power of data. It now hamstrings them from doing anything that deviates from being incrementally above or below average.
I recently worked with a B2B technology company that wanted to launch a new digital thought leadership magazine. For them, this was an innovative new approach to delivering education to decision-makers in their industry. They spent time developing a solid set of “big ideas.” They decided on a content strategy of cutting-edge ideas rather than pragmatic how-tos. They planned to position their subject matter experts as people who could pull customers into the future. The team was excited.
The vice president spearheading this initiative made the rounds to get buy-in from the product, brand, public relations, and C-suite teams.
It didn’t go very well.
In each conversation, the vice president got a lot of resistance with questions about what the data said. In an ironic twist, the data referenced by these other teams was what the marketing team had used to demonstrate the success of previous campaigns. The vice president heard:
- “This sounds like it runs counter to what our SEO data says.”
- “Data says that the end buyer isn’t senior leadership – shouldn’t we be solely targeting the buyer?”
- “Where is the data that shows that senior leaders need this information?”
- “What is your forecast for the number of leads we will get from this?”
- “Do we have data on whether these topics are popular?”
In the end, the magazine project was put on hold.
The lesson isn’t that the company didn’t get to launch a new digital magazine. The lesson is why they didn’t get to launch it.
The team had oversold their use of data to justify every single thing that they did. They had established that they were “data-driven.” Their colleagues simply responded based on what they had been sold: “Why did the data drive you to this conclusion?”
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Data should ride shotgun, not drive
Measuring content and experience is difficult. It always has been and always will be. As I’ve written, our objectives matter more than the accuracy of the data. Ask what is the most important insight to get – that the blog post or white paper was found, it was read, or it changed a behavior? Often, we want insight from the latter, but we use data and make decisions based on the former.
One of my favorite books about data and measurement is The Haystack Syndrome: Sifting Information Out of the Data Ocean by Eliyahu Goldratt. I always reflect on this quote:
Tell me how you will measure me, and I will tell you how I will behave. If you measure me in an illogical way, don’t complain about illogical behavior.
In our selling of data’s capabilities, we must acknowledge occasions will arise when we’ll need to go against the data or proceed without it. Otherwise, we’ll be data-driven to mediocrity.
Data informs the answer to questions. We should drive the car. Data should ride shotgun.Content marketers should drive the car. Data should ride shotgun, says @Robert_Rose via @CMIContent @acrolinx. Click To Tweet
To have the flexibility to try innovative things, we must reframe how we sell data as a value to our content and marketing strategy. These two ideas can help:
- Stop treating data as proof of life: You should cease using and selling the value of data to justify decisions already made. Data-driven value determined retrospectively, as in “Did this campaign work?” is helpful. But if you let data drive your entire strategy, you will put future content marketing ideas into a box – every decision becomes about “beating” the last decision. You’ll never try anything that isn’t trying to “fix” the last decision.
- Content and marketing strategy is not Jeopardy: Get beyond scanning mountains of data to come up with an answer in the form of a question, which shapes your strategy. First, form a purpose, an objective to reach, and then assemble a list of key business questions to help form a plan to reach that objective.Remember, in business, it’s much better to know what you don’t know than to not know what you don’t know. When faced with the latter, the tendency is to dive into the data and find an answer that matches a question you could have.
If you start with an objective, develop the key questions to meet it. Then design what data is needed to answer those key questions. Only then are you using data to inform a decision, not to justify one. Indeed, a key question might be, “Should we do this?” But then, if it’s a new thing, you can acknowledge that answer may not be known before the project begins.
Learning to succeed
Sometimes it’s better to learn than succeed.
Here is an experiment that you can run with your teams. On your next Zoom call (or in your office as the new normal may be), ask everyone three questions. The first is “Should companies like ours be innovative?” I’d bet a fancy cocktail that 90% will nod their heads.
Then, immediately ask the next question: “Is our company (or team) innovative?” This query will almost assuredly result in questions: “Do you mean, like, ever?” or “ Do you mean, now? Are we innovative now?”
Clarify as necessary: “Yes. Ever. Have we ever been innovative?”
Depending on the type, age, and size of your company, your mileage will vary. But for those yes responses, I would bet another fancy cocktail on the answer to the third and final question: “When was that?”
With, I dare say, with few exceptions, everyone will cite something that ended up successful.
You see. Everybody LOVES and remembers innovation, just so long as it worked.
In a business only driven by data, nobody wants to be the dope who said yes to the new strategy that had no data to support the decision and failed.
In a “data-driven” business, you can become incapacitated by the feeling that data should always be the driving force. You’re unable or unwilling to embark on any activity that you can’t ensure will nudge your stats in the right direction.
If you reframe the use of data and measurement, get agreement on the objective, then ask better questions to enable you and your team to make more things that might succeed spectacularly or fail with a thud. As Nobel Prize-winning physicist Niels Bohr once said, “An expert is someone who has made all the mistakes which can be made in a very narrow field.”
So, let’s go use data to empower the decisions that free us up to make some of the best mistakes.
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Cover image by Joseph Kalinowski/Content Marketing Institute