Data-driven marketing is all the rage these days in the era of digital marketing, but creating a solid data-driven marketing strategy still eludes many companies. There is so much data out there and trying to wrangle in all together and make sense of it to drive decisions can be daunting. In one survey, 81% of marketers said implementing a data-driven marketing strategy was “extremely” complicated. If you’re in this boat, you clearly aren’t alone.
While coming up with an effective strategy may be challenging, it isn’t impossible. Before you can come up with a data-driven marketing strategy, you and your team have to thoroughly understand the data-driven approach.
What is a Data-driven Marketing Strategy?
Data-driven marketing must begin with a data-driven marketing strategy. Without one, it’s like playing football without a game plan. Everyone is doing what they think drives results, but there’s no overarching vision or roadmap on how to achieve goals.
At the most basic level, data-driven marketing is using customer data to drive marketing campaigns. A data-driven marketing strategy is simply defining how you will collect and access customer data, how that data will be used, and the goals of the data-driven campaigns. The strategy should outline roles and responsibilities, as well as how success will be measured, reported, and drive continual improvement.
Why Do You Need One?
Marketing has always been about getting into the head of the customer. In the past, however, marketers were limited to their gut feelings and maybe relatively small market segments where marketing ideas could be tested. These methods may have worked okay in the past because they were the only options, but they were hardly scientific. One study found 36% of marketers strongly agree that data-driven decisions are superior to those based on gut instinct or experience.
The success of the marketing campaigns that resulted was little more than throwing spaghetti on the wall to see what stuck. Trial and error was the name of the game. Some ideas did great, while others failed miserably, consuming precious resources along the way and resulting in missed opportunities as they missed their mark.
Today, we have more accurate, reliable customer data at our fingertips; data that is gleaned not from a small segmented population, but from actual customers from around the globe. Marketers have access to all kinds of customer data – data in the CRM, ERP, social media data, sales data, website data, e-commerce data, and other martech tools. It’s all there, but it isn’t always accessible or integrated, making it challenging to do anything with it.
When it’s all connected, however, that’s when you get a comprehensive picture of your customer – their likes and dislikes, preferences and buying habits, personal details like anniversaries and special events, and so much more. That’s where a data-driven marketing strategy comes in. It helps define how you can use that data to fuel marketing campaigns at an entirely new level. Instead of mass marketing to a relatively unknown audience, you can opt for targeted, personalized marketing that is more likely to resonate with your segmented population. Your campaigns become less about trying to find the needle in the haystack and more about reaching precise customers at the right time with the right messaging on the right channel.
This kind of marketing is proving to be much more beneficial from an ROI standpoint than traditional marketing efforts and it requires a data-driven approach. But here’s the caveat: your data has to be accurate, contextual and relevant. Forbes warns that even with a ton of customer data, not all of it makes sense, saying, “Certainly, some brand decisions are made more thoughtfully with better information. But others are now being ‘informed’ by spurious or irrelevant information, making the related decisions just as likely to be wrong, though perhaps for different reasons.”
It’s not just the quantity of data you have; it’s about the quality of that data. You have to have confidence that your data is clean based on your set standards, and records are current, complete and ready to use in real-time.
Common Pitfalls of Data-Driven Marketing
So, we know gut instincts and limited market testing isn’t ideal, and now we have to worry about our data not being perfect, either? Well, sort of. Data is just data. It doesn’t do anything. It’s just information. There’s a lot of it out there and it changes all the time. It doesn’t do you or your marketing team any good until it’s validated, operationalized and actionable. That means the data needs to be thoroughly cleansed, analyzed, and reported in a way that actually eases decision making.
Marketers have all kinds of tools in their martech stacks, yet the vast majority of leaders still feel overwhelmed when trying to design a data-driven marketing strategy. That means they have the data, but they don’t know how to access or use it properly. Poor database visibility is one of the most common complaints among marketers and it’s precisely the reason so many strategies fail.
Another problem is the fragmented nature of the martech stack. The CRM doesn’t talk to the ERP that doesn’t share data with the marketing automation platform (MAP). Instead, marketers use labor-intensive, time-sucking, manual processes to dig into these systems to try to connect the dots. Gartner found that nearly one-third of marketers believe a lack of integration between their martech solutions is the largest impediment to effectiveness.
All of this inefficiency is more than a drain on resources, it takes up precious time that could be used to identify and leverage real opportunities. If you’re missing opportunities to engage and delight your customers with relevant content that drives purchasing decisions and boosts brand reputation, you can bet someone else is cashing in. Timing is everything in marketing. Marketers must be able to be agile and responsive, transforming marketing data into actionable intelligence.
Developing a Data-Driven Marketing Strategy That Works
When approaching a data-driven marketing strategy, the first thing you must do is understand the enterprise’s strategic vision. What is it the company wants to do? Is it to increase customer engagement? If so, that becomes your vision, too. Your strategy, therefore, is to outline the marketing goals to achieve that strategic vision and then roadmap exactly how you’re going to get there. You need to then break down ideas into actionable plans that include assigning resources, responsibilities, budgets, and work.
From there, you need a software solution to make the applications in your martech stack talk with each other. Remember: access and visibility into the data are critical. Until you connect all of your systems, tools and applications into a centralized platform that cleanses, analyzes and operationalizes the data, your data will remain in silos. Your people won’t have the data they need, costs will continue to escalate, and opportunities will be lost.
Once you have shared data from across your martech stack, you can then begin executing the plan. Perhaps boosting engagement begins with increasing personalized content across multiple channels. With accurate, contextual, relevant data in hand, your team will be able to properly segment your target audience, generate content you have confidence they will want and deliver it to them on the channel they prefer when you know they are most likely to want it.
From there, you have the systems in place to measure the success of each campaign at macro and micro levels. You can identify trends, better understand budget and resource issues, and see which marketing efforts delivered the most value.
This is just one aspect of what a software solution can do for your data-driven marketing strategy. The solution should be able to help you identify and analyze your total addressable market, rank the quality of your database, reveal your company’s marketability, and much more. The key to any solution is to integrate your martech, provide visibility into actionable insights, and automate as many processes and tasks as possible to optimize resources.
Implementing a data-driven marketing strategy doesn’t have to be complicated. You just need the right software to bring all of the components together. By empowering your team with the right data that’s hiding in silos, they can be more productive and effective as they execute the strategic vision.