We all know that marketing is a broad discipline, demanding both creativity and an eye for numbers. Yet even those who are more comfortable with the latter are sometimes daunted by the use of data science in digital marketing.
While many marketers are now familiar with the concepts associated with data science – such as machine learning and big data – knowing when and how to apply them is often a different matter. But if you are going to make a strong case to senior management for investment in a big data business strategy, you will need to understand how it delivers on marketing campaigns.
Google, social media and email analytics offer powerful insights about your audience, track engagement and drive conversions, although they only take you so far. One problem is siloed and/or incomplete data make it difficult (if not impossible) to maximise ad spend, since you risk choosing the wrong channels and creating content that fails to resonate with potential customers.
Demographic surveys can be another source of poor-quality data, leading to ill-founded assumptions about purchasing behaviour being influenced by something as vague as age or location. In a world where people are bombarded by marketing messages, there is a danger that they will either switch off or worse still, perceive the brand negatively.
Alongside the usual digital marketing analytics, data-led segmentation enables you to gain a deep understanding of who your customers are, including the values, beliefs and past actions behind their purchasing decisions.
Clustering in a common technique in data science – in a nutshell, it groups together data points according to any number of specified variables. From this, you are able to segment customers according to shared characteristics, which could be anything from how they choose a holiday to what they buy as part of their weekly shop.
These segments carry more weight compared to traditional demographic methods, since they are based on real actions and sentiments. Suppose a grocery retailer wants to know whether it is the right time to launch a new vegan line, for instance. By understanding shoppers’ attitudes to meat consumption, they can determine whether those most likely to buy plant-based products are a valuable segment before making an investment.
It is important to remember that a good data scientist will not present you with vast swathes of information but clear and actionable insights that allow you to build customer profiles and optimise your marketing budget. Every successful campaign, no matter how creative, is underpinned by robust data – so, whether you are targeting new or existing customer segments, data science is key to achieving your marketing and business objectives, while also delivering an impressive ROI.
If you want to learn more about how data science could support your marketing strategies, contact us.