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Conceptual illustration of data structures in shades of red and blue. Conceptual illustration of data structures in shades of red and blue.

Why data analytics training is important for marketing teams

From instinct to insight: How data skills secure your place in modern marketing

You might have heard the saying, “Data is everyone’s business”. And it’s true. Ten years ago, organisations might have left data to IT, or specific Insights teams, but these days data science and analytics inform the operations of practically every department – including marketing. If you’re a modern marketing professional with zero data skills, you’re rapidly working yourself out of a job.  

That’s because marketing is built, fundamentally, on decision making. Which audience to target. When to run a campaign. What messaging gets the greatest cut-through. And when your GM turns around and asks, “Why did you choose A instead of B?” you need to be able to answer with something better than, “Because it felt right.” That’s where data analytics comes into play. 

If data is king, then marketing is a monarchy.
Raja Subramanian from Power Wizard

What is marketing data analytics? 

Marketing data analytics is simply using customer and purchase data to develop marketing insights. This can cover a broad variety of metrics, from audience segmentation to A-B testing to personalised digital campaigns. With every action, and each piece of data collected, marketing teams can generate a better picture of their customer base, and their product, which informs their decision-making going forward. In other words, data analytics is the process by which marketing teams become more effective marketing teams.  

Why is data analytics important for marketing teams? 

Data analytics can help marketing teams in several ways. Really, it’s about improving decision-making through data-driven insights.   

Insight generation 

Data analytics allows marketers to gain insights into customer behaviour, preferences and emerging trends. By analysing data from web traffic, sales and social engagement, marketing teams can basically understand the mysterious alchemy that drives consumer behaviour. Then – and this is the crucial bit – adjust their strategies accordingly. Data insights without action are meaningless. The trick is to take customer data, and then spin it into a tangible marketing strategy.  

Targeted marketing 

If you’re not already segmenting your audience by demographics, behaviour or preferences, you’re doing marketing wrong. Data analytics allows marketers to create targeted social or SEM campaigns that resonate with specific customer segments, and identify which of those segments generates the highest ROI and conversion rates. As American marketing expert Philip Kotler says:   

There is only one winning strategy. It is to carefully define the target market and direct a superior offering to that target market.

Optimized campaign performance 

By continuously analysing marketing campaign data, marketers can essentially figure out what’s working, and what’s not. This lets them optimize their strategies in real-time, adjusting key messaging, creative, or channel selection, to maximize return on their spend. Does TikTok generate better click-through than Instagram? If so, it might make sense to push budget in that direction. Email campaign getting poor open-rates? Let’s mix up the subject lines and quickly A-B test. Data analytics lets marketers answer the most fundamental question of marketing: “Is our way of doing things the best way of doing things?”   


Personalised marketing has been the catch-cry of the industry for at least the last 10 years. With vast amounts of consumer data at their fingertips, marketers can finally serve up personalised ads, based on purchase history, social interaction, and browser patterns. Personalisation has become so all-pervasive that Salesforce research found that 66% of consumers now expect companies to anticipate their unique needs. 52% expect all offers to be tailored specifically to them. This is a challenge for marketers – customer expectations are higher than ever – but also an opportunity. With personalised marketing content, you can reduce customer acquisition costs by almost 50% 

Forecasting and planning 

Putting together your big marketing strategy presentation? One of the first questions you’ll be asked is: what do our next 12 months look like? How about the next five years? Through data analytics, marketers can forecast future trends and consumer behaviour, enabling them to make informed decisions and plan their strategies accordingly. You can start by looking at historical user data, to try and identify seasonal trends. This not only helps your marketing team get a leg up on the competition; it positions the business as a forward-thinking industry leader.  

Measuring ROI 

If a campaign exists, but there’s no way to measure it, did it really happen? This is one of those philosophical questions that have plagued marketers since the dawn of time. Luckily, we have ROI and advanced data analytics to provide an answer. With a robust data suite, marketers can measure things like customer acquisition cost, cost-per-click, conversion rates, customer lifetime value, and dozens of other key metrics to find out if a campaign was really ‘worth it’. And this can get quite granular. ROI isn’t simply “Did our revenue outstrip our spend?” – although that’s a big part of it. To really analyse return on investment, you need to dig a little deeper. 

This article was originally published on 6 June 2024