4 Steps to Incorporate Big Data Into Insurance Marketing

Marketers across all industries struggle to define and derive business benefit from big data. A recent survey by Neolane and the Direct Marketing Association (DMA) found that many marketers are ill-equipped to handle the influx of growing data and are behind in planning for tremendous growth. Specifically, 60% of those surveyed noted that they do not currently have or are unsure if their company has a specific strategy for handling its challenges — because big data is still an emerging concept, it’s not uncommon to see differing perspectives about what it is and what it means.

Big data is all about the customer — looking at the volume, velocity and variety of customer data entering the organization. If analyzed quickly and effectively, that data can be used to make more informed business decisions resulting in more profitable customer engagement and relationships. In insurance marketing, because most firms offer a variety of products – from life and health insurance to home and travel insurance – and different contract types, this means customers’ relationships with the company can differ drastically.

While insurance marketers have long used data to segment and target customers, analyzing and acting on this data offers even more. It offers the potential to target customers with much more sophistication than mere segmentation, as well as the opportunity to demonstrate a detailed understanding of the customer and market to each as an individual. When this potential is realized, organizations see engaged customers, improved trust and loyalty, heightened revenues and improved return on marketing investment.

Getting started

The big data conversation becomes more tangible when framed around the explosion of customer data, transactional data, marketing communications, channel interactions, and behaviors. Until recently however, customer data had to be analyzed in ‘queries,’ using traditional database tools which often took days to process even snippets of history, even then delivering only approximated answers to fairly broad questions.

Today though, business users can access analysis of massive data volumes in real-time. Using predictive modeling tools and a conversational marketing software platform, marketers can automatically generate one-to-one personalized messages almost instantaneously. These can be delivered to millions of customers in minutes, or presented to a customer just as they are interacting with you, such as over the web or engaging with your call center.

Questions and challenges

To win from a big data investment, marketers need to first be certain of their business case. Many organizations simply collect everything in costly data centers with no idea how to make use of it all. In general, marketers need to ask the following questions before embarking on a big data initiative:

• What are the marketing goals?
• How will data be captured from multiple entry channels?
• How will legacy data be incorporated?
• What about data quality and matching?
• How will unstructured data be dealt with, such as Tweets, blogs, Facebook posts and the text, symbols and html links they might contain?
• How will on-going insights be updated, delivered and shared?
• How will sensitive customer data be handled, along with legal or ethical issues?
• What skill sets will be required to take advantage of Big Data – both to analyze it and to translate the analysis into action?

All of these things are important to consider in order to ensure the success of big data-driven marketing efforts.

First steps

To get started, marketers are not required to be experts in this field. Here are some recommendations for leveraging big data now, while allowing for development in the future:

• Collect meaningful customer data from a variety of sources. It will form the basis for future analysis.
• Link data to metrics developed for measuring marketing performance. It is important to define which data is critical to measuring your internal marketing ROI.
• Share data across the organization, linking datasets together at the customer level, allowing for a more comprehensive view of customer behavior.
• Utilize shared data to more effectively target and personalize marketing efforts. Conversational marketing platforms excel in applying business rules optimize offers.

Big data initiatives have the potential to open doors to improved product development, communication strategies, customer satisfaction, customer service management, marketing mix optimization, offer optimization, channel spend and more. The possibilities do seem endless, but for the insurance industry, the first part is simply starting the journey.

About the author: Kristin Hambelton is vice president of marketing at Neolane, responsible for the company's market and brand strategy and operations including corporate communications, demand generation, product and partner marketing, and digital marketing including search and social media. Follow her on Twitter: @KMHambelton.