By Karl Wirth, CEO, Evergage
There’s a common sentiment about big data – we’re drowning in it. Among marketers, some might also say there are so many tools to manage all the data that marketers are drowning in those as well.
In this “sink or swim” atmosphere, it’s not surprising that marketers can be overwhelmed by all the analytics tools and choices at their disposal to improve and manage campaign effectiveness. If the ultimate goal is not only staying afloat in the data but also realizing a lift in conversions and improved customer experiences, what’s the best way to approach analytics?
It would require several novels to cover this subject in appropriate detail – but, at a high level, marketers should look to accomplish the following activities when it comes to big data analytics:
- Measure and Improve Digital Experiences and Engagement
Marketers’ digital properties are the primary places of engagement with prospects and customers. And in the era of digital channels, the most basic form of monitoring and assessment is through Web analytics. Rightly so, a huge amount of effort goes into understanding how groups of customers interact with Web pages, flows, emails and mobile apps.
When it comes to collectively understanding digital audiences, you can use a combination of products ranging from well-known industry tools like Google Analytics to more specialized solutions like heat mapping and session replay services. Also, don’t forget about the analytics within your email provider, which can prove invaluable in optimizing newsletter and promotional communications.
While each tool serves a different purpose, they’re all designed to help marketers obtain a holistic view of their digital channels and, more specifically, what’s working/not working, where people are dropping off, and what pages or paths are converting. After all, you can’t improve what you don’t measure.
- Collect Customer Trends and Insights Across Channels
Whereas digital/Web analytics are focused on helping marketers understand and improve Web experiences, customer data warehouse and analytics initiatives center on helping marketers understand their customers. In addition to aggregating ever-expanding volumes of data from a variety of sources, customer analytics can also encompass a combination of segmentation and predictive tools that help companies gain deep insight into how customer attributes and behaviors impact business goals.
If your company has the resources and expertise, you can leverage modern open source database technologies like Hadoop, Cassandra and MongoDB to build data clusters to capture and process different sources and types of customer data. But if you don’t have an IT staff or team of data scientists at your disposal, there a number of vendors with proprietary solutions that can help aggregate, manage and process customer information.
Getting the most out of customer analytics requires a multi-departmental commitment. If implemented correctly and managed effectively, company executives can obtain enormous insights about their customers – or segments of customers – which can be used to spot trends, forecast demands and make informed business decisions.
- Understand and Respond to Individuals
Another form of big data analytics is real-time engagement, which can move companies to what some have referred to as the “Holy Grail” of digital marketing – 1:1 personalization. Real-time engagement builds on both digital/Web analytics and customer analytics, but rather than analyzing traffic patterns as a whole or behaviors among groups of people, real-time engagement leverages the same data to enable marketers to understand and respond to people at the individual level.
Over the years, companies have attempted to develop real-time engagement tools in-house or piece them together using best-of-breed solutions, with varying degrees of success. More recently, though, solutions have emerged that not only combine individual Web and behavioral data, but also make this information available to marketers – not just IT or data scientists.
Real-time engagement enables marketers to harness big data to tailor the digital experience to individual customers in real time. This class of analytics puts big data to use by providing personalized experiences and communications based on a deep understanding of each customer’s behavior.
Successfully Wading Through the Sea of Analytics Tools
Each of these types of big data analytics has its place, and all are needed. To stay afloat – and swim successfully – in the sea of analytics tools, marketers need to understand the types and classes of tools at their disposal, as well as the benefits they bring. Armed with that knowledge, they can further improve customer experiences – with the ability to interpret and act on data, deeply understand patterns and behaviors within their customer base, and respond in real time in the most personally relevant way.