4 elements of a strong data-driven marketing strategy
Ben Hannan, Operations Manager - Innovation & Marketing, Ovato
The concept of using data to drive decisions is nothing new. In 2019, there are plenty of organisations talking a big game when it comes to data - but many of them aren’t actually delivering on the promise.
Yet customers expect experiences to be seamless and personalised, which means data is essential. This doesn’t mean using all the bells and whistles to ‘surprise and delight’. Sometimes it’s as simple as using the information a customer provides to give them fewer hoops to jump through.
So, as a marketer, what should you actually consider when it comes to building (and executing) a data-driven strategy?
The first step is making sure your data is accessible and easily understood. While marketing has typically been siloed into different departments, from events and direct marketing to digital and social media, this led to a fragmented approach that now needs to be effectively integrated.
Unifying all your sources of marketing data will give you a single view of customers that means you can understand them on a more personal level. You’ll know if someone that received your store catalogue has also interacted with your customer support team online or subscribed to your email newsletter. Understanding how that person interacts with your brand online will also let you show them more relevant content or personalise their next conversation with you when they’re trying to solve a problem.
2. Smarter targeting
With a cohesive view of your customers, you can get smarter with your targeting tactics. Ultimately, the right targeting will eliminate irrelevance and wastage – for both your brand and the audience. Your customer won’t see material that’s not relevant or useful to them, and you’re not spending money and resources getting that marketing message in front of them. Instead, you can focus only on the customers that are likely to purchase and will find your messaging valuable.
In the digital world, this means being clear on who you’re trying to reach. Narrow down by different criteria, like location, age, interests or job title. Lookalike audiences enable you to reach people similar to your most profitable customers or prospects. And with matched audiences you can use existing data, like website visitors or an email subscriber list, to reach only those people.
When it comes to print marketing, you can apply the same concept. Custom audience segments, based on how they transact with Australia’s biggest stores, let you identify the most valuable (and least valuable) groups to receive your printed materials, such as catalogues or flyers. This means you can test and trial new things without risking your bottom line, as well as identifying distribution locations that are directly contributing to an increase in sales.
When you’re targeting a relevant audience, you also want to make sure your message is relevant. And a little personalisation goes a long way. Using data to inform your content allows you to add that personal touch, whether it’s as simple as adding the recipient’s first name to an email subject line, or as sophisticated as creating an entirely personalised catalogue for a set of VIP customers based on their previous purchase habits and local offers.
Personalisation also extends to the experience your customers have with your brand. There’s a reason that Amazon’s recommendations engine accounts for so many of its sales – it gives customers the sense that they’re receiving tailored product selections picked just for them, based on purchase habits and interests. The same applies to customer support and your front-line sales or service teams. If they have a solid understanding of who the customer is and what they need before even initiating conversation, it will be a more fruitful and positive interaction for everyone involved.
As machine learning and artificial intelligence become increasingly accessible as business tools, predictive analytics will soon be an important driver of marketing decisions. Based on real behaviour and transactional data, we can start to predict likely outcomes. This means you can better understand the next action your customer will take – such as making a purchase or taking a step to learn more about your business offering – and tailor their experience for them. When managing digital and social campaigns, predictive analytics will also give you better insights into how your campaigns are likely to perform, so you can allocate spend and resources effectively. We’re already seeing a simple version of this, with platforms such as Google AdWords and Facebook providing predicted reach and engagement figures based on chosen targeting and budget, but it’s only going to get more advanced.
Using data to inform your marketing strategy isn’t about seeing your customer as a set of numbers and graphs. It’s about recognising that customers are real people and using all the insights at your fingertips to treat them in an individual, personal way.
Find out how Ovato can help you to harness your business data to create more efficient and effective marketing strategies.