3 Ways Data-driven Insights Boost Insurance Agent Performance

by  Sharone Volk  |  30 Mar 2017

Data is extremely powerful and has the ability to completely upend the way insurance agents and brokers track and improve their performance. 

It can do this in two key ways:

  1. By improving the delivery of a personalized customer experience, which according to McKinsey is the key "growth engine" for middle-man businesses, such as insurance distribution.
  2. By enabling management to make better business decisions, such as setting appropriate pricing and choosing where to invest resources for the maximum possible return.

Together, these can make a significant impact on the bottom line.

The intrinsic value of data, however, is virtually nil. Until it is analyzed, data is nothing more than a repository of information.

In order to turn data into actionable insights, businesses should adopt strategies that leverage it to its fullest potential.

The following are three ways data-driven insights boost insurance agent performance:

1. Customer profitability tracking

In order to ensure that agents are investing their time wisely (on the highest yielding accounts), managers should ensure that adequate systems are in place to track time expenditure.

Time-tracking software, which can exist both as stand-alone software or as part of a modular end-to-end platform, offers the intrinsic value of giving management an overview of where their agents' time is being invested.

Even though account profitability is (and has always been) a metric of fundamental importance for those in customer-facing businesses, it was not until the advent of such software that assessing an account's profitability was even a feasible task. Modern insurance agents should take advantage of their ability to access the data to do so, and use its insights to optimize internal resource allocation.

2. Predictive analytics

If agents don't derive information from their customer data, important tranches of business intelligence information - which can contain many cues for action - risk being lost.

As Philip Ellis, chief executive officer at Willis Strategic Group Consulting observes, insurance agents and brokers are increasingly leveraging advanced tools such as predictive analytics to bolster their business performance.

Predictive analytics works by extrapolating likely user behavior based on known purchasing patterns, and therefore allows agents to use cross-selling and up-selling strategies that are mathematically known to have a statistically likely chance of success.

These are often pairings which may not be obvious to the agents themselves due to the existence of silos (according to coverage type) within many agencies. A policy from the general book, for instance, could well be of interest to a consumer looking to purchase life insurance, but the cross-sell opportunity may not be obvious to agents dealing exclusively with either policy type.

In addition to its role in increasing account revenue, predictive analytics can be leveraged by brokers to mine customer data and make accurate observations about claims histories and likely usage patterns. This, in turn, allows brokers to offer these customers individually-tailored customer experiences by bringing features to their attention (such as the ability to make mobile claims) that they know will probably be found to be beneficial. In this way, agents/brokers can avoid causing frustration by 'mis-selling' customers irrelevant services.

3. Total transparency and 360-degree visibility

Analytics systems must offer total transparency and visibility in order to be useful for guiding business decisions.

In addition to displaying information from across the business (such as information from different business divisions, geographies, and focus verticals), transparency about the origins and methodologies used to extract business data are vital for that data being tackled by the expertise of the crowd. In the case of insurance brokers, that 'crowd' of experts could be a brokerage's senior leadership who might want to argue about the exact derivation of information being used for decision-making, as well as challenge any assumptions used in its compilation.

Serious data analytics is a holistic discipline that involves every customer touch-point from call center contact through to policy purchase renewal. Ensuring full transparency and dissemination throughout the company of both the outcome of this process and the means of achieving it, is a must.

In Conclusion

Data delivers actionable insights which agents can use in these three ways to maximize its fullest potential.

Novidea’s data-driven insurance agency management platform provides real-time visibility, intelligence and actionable insights, resulting in increased sales, profitability and productivity.

 

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