Everything You Need to Know about MarTech for Insurance Companies

Everything You Need to Know about MarTech for Insurance Companies

Today's insurance customers are moving targets for the marketing professionals who need to reach them. With increasingly competitive markets, marketers need sophisticated tools to learn more about consumers and make the best decisions about how to reach them.

Consumers research and shop online today more than ever before. Insurance companies and agents have a great opportunity to benefit from many choices they can make about the platforms they will use to connect with consumers. In addition, this technology has improved immensely over the past few years.

People who are involved in any aspect of insurance marketing should understand the different science and technology platforms that insurance marketers can make use of today and in the near future.

The MarTech Panel

A four-person panel of digital marketing executives contributed to a very insightful discussion about MarTech (a.k.a. marketing technology) at InsureTech Connect 2016:

The panel members included:

  • Frank Kasimov, co-founder of Insurance Revenu
  • Josh Reznick, founder and CEO of Datalot
  • Ross Shanken, founder and CEO of Jornaya
  • Steve Yi, co-founder and CEO of MediaAlpha

Each of the four panel members introduced their own particular niches in the MarTech industry:

  • Insurance Revenue provides a marketplace for online insurance leads, phone calls, and website clicks.
  • Datalot works to streamline and consolidate marketing channels from internet searches to online lead gathering to actual calls to agents.
  • Jornaya has constructed an online platform to provide consumer insights about in all stages of the buyer's journey to help marketers optimize each step in their campaigns.
  • MediaAlpha builds and maintains programmatic buying and selling platforms for a variety of different industries , including insurance.

How Marketing Technology Advances Benefit Insurers

Typically, consumers would fill out some sort of query form to generate a lead, and then that lead would be brokered to lead buyers. After that, the consumer's information would be sent off to an entirely different marketing channel. Everybody suffered from a disconnect between the original publisher and the eventual lead buyer. Nobody knew if the advertiser could deliver what the consumer thought he or she was promised.

Consider some ways that advances in MarTech can improve this model:

  • With the rise of mobile devices, it has become much more natural to move from a web search for insurance products straight to a phone call.
  • The old model left gaps in both the lead gatherer's and the eventual lead buyer's understanding of the consumer's intent.
  • New technology can give marketers insight about different stages in the buyer's journey. For example, marketers can learn if specific buyers are ready to buy or just shopping around.

On one side of the equation are publishers using multiple marketing channels like social, search, and email. On the other side are media buyers (insurance carriers) who use their own underwriting metrics, conversion metrics, as well as 3rd party data providers to determine the value of a lead.

One challenge that insurance marketers have had with media buying has been a lack of transparency in the space. Sadly, the insurance vertical has appeared to lag behind other verticals. This made it difficult for media buyers to really understand what they were purchasing. If a company has existing processes that already work, they may not care to change their own systems to conform with traffic they are paying for.

So how do you optimize thousands of publishers each running multiple campaigns and hundreds of buyers with their own preferences? At Insurance Revenue, they apply machine-learning to the problem, setting up feedback-loops on the buyers to discover which sources they liked. Over time, it has illuminated which sources and/or campaigns performed best for certain buyers.

Furthermore, the data is applied to optimize the distribution tree in order to send a lead to the best-fitting buyer, who is most likely to buy, rather than the highest bidder. In this way, machine-learning is a mechanism for generating subjectively high-quality leads.

The Future of MarTech

Insurance companies spend a lot of money on traditional media. But some companies emerging in insurtech will be able to save insurance carriers money by helping them to connect with potential customers in less expensive ways. For example, much of the money spent on TV advertising is lost on millennials, who are more likely use streaming services to bypass ads altogether.

Only now, has media buying for insurance begun to catch up to other industries. Programmatic buying technologies can offer insurance media buyers a lot more information about their audience, like how qualified the leads are and where the consumer stands in their buyer's journey.

This better understanding of each individual consumer helps marketers offer those individuals what they are truly searching for at the appropriate time. Insurers save money by connecting with consumers that they can serve. Customers have a better experience too because they won't be deluded with information they can't use. Useful MarTech can help insurers enjoy better returns on their marketing dollars and improve the industry's reputation with consumers.


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