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Big Data: Insurance Companies Ask What It Is Good For

Acxiom Last Updated June 12th, 2020
Big Data: Insurance Companies Ask What It Is Good For

Insurance companies are renowned for being conservative. Conservative in underwriting. Conservative in marketing. Conservative in financial management. So it’s fascinating to us at Acxiom just how quickly big data has taken this industry by storm.
Almost all of our clients are inquiring about and/or experimenting with big data platforms. And often without the remotest notion of how these will add to the bottom line. Don’t get me wrong, we applaud the industry for taking the leap into big data science. And while we see many clients struggling to figure out how to measure business impact, we strongly believe that now is the time to double-down. Now is also a perfect time to share our perspective, one that should help everyone realize the elusive financial and business impacts we all seek.

Before we get started, some context around big data:

What big data is NOT:

• A substitute for customer or prospect database
• A really cool IT project
• The answer to all your data analytics challenges
• A silver bullet for transforming business performance
• A fad
• Cheap
• Easy

What big data IS:

• Transformative (when done right)
• An efficient way to manage extremely large, complex data – especially unstructured
• Valuable when focused on solving a business problem
• A major cross-functional corporate initiative

As mentioned above, big data environments are not a replacement for traditional marketing databases. Rather, the platforms excel when used for extremely large data sets that often include unstructured elements. Examples include weather data, transaction history, website clickstream data, contact center details, social media posts, etc. Generally, these sources of data can be characterized by velocity (ie. batch vs. real time) as well as variety and volume (structure vs. unstructured). The following matrix provides a simple way to categorize sample data flows. MT big data graphic

Now that we have a better idea of what big data is and isn’t, the question is: where do we start? There is literally an infinite amount of data that can be on-boarded into a big data environment.

MT insurance MM heat map

Channeling our Marketing Maturity Model can provide relevant guidance in helping firms prioritize data analytics projects using their big data environment. As the table above demonstrates, the average insurance company scores very highly in categories in which they are regulated by law or statute, such as Privacy and Compliance or Information Governance. Unfortunately, insurance providers are weaker in marketing competencies that impact the customer experience, such as Lifecycle Management and Understanding Consumer Preferences.

Focusing our efforts on improving the customer experience is an important first step as it creates the strategic imperative that should drive ongoing efforts. Moreover, it provides specific guidance as firms develop specific big data project plans. The following guidelines will help hone efforts in big data:

  •  Objectives & Outcomes – must be clear, concise and measurable
  • Capability, Competence & Capacity – dedicated resources and time must be applied to solve challenging problems
  • Data, Delivery & Devices – access to the right data must be ensured (both via technology and in a privacy-compliant manner)
  • Insights, Implementation & Inspiration – be creative and focus on fresh hypotheses
  • Value to firm, customer & staff – project outcomes must provide quantifiable value to all 3 constituencies

The big data journey is just beginning. There will almost definitely be bumps along the way. So put your seatbelt on and enjoy the ride because this is setting up to be one of the most interesting periods in the history of our industry!