Cutting through the jargon

Big data, attribution modeling, artificial intelligence, marketing automation, segmentation, analytics. These are some of the terms and phrases that get thrown around whenever someone mentions the words “data” and “marketing” in the same sentence. While it can feel like you need to learn a whole new language just to keep up, the truth is that data marketing really isn’t that complex.

“Data marketing is actually really simple and if explained in less complicated language, can be understood very easily,” says Keith Lindsay, managing partner at Arc, a data-driven creative agency,

Data insights are particularly simple in that they’re something people use daily, he points out. Think about the last time you spoilt your best friend with a gift you knew they’d love or all those times you buttered up your parents before asking for something you wanted. These seemingly innate efforts are actually driven by data insights – the act of using something you know about somebody, with the goal of getting a positive reaction from them.

“The better we know someone,” adds Lindsay, “the better equipped we are to know how to speak to them, understand how they’d like to be treated and what they are interested in. And it’s no different when it comes to data marketing, because it’s these same data insights that we use to create communication that appeals to our target audiences and in the end, gets them to act in the way we intend.”

In other words, data marketing is not about being Big Brother or proving how clever you are, but rather about delivering the best experience to your customers, using what you know about them, so that you can serve more relevant offerings to them and ultimately ease their path to purchase. Don’t forget that in the process, you’re saving money too, because you’re marketing directly to people who are more likely to buy your product, rather than wasting your time on people who are just not interested.

So, the concept of data marketing is seemingly simple, but where exactly do you start in a world where data forms part of nearly every touchpoint in daily life (think: social media, gym, hotels, loyalty programmes).

The first rule of data marketing, says Lindsay, is beginning with the end in mind. “Start with what you want to achieve, and this must extend beyond just wanting to know your customers better. Your data marketing strategy must have a solid transactional component – for example, get more customers, retain the ones you have, get current customers to spend more or shift customers’ purchases to your more premium products.”

Second, think about the data you need to identify to achieve the desired outcomes. Customer data can very often be elusive, so it’s important to craft a strong strategy that puts measurement first. The best data strategies start with the development of an ideal customer journey. Ask yourself how you would like your customer to experience your brand and what their ideal responses and actions are over time. Good data isn’t captured overnight, but the key is to ensure you have a continuous and consistent stream of useful data, so when planning, keep this in mind.

Third, make sense of the data. “Those who see the most success when it comes to data are those who only use what is needed. It’s important to reduce complexity, deliver key insights and come up with a clear direction that guides your strategy,” he says.

Fourth, don’t let a small budget stop you. “You don’t need a million-rand marketing automation platform to make your data work for you. If you’re good with Excel and then VLOOKUP is your superpower, use it. And if segmenting data in Mailchimp works for you, do it!”

Lastly, but most importantly, he says, start small and experiment. “Don’t get caught up in mapping out your customer journey in intricate detail, and with every eventuality and permutation. It’s easier said than done, but remember, simply starting and doing something is the best research. Use what the data is telling you and refine as you go, and don’t forget to test all along the way.”