November 19, 2021

The Problem With Marketers Saying They're "Data-Driven"

Oh, the data-driven marketer…

I’ll be honest — I used to identify as one.

But I don’t anymore.

I’ve learned over the years that it creates an overreliance on quantitative analysis.

Quantitative analysis requires clean and comprehensive data.

But most of the time, that doesn’t exist.

Take marketing touchpoint data.

Most touchpoints can’t be tracked with software because so much of the buying process (especially for B2B) happens via dark social.

When the data needed to make a decision doesn’t exist, marketers get stuck in analysis paralysis.

Analysis paralysis prevents action, which leads to little or no results.

I’m not implying that quantitative analysis doesn’t have its place. 

Rather, it should be used in combination with more readily available and abundant qualitative data.

 In this post, I’m going to lay out the mental model I use when thinking about the role data and analytics play in marketing decision-making.

Our overreliance on quantitative data

Back in 2005, the term “big data” emerged.

Fast forward 17 years later, and it’s amazing what “big data” has enabled:

I appreciate how far we’ve come with data and am optimistic about future use cases, but in marketing, I tend to see an over-reliance on quantitative analysis.

Here’s a common scenario:

A decision needs to be made by the marketing leader, and they want to make the correct one. 

They accumulate as much quantitative information as possible to help inform that decision. 

But, when the data doesn’t provide a clear answer on what to do, analysis paralysis sets in. 

The executive keeps searching for new information and new analyses.

Weeks go by with no decision. 

The executive doesn’t see the quantitative data to support a specific decision, so they choose the path of least risk — change nothing and continue business as usual.

Decision-making like this halts innovation and kills companies.

We live in a world where online privacy is being prioritized more and more. 

Trends appear to be pointing to over time there being less data available to marketers (IOS 14 is a good example).

Historically, marketer’s have been trained to justify everything they do with data.

But in a world with less data and customer buying behavior changing as technology evolves, justifying everything with data is impossible.

It's time to reframe the role data and analytics play in marketing decision-making.

A mental model for data and analytics

When someone is stuck in “analysis paralysis” mode, they’re usually looking for a perfect answer.

But a perfect answer doesn’t exist.

There’s always going to be some degree of uncertainty in any decision you make.

Take Nassim Taleb’s Black Swan Theory.

A Black Swan event is a rare and unpredictable event, with extreme impact.

The rise of the internet is a Black Swan event.

Many retail businesses didn’t see the internet coming and were destroyed by it.

You can’t predict everything that will impact your business and will always be operating within some degree of uncertainty.

The purpose of data and analytics in business is to reduce uncertainty in decision-making, not eliminate it.

Rather than trying to use quantitative analysis to make perfect decisions, use it to reduce the probability that you make the wrong decision.

Qualitative data and the human brain

JeVon McCormick is the President and CEO at Scribe Media and former President and CEO of Headspring.

He played a major role in taking Headspring from $2m to $100m and is also an author, prolific stock market investor, and student of business with 30 years of experience under his belt.

He made decisions at Scribe for years with very little quantitative data because it wasn’t available to him. 

So was he making blind, irresponsible decisions?

No.

We say certain people have good intuition.

But where does intuition come from?

Experience.

Think of all the experience JeVon has after 30 years in business. 

Experience is just a mental model for crunching qualitative data and the data source he was crunching was people data.

He’d talk to people. 

Customers, people at the company, friends, etc.

Over the years, the model he used to understand the information he was receiving from people got better and better.

Examples of other forms of qualitative data in marketing:

  • Comments left on social media posts or ads
  • What customers tell you when you talk to them
  • Free-form responses on a market research survey

There’s tremendous value in qualitative data like the examples above because it provides added context you can’t obtain quantitatively.

So why do we value quantitative data more than qualitative?

It’s pretty simple.

Quantitative data is tangible.

You can present it on a table or chart for the entire boardroom to see.

It’s hard to argue with quantitative data.

Qualitative data on the other hand has to be interpreted.

Because there are different interpretations, qualitative data lends itself to being more subjective. 

But you want both as a marketer.

Your goal should be to reduce uncertainty with both quantitative and qualitative data, while avoiding analysis paralysis and not allowing a lack of information to slow you down.

How to analyze qualitative data

The most useful qualitative data for marketers comes from your customers (e.g. talking to customers, surveying customers, etc.) and you analyze it by listening.

When you consistently communicate with the people that buy from you, it’s amazing the connections your brain makes with the information. 

For example, when I started as Head of Growth Marketing at Scribe Media, I spent a full month listening to at least one sales call each day.

By listening to sales calls, I developed a deep intuition of who our best customers are, how they talk, why they want to write a book, what questions they have, etc. 

I still listen to at least one sales call each week.

Even better than listening to sales calls is talking to both current and potential customers.

You can guide the conversation and go deep into areas you can’t go into on a sales call.

You might be thinking, “Okay that sounds great, but how do you know what questions to ask?”

It depends on what you’re trying to learn.

Sometimes it’s something specific like, “why do you use this product feature?”

But more often than not, you don’t know what you’re looking for until you find it.

Here are a few tips to improve the quality of information you’re getting from customers:

Qualitative analysis of your customer isn’t something you ever “finish.”

As your business grows, your customer base grows, which means there’s always more to learn about them.

Final thoughts

In marketing, qualitative and quantitative data should be given equal weight.

Your goal is to reduce uncertainty in decision-making using both types of data.

Don’t let a lack of quantitative data prevent you from moving forward.

DM me on LinkedIn or Twitter if you have any questions!

Until next time.