The way we market has changed. Gone are the days of one-size-fits-all campaigns, massive email blasts and measurement of direct mail campaigns by their weight. Relying on a “spray and pray” approach simply won’t work anymore because customers expect so much more from us as marketers. Customers now expect their interactions with a brand to have greater immediacy and personalization.
Changing customer expectations have forced all marketers to use analytics to understand behavioral trends and better personalize our interactions with customers. If you want to evolve into an analytical marketing organization, first you need to focus on your mind-set. The evolution of your organization begins by shifting how you and your organization think about data and analytics in the way you go about marketing.
The shift to adopt an analytical mind-set certainly had an impact on my career. It was initially driven by our need to do a more effective job at measuring the value of what we were doing, especially when considering our impact on the sales pipeline and revenue. And we had to think differently because we now had all kinds of new data and metrics available that would allow us not only to look at effectiveness, but also to identify potential. Measuring impact in a quantitative way was critical. Being able to use analytics in predicting what would work or responding to the customer’s behaviors was an even more powerful motivator.
These changes were also forced on us as marketers because, due to the massive influx of new digital channels on the Internet and social media, our customers’ expectations had changed. And they continue to change. We understood that if we wanted to respond more effectively to our customers on their decision journey, we needed to build an analytical culture capable of interacting with them in a highly personal and customized manner that was also flexible enough to change directions quickly.
Be accountable for your data
The first step in shifting your organizational mind-set to that of an analytical marketer is changing how you think (and feel) about data.
Everyone on both the consumer and business sides appreciates the value of data — all types and sizes of data, as well as the evolution from Big Data, and the Internet of Things. The key for the analytical marketing organization, regardless of your industry or your customer, is to understand how you can use all of the new data to effectively personalize your interactions with your customers. After all, as Emmett Cox, a business intelligence expert who has worked for large organizations like Walmart, GE and Kmart, writes in his book, “Retail Analytics,” “Data without use is overhead.”
The key is that you and your whole marketing organization need to shift your mind-set so that you understand the importance of data. It’s your responsibility to collect it, care for it and establish rules for governing your data. Cox told me that, while most organizations have moved to embrace their data, they’ve also fallen prey at times to collecting data for data’s sake, without first taking in the business value of that data.
“Too often, organizations start chasing everything they already have,” he said. A good rule of thumb in making sure you are collecting the right data is to ask yourself what three things about your business are keeping you up at night. If you are collecting data that will help address those concerns, then you’re on the right path.
A continuous process
Our experience with a data strategy is that it is a continuous process. Even with all the tools at our disposal, data collection, management and governance are challenging. As you grow and change, your needs will continue to shift direction. The way we sell, market and support our customers has morphed through the years, affecting the type and volume of data we have. For marketing, we’ve continued to expand our data sources in an effort to gather more and more information on our customers, especially from preference and behavioral perspectives.
Our journey as an organization to better embrace the stories behind the data we were collecting began in 2009 when we modernized our approach. Until that time, we had relied on a disparate array of data sources, mostly dozens of spreadsheets, to track our marketing campaigns and responses. It was largely managed manually and on an ad hoc basis, which created huge hurdles every time we needed to create a contact list for a new campaign. Sometimes it took up to three months just to build an accurate list we could use as part of a promotion. In time, we began to realize how untenable that kind of system was.
That’s why we shifted direction and began to implement what we call our data mart, which is quite simply a structured source that pulls together all the disparate data that used to live in spreadsheets. With our data all in one place and updated daily, we could begin to paint a full picture of our customers, because we could, for the first time, see how all of their different behaviors were connected. For example, in the past, we might have lost track of which contacts at which customers we had reached out to during certain campaigns, and how they responded.
“A lot of marketers have access to web analytics and behavioral data,” Matthew Fulk, a marketing director at SAS said. “The differentiator is learning to ask the right questions about the data and making it a priority to do so.”
Understanding the customer experience
A powerful aspect of the data we were now collecting was what people were doing on our website, something we call “customer experience analytics” or CXA. We now knew how much time customers were spending on our website, what they were looking at, which white papers they downloaded, what videos or webinars they watched, and so on. That all combined with more transactional records, such as installation records on a customer’s software service record or how many times a customer called tech support and why, as well as offline behaviors, such as when a customer attended a conference or event and what he or she did there.
Through our data mart, we also began to tie customer behaviors back to building sales pipelines and generating revenue. In other words, the data we now captured could tell us that X dollars of the pipeline eventually turned into revenue and could be tied to which outbound or inbound marketing actions we took.
Added up, that meant we now had a much more complete picture of our customers based on the breadth of the data we could collect, store and, perhaps most importantly, analyze. We had new opportunities to apply our analytical tools to examine customers’ different behaviors, depending on where they happened to be in their decision journey.
Clean data is essential
Having a reliable and clean source of data to work with is critical. Those using reports or analysis can lose confidence when something doesn’t seem correct in the outcome. The first thing they blame is the data, and when they lose confidence in the data, all sorts of problems result. When everyone in the entire organization takes full accountability for the value of the data and its care and feeding, and they truly know the data, the results are strong. The confidence level in decision making is high, the level of innovation is robust, and the impact is evident.
Done right, data digging will bring you to conclusions and additional questions. This provides the foundation upon which you can make solid business decisions. Unfortunately, all too often, we can fall into the trap of using data to confirm a presupposition or bias. That’s why the data by itself isn’t enough.
Adele Sweetwood is senior vice president of Global Marketing and Shared Services for SAS, the world’s largest independent analytics company. These articles are reprinted by permission of Harvard Business Review Press. Excerpted from “The Analytical Marketer: How to Transform Your Marketing Organization.” Copyright 2016 Adele Sweetwood. All rights reserved.
