With data growing bigger and bigger each day, marketers are finding it increasingly urgent to be able to transform it as quickly and easily as possible. Yet, as many soon realize, there is no ‘one size fits all’ solution to getting clean data to flow through an organization. The fact that there are so many different tools out there is proof enough.
And so, as much as we can all agree that data transformation is key for just about every data-driven business out there, we feel like there is a need to focus a bit more on the 'why', why is data transformation so important for marketing analytics?
“Companies that are spending the most on marketing technology are also the top performers,” the MIT Sloan Management Review cites a recent study. In other words, investing in the right data transformation and analytics tools can send companies to the front of the line and ahead of their competition.
Meeting customer needs and optimizing teamwork
A survey that we recently conducted among over 300 respondents in C-level positions, including CEOs, CMOs, CTOs, and Chief Data Officers (CDOs) found that more than 60% of those executives consider improving their company’s data analytics capabilities to be a number-one priority.
These results are in line with what a Gartner report discovered about companies’ marketing spend. Although many are cautious about investing in too many marketing technologies - likely due to their struggle to completely understand their benefits, spending on data analytics tools has gone up. In fact, it gets the largest share of marketing budgets for 2018 at 9.2%.
Now, on a general level, the benefits of data transformation tools are quite straightforward: They allow for large pools of data to be cleaned and harmonized quickly and accurately, with minimum time spent on the part of employees. That way they can concentrate on the actual analysis and on deriving actionable insights.
More specifically, though, such tools can help marketers establish a closer relationship with their customers and focus on what is really relevant.
Ensuring the quality of your customer data
As most of you surely know, customers are not easy. They want to feel special and have their wishes met by companies. If your data is off and you target the wrong people with the wrong content, chances are none of them will stay with your company for too long. If your data is indeed good, however, you may well be on your way to overnight success.
“You can run the best campaign in the world, but if the data is dirty, your conversion rate will suffer simply because sales teams need to work harder to get in contact with the lead,” reads a post on ReachForce’s blog. Or it might even be the case that you go after the wrong customers in the first place.
Data transformation is, thus, crucial. Without the proper tools to collect and transform your data in near-real time, it could be that you are always just a bit too late to deliver exactly what your customers want and need.
What’s more, data transformation is sure to improve your internal team dynamics, too. The fact is that, quite often, people work within the constraints of their own teams and interact with others when actually necessary. That’s the case in most large organizations anyway.
Well, an integrated data transformation and analytics process can help break some of those walls. According to insights from Google, “86% of senior executives (senior VP or higher) agree that eliminating organizational silos is critical to expanding the use of data and analytics in decision-making.”
Data transformation is there to not only speed up certain processes but also to democratize access to data, so as many (relevant) stakeholders as possible can make use of it. Eventually, with various teams working more closely together, you are sure to get the most out of your data, meet your customers’ needs and contribute to your company’s overall bottom line.
Getting visual with your data
Using the right tools to transform your data into clean and structured sets of information is the first step to getting your hands on the insights you really need. The second step is to connect the dots and draw the right connections between the individual data points.
And what better way to do so than by visualizing what is already there?
For many, turning data into smart (visual) data, and doing so as quickly as possible, has proven crucial in recent years. Imagine the following: Instead of seeing a long list of numbers for your weekly or monthly sales, with smart data you get a graph that visualizes the ups and downs in those sales over time. Not only does the latter look nicer, it’s a lot more useful, too. Overlay that with an additional set of criteria and you know who is buying your products, when and why.
In a world of constant information overload, visuals are crucial. Essentially, they serve two main purposes. On the one hand, visuals attract people’s attention, while on the other, they help put information in the right context and help make sense of it all.
Internally, marketers have been using visualizations to illustrate whether or not certain marketing efforts are paying off, how their campaigns are performing, and what kind of messages are actually having an impact on customers.
For customers, in turn, “data visualization helps guide them through the sales funnel. These visualizations can be incredible tools, clearly demonstrating the upside of a product or service. If packaged with reasonable, balanced, and no-nonsense content that interprets the data, the power of data visualization can translate into sales,” according to digital marketing expert Mike Canarelli.
Marketers often use visualizations in their reports to clients as it is the easiest and most clear way to highlight the connection between their marketing efforts and ROI. We all know that ROI is a tough one to prove anyway.
Leverage an analytics tool to get the most out of your data
At the end of the day, all of this would not be able to achieve unless your data has first been transformed by a powerful data analytics tool of your choice. Once you have one at hand, you can leverage it to quickly sort through your data, identify the most relevant bits and pieces of it, share it across teams, and visualize it on demand. And that is the basis for the rest of your marketing efforts.
