Marketing Analytics Blog | Adverity

5 New Skills The Modern Marketer Needs

Written by Lily Johnson | Apr 26, 2022 1:01:00 PM

The role of the marketer is changing. Customers are increasingly calling for more channels - and according to McKinsey’s latest research, this goes for B2B customers too. So, the mountain of marketing data is growing. But many are still struggling to turn this data into valuable insights.

The mounting evidence that using data insights to optimize ad spend increases profitability has led to more and more marketers exploring new ways of making data-driven decisions, and their success has led to a shift in the role of the marketer.

Here are 5 skills that the modern marketer needs to add to their arsenal.

 

1. Hypothesize - gut instinct still has a place in data-driven marketing

You’ll have some historic data to work with here, but it’s up to you to turn those insights into a campaign and figure out what’s going to resonate with your audience. And that means more than just the messaging and creative - it means thinking about who you’re targeting, which channels will have the most impact, what day of the week or time of day. The closer you can get to begin with, the better.

While not a new skill, it’s much more complex today than it was a few decades ago when gut instinct was all marketers really had to go on. Today, there are countless dials that the marketer can turn to increase the impact of a campaign, so you need to have a clear plan if you want to optimize your campaigns in real-time. 

Data helps iterate an idea and finetune where those dials need to be to optimize impact, but it’s important to adopt an overarching hypothesis. If you don’t know what you are looking for, what you are trying to test, and how that is related to the overall objectives of the company, then trying to assemble relevant data will become an enormous challenge.

 

2. Test, test, and keep on testing - remember, you’re mining for moments

Again - this one’s not exactly new, but it’s evolved way beyond Nielsen figures and having one guy for TV, one for radio, one for print. With so much data available you need to know what you’re looking for, and you need to streamline that so you’re not waiting days for data insights. This is where tech can really level the playing field for small and medium-sized companies.

According to Andy Lark, Chief Customer Officer at Dubber, the philosophy behind your data should be centered on moments; “You need to be mining for moments, moments that then trigger downstream decisions. And if we can identify moments, we can then architect to meet the customer in the moment before they quite realize they need us, but we can see they're going to need us.”

 

Want to build a truly insights-driven marketing team?

 Check out our roundtable with leading experts Andy Lark, John Veichmanis, and Wes Nichols, on what marketers and CMOs can do to create an insights-driven culture that provides tangible results.

 

3. Don’t be afraid to fail and adapt - avoid confirmation bias 

Telling a story with your data insights isn’t about cherry-picking results that back up your gut instinct. If you’re using your data well then it’s much harder to hide where your campaigns have fallen short - and you shouldn’t feel like you have to.

“A big part of making decisions with data is trial and error - and that means allowing room for your marketers to make mistakes. But, if your company sees marketing as a cost center then that’s not going to happen,” says Harriet Durnford Smith, Chief Marketing Officer at Adverity.

This goes for the big picture too - if you’re not getting the right data, if it’s taking too long to get insights from that data, then it’s time to take a step back and figure out how to make that process more efficient.

“You've got to create a safe culture where everyone is comfortable saying, ‘Yeah, it broke yesterday. And I was at the wheel when we drove the car into the wall,’” says Andy Lark. Indeed, failure itself should be seen as valuable insight itself from which further actions can be derived.

 

4. Smash those silos

At the moment, there’s a gap between the data-savvy analysts and the marketers, who have a much clearer picture of the strategy. In fact, many marketers aren’t currently aware of the data tools their team has access to

Analysts and marketers can’t rely solely on a profound knowledge of their own roles, because like it or not, they’re in this together. If their knowledge is sitting in two separate silos, then it is much less valuable.

The most sophisticated marketing tech stack in the world is useless if its insights aren’t being translated into actions.

“Tech will inevitably become more marketer-friendly, and at the same time, marketers will become more data-savvy. First, we change the technology, then the technology changes us,” says Alexander Igelsböck, CEO of Adverity. But analysts and marketers need to work together to make this happen.

 

Did you know that 30% of marketers say they don't trust their data due to inaccuracies and mistakes?

Learn more in the Marketing Analytics State of Play 2022 report!

 

5. Now take a step back, and get creative with your data

The amount and complexity of data that you can currently use to make marketing decisions is phenomenal. It goes beyond your typical marketing data like impressions, CTR, or sales figures - and I’m not just talking about cookies either. External data sources like footfall or weather data present a really interesting opportunity for marketing. 

Wes Nichols, Partner at March Capital, recounts how he used data while working for a pharma company.

“This company is a large producer of flu medicine,” says Wes. “Every year they were either way over budgeted or way under-budgeted.”

“We saw bus ridership and metro ridership, public transportation numbers, go down several days before the flu symptoms started to be googled.”

Commercial data analytics on this scale have existed for a while - mostly within the finance world. But now that they’re more accessible than ever before, it’s up to marketers to adapt that technology, and figure out what data has value for them. 

 

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