Big Data is a hot topic and one that email marketers are struggling with as far as defining goals and determining approaches and practices. As Angelo Racoma writes, citing a Yesmail and Infogroup survey, “Marketers love Big Data, but don’t know how to use it.”
Similarly, Tim Suther, chief marketing and strategy officer at Acxiom, argues that, “There is so much data and so many options regarding what to collect and how to analyze it that marketers don’t know where to start.”
For what purposes can email marketers harness Big Data, and how should they go about doing it? In general, there are five major ways that email marketers can benefit from Big Data:
- Customer Profiles and Personas – The information required to understand the tastes, interests and personalities of prospects can be obtained from Big Data sources like social media, website visits and shopping histories. This information can be used to build customer profiles and buyer personas. Missing information can be obtained from demographic appending services.
- Segmentation – The profiling data that is collected for prospects can be used to categorize and segment them for targeted email campaigns. The relevancy of email messaging can be optimized for each segment, and the content tailored and personalized to achieve higher engagement and conversion rates.
- Real-Time Targeting and Messaging – Big Data streams can be monitored, and triggered emails delivered, in response to the real-time activities, queries, and expressed interests of prospects. Triggered email systems can be put in place that will dynamically populate the emails with personalized messaging.
- Market and Competitive Intelligence – Intelligence can be gleaned from Big Data streams to understand trends, gain insight into where your brand stands in the marketplace, and learn how competitors are conducting campaigns. Email campaigns can be formulated and refined based on gathered intelligence that is used to guide your approach to whom to target, how to target and where to target.
- Predictive Analytics – Although there is controversy surrounding the value of predicting behavior based on historical data, there are companies that have reported success in this area. Predictive analytics typically requires the specialized talents of quants and data scientists, as well as investment in data warehouses and analytical tools. More affordable SaaS tools also are becoming available.
Use number 5 is a sticking point for many marketers. Big data is often associated with the crunching of huge data sets to find patterns for predictive purposes, and this is where many marketers feel they lack the skill and resources, which is causing them to hold back.
There are a number of commentators who question the value of predictive analytics based on large data sets operating on historical data. Among them is Mark Hancock, strategy director at Lida, who argues that “marketing professionals are mistaken to think that big data should rule over creative intuition, despite what vendors say.”
Jon Maddison, VP at Lyris, on the other hand, sees a use for Big Data for personalization and more relevant messaging, arguing that the more you learn about each individual customer and become capable of speaking with them in a personalized manner, the more your total data set grows, which in turn helps you to spot aggregate patterns. This, says Maddison, “enables you to plug the gaps in your data and target customers with products and services that someone with a similar profile has bought in the past.”
As marketing strategist Debra Ellis points out, even companies without a team of statisticians can extract useful information from the data stream to increase sales by monitoring customer behavior and activity and sending customized emails in response.
Likewise, Vida Tamoshunas of Sigma Marketing Group counsels marketers not to worry so much about how big your data is, but to ask yourself whether you are extracting enough value from it.
As with email marketing in general, top-tier marketers will achieve better results through the diligent application of leading-edge approaches coupled with best practices. In today’s world of segmentation, triggering, and big data, best practices include the use of data appending to acquire missing contact information and complete customer profiles, as well as regular email hygiene to achieve optimal data quality.
Analyze your email list today with a free validation report from TowerData. Click here to begin.
Photo Credit: caribb