Marketers’ Appetite for Data Is Huge; Their Ability to Digest It Is Not

By Ashley Stirrup | 10.13.17

It’s not uncommon for marketers to feel like they’re among the few not yet wringing every bit of value from their data. The reality is, data optimization is a work in progress for marketers at even some of the biggest brands. Success lies in structuring your operations to amplify data.


Consider: Only a few years ago, Starbucks’ director of analytics and business intelligence, Joe LaCugna, said the Seattle coffee giant had struggled to make sense of the data pouring in from its loyalty card holders, which at the time was over 13 million and comprised 36 percent of all Starbucks’ transactions.


The same was true of its social media data—the coffee conglomerate had mountains of it, but still couldn’t quite figure out what to do with it all, according to AdAge’s coverage of LaCugna’s comments from Big Data Retail Forum.


You’re not alone

Nearly every CIO and CMO understands that harnessing customer data to strengthen operations and grow profitable sales through more effective marketing is essential to differentiating their brand and staying ahead of the competition. Many C-suite leaders have spent millions over the past few years building central data repositories in an effort to eliminate data silos, integrate applications, and extend self-service capabilities to data scientists and business analysts alike to become more data driven.


But like Starbucks, many marketing leaders still struggle with how to best utilize the reams of structured and unstructured data they have about their customers. A whopping 95 percent customer experience decision makers polled for a recent Forrester report revealed that they’re still unable to make sense of data. According to the report, they “rely on segmentation, use single data points, or provide no value when personalizing experiences.”


Although our appetite for data is huge, clearly, our ability to digest it is not.


Data overload leads to poor business practices

Companies have wasted millions of dollars investing in the wrong systems for data management and use. They spent far too much time trying to implement these new systems or connect them to legacy applications. And then they compounded the problem by handing their employees access to data they can’t possibly analyze or effectively manage—i.e. ensure it’s clean, accurate, governed, and accessible. The result? They’re unable to extrapolate meaningful insights. Worse, marketing executives and other business leaders may make inaccurate predictions and bad decisions based on inaccurate information, resulting in poor business performance and ineffective sales and marketing efforts.


It’s no wonder so many marketing leaders feel discouraged or overwhelmed when it comes to managing data.


Despite the many challenges of big data management, several companies have successfully built systems that enable more informed, real-time business decision making. As previously mentioned, Starbucks has made considerable progress in this area, and so has McDonald’s. Both have created data integration and management systems that have well positioned them to get deeper customer insights and distance themselves from competitors.


Starbucks’ uses marketing to enhance the customer experience

Starbucks is making extraordinary use of customers’ data to enhance the overall coffee drinking and café experience. The company has built its mobile reward app into one of the most successful loyalty programs in the United States.


Using its reams of customer data, Starbucks created a holistic view of each customer so it can use marketing to build and strengthen customer loyalty and to spur repurchase. For example, the company personalizes special promotions via smartphones to “non-Starbucks groupies” that gets them back to retail outlets faster than if they hadn’t received the promotion. The coffee company also uses geographic information systems (GIS) to send automated alerts to customers’ phones; for instance, highlighting nearby Starbucks locations where they can redeem reward points or take advantage of special on-site promotions.


McDonald’s bites into digital transformation

McDonald’s is also undergoing a digital transformation that is centered on data. It’s meant to bring “a new level of convenience to more of our customers as we continue to transform the McDonald's experience,” CEO Steve Easterbrook said in an article in The Verge.


The fast food giant used data analytics to augment customers’ drive-through experience by redesigning its drive-thru windows and fine tuning the information provided during the experience. McDonald’s also is using historical data (e.g., wait times during specific periods) to predict future demand patterns to optimize staffing.


Additionally, the company closely watches the data flow of in-store traffic, customer interactions, ordering patterns, point-of-sale data, and sensor data, among others, to optimize operations. McDonald’s used to share average results with individual stores, but later switched to trend analytics to provide better correlations and more clear and relevant information to improve individual store performance.


The quick-serve restaurant chain isn’t stopping there. To connect with younger, mobile app-using customers, McDonald’s is rolling out mobile ordering, curbside check-in, and delivery service in a partnership with UberEats. It’s also investing in touchscreen ordering kiosks, mobile charging docks, and digital payment options such as Apple Pay at some locations.


Structure your operations to amplify data

Both Starbucks and McDonald’s have built data management systems that integrate all forms of data across systems and applications at scale so they can make data-driven decisions. In each instance, the organization broke down barriers to new and innovative markets by using a higher level of information and leveraging that data in near real time. To do so meant having access to the most up-to-date information on customer preferences, products, services, and locations, as well as robust data management practices that leverage information when and where it’s needed.


Your organization doesn’t have to be as big as Starbucks or McDonald’s, nor do you have to throw out your legacy systems to become data-driven. But you do have to develop a strategy, make sure IT provides clean data, and embrace employee self-service. To get started, you should:


  • Develop a data vision and strategy: It’s essential to define a forward-looking data-driven strategy using clear and concise language stating what your business wants to accomplish. Being data-driven isn’t an end goal; harnessing data to make better decisions and improve specific operations is. This vision creates a platform that helps the organization work toward a common goal and the framework it can execute against. A typical strategy would use a phased approach, with interim goals and milestones. When properly developed and presented, the vision and strategy can also help bolster the importance of enterprise information, and a new data-driven culture starts to bud within the organization.


  • Create a single source of the truth: Data-driven organizations such as Starbucks and McDonald’s embrace the use of unfamiliar or previously unavailable data sources. They use unstructured, multi-structured, and external data sources. Organizations need to ingest, cleanse, and centralize all this information into a governed data repository, such as a data lake, that can then be monitored and maintained by IT, but also accessed via self-service tools. The net effect is to not only organize and qualify the massive volume of information, but also to increase the number of touchpoints where data can be used to make a difference.


  • Empower all employees with self-service: To drive businesses forward at today’s pace of change, everyone needs to have access to the data they need when they need it. Not everyone has a degree in data science, of course, so CIOs should provide easy-to-use, self-service data manipulation and analysis applications and tools to business users. CIOs also need to integrate intelligence into data management applications and workflows to make it easy for business users to leverage advanced technologies such as machine learning and natural language processing.


By integrating information in a way that makes data accessible to business users, while ensuring its quality and protection, companies can find new routes to market, remain competitive, and drive growth. In fact, being data-driven—i.e. gathering, processing, and analyzing data in real time as it flows through the enterprise—results in a 23 times greater likelihood of customer acquisition, a six times greater likelihood of customer retention, and a 19 times greater likelihood of profitability, according to a report from McKinsey Global Institute.


Those are pretty compelling reasons to put data at the heart of your business.

About the Author

Ashley Stirrup joined Talend in 2014 as CMO. In this role, Ashley is responsible for driving market leadership, global awareness, product management and demand generation. Prior to Talend, Ashley held a number of senior leadership positions in marketing and products at leading cloud and software companies, including ServiceSource, Taleo, Citrix and Siebel Systems.

Find Ashley at @astirrup