Is There too Much Data in Marketing?


Big data has made its mark everywhere, including in marketing. The thought of a company choosing to ignore its data to drive marketing decisions is unthinkable these days. According to the World Economic Forum, the digital world's size was 44 zettabytes in 2020.


For the sake of scale, that's more than 40 times the number of stars in the observable universe. As marketers become ever more obsessed with gathering and dissecting their data, is there a danger of insight getting lost in this massive stack of information?


Aaron Belz, Content Strategist at financial holding firm Truist, thinks so. "Our algorithms tell us to behave a certain way to appeal to prospects," he says. "However, reflecting the wants and needs of the user might not necessarily be the best thing to do at all times."


The Problem With too Much Data

As data collection efforts ramp up increasingly, there's too much focus on quantity over quality. One of the issues that companies perennially have to deal with is separating the signal from the noise.


In his book Social Network Analysis for Startups, author Maksim Tsvetovat says that raw big data often looks like a hairball, and a scientific method is necessary to unravel it. Teams have to take into account the context in which the data was collected to generate insights.


For instance, a KPI such as page depth scrolled on your pillar content might lead you to think that a visitor was deeply engaged. However, there is a possibility that they were looking for specific information and couldn't find it before leaving in frustration.


Combining other data points, such as that prospect's place in your funnel, along with engagement with other forms of content will help you create a picture that is in line with reality.


Even if you do manage to sift through reams of data, you're likely to find that the information you've received is incorrect. For instance, a report by Experian highlighted that 75% of firms believe their customer contact information is incorrect. Most companies might as well not collect any data!


Big data collection and analysis that aren't backed up by proper governance and integration processes is pointless. It's a bit like trying to drive to a destination without a map to guide you. You're just as likely to end up in a ditch as you are at your goal.


Aside from the lack of processes guiding big data analysis, there's a bigger problem with relying too much on data.


Innovation and Data

The fact is that innovation, the kind that really changes perspectives and creates giant leaps forward, does not come from existing data. If Steve Jobs relied on data to build the iPhone he would have concluded that such a thing would be impossible to build. After all, there was no precedent for such a product.


This isn't to say that no innovation comes from data. However, by its very nature, data constrains you into viewing user behavior a certain way, and as Belz aptly puts it, "People don't always know what they want."


To create a genuine connection, you need to give your brand and product a human feel. You have to give it an identity that gives it personality. It has to have a voice. This is how you can get your prospects to trust you when you push your product towards them or take a stand on controversial topics.


Ignoring the human touch when testing brand resonance can lead you down the wrong paths. For instance, Belz highlights an example of the common process of testing CTA effectiveness when developing messaging. After measuring user clicks, the bottom 5 CTAs are eliminated, and brand language evolves around the top 5.


"We're responding to traffic, and this often constrains the user from getting something new," he says. "There's a danger that we're reacting to a false premise within our data."


The test CTA messaging in this case isn't considering the possibility of creating something new.. It's merely tweaking existing messaging and hoping for revolutionary results.


True change does not happen this way. If your brand's existing messaging was formulaic, it's unlikely to change the way you're perceived by your audience.


A Better Process

Despite all of these pitfalls, there's no doubt that data is essential in today's marketing landscape. The right way to go about using data would be to adopt an approach that marries the importance of data with a human touch.


Teams that wish to make data-driven decisions should practice good governance policies and always keep the data context in mind. Make sure you're measuring the right thing when determining your KPIs.


If your aim is to change your brand messaging, then validating your data-driven conclusions against your buyer personas is a good move. Buyer personas often change, and your data might be alerting you to this. Alternatively, you might be measuring the wrong parameters and might need to revamp your assumptions entirely.


While listening to your customer is important, you must give them what they need, not what they say they want. This approach demands that you step back from your data and consider the big picture. Understand that data only shows you what has happened.


Deriving conclusions that change your business requires a human touch and creativity. A purely data-driven approach cannot achieve this kind of change.


The Best of Both Worlds

Intuition has been receiving a bad rap as data collection has increased. There's no doubt that data is preventing companies from betting millions on incorrect hunches. However, completely discarding intuitive inputs is extreme.


Effective marketing and brand communication these days require you to combine these two worlds and bring greater context to your conclusions. The results will be rewarding, and your customers will make sure you know about it.

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