The number of insurance agencies in the US has been on the decline, as have the number of agents. A key issue for insurers today is not only just retaining agents, but also making them both happy and successful. Engaging them with predictive and adaptive analytics strategies can help with this.
When people think about adaptive and predictive analytics, what comes to mind mostly is the direct sale, through a call center or the Internet. This makes sense – it’s the closest to retail sales, it’s something that everyone understands and can relate to. It’s also “sexy”, because it’s very simple to show and understand the benefits. But people don’t stop to think about how analytics can be used to help manage the agent, and to help make the agent both happy and successful.
Granted, since an insurer owns the desktop for captive agents, there are more options for how analytics can be leveraged with captive agents, but there is a tremendous amount of room for improvement with independent agents also.
When insurers begin to plan their analytics strategies for agents, they have to have a good sense for what is trying to be achieved with advanced analytics, where agents will want to opt in and opt out, and what applies internally from the perspective of agent management. A key element for success is aligning the strategy for using analytics to match the business strategies that the insured is trying to execute. Intuitively, you would think that this would be the case but misalignment is pretty common.
The other key issue: analytics need to be actionable. Analytics is no longer just reporting; it should drive recommendations that agents can act on and systems that can execute both workflow and tasks to support analytic-driven decisioning and recommendations.
There are several common scenarios where analytics can be leveraged to improve agent production and agent satisfaction.
- Coverage recommendations – whether during the new business application process, renewal or mid-term transactions, analytics should constantly be reviewing transactions to determine what the optimal level of coverage and what product mix would be the best fit for the client. Based upon the demographics of the client, the market, the economy, there is an optimal mix of products and coverage that best fits each client. Analytics can do that level of analysis, taking into account client value, recently closed transactions, etc. and can recommend what this optimal blend will be to the agents. Agents can disregard recommendations but at least they see what product mix has been selling successfully in the market, and why.
- Book of Business Lead Generation – an insurer never has full visibility into the full book of business that the agent is writing but it can see the book of business that the agent is writing with the insurer. Analytics can review that book of business and, based upon coverage recommendations described above and the characteristics of the agent’s book, analytics can make recommendations on where the agent has cross and up-sell opportunities. These opportunities can launch tasks and workflows that provide product descriptions, sales scenarios, best practices and material that the agent can leverage when perusing identified opportunities.
- New Product Launch – where book of business recommendations become extremely useful is when the insurer launches a new product in the market, or changes existing products. As part of a launch process, the insurer can run the new product parameters against an agent’s book of business with the insured and highlight account where the new product would be more likely to be successful. This not only helps the agent generate new revenue but underscores how to position a new, and possibly not fully understood, product.
- Client Retention – insurers are constantly gathering information on clients, from application information to third party data to transaction histories and claims. This data can be leveraged to identify when a client may be more likely to become a retention risk. As the insurer runs analytics on clients, when it identifies that a client may be at risk, for whatever reason, the insurer can share that information with the agent, including best practices for retaining the client. This can also be tied into specific transactions made by the client where it becomes apparent they are about to terminate a policy or product. Transaction systems should be tied into analytics to determine what the best practice would be to retain the client and then initiate the appropriate response, which could be executed across channels, platforms, systems, workflow etc depending upon the circumstance.
- Agent Management – regardless of what type of agency structure an insurer supports – independent or exclusive – there is a relationship manager who manages the agent. Where this manager sits varies by insurer, but the role exists somewhere. These Relationship Managers are responsible for setting sales budgets, educating the agent on the insurer’s products, compliance with procedures, etc. Analytics, usually starting with a dashboard and then extending into processes, can be leveraged to give relationship managers maximum visibility into agent performance. This includes being identified when something is changing in an agency’s book of business (signaling a possible move), to when an agent might need some help or identifying where an agent might be missing out on new product opportunities. The goal with agency management is not meant to be punitive but to work with the agent to make them successful and optimize the Relationship Managers time. This can extend to items such as managing when agency visits need to occur based upon agent performance and other company guidelines. Agents, similar to clients, can be associated with an “Agency Lifetime Value” (ALV), which provides a score for how valuable an agent is to the insurer. Leveraging this metric, insurers can determine how much to invest in an agent and trend the ALV over time, another powerful tool for agency relationship management.
- Best Practice Recommendations – throughout the entire insurance lifecycle, best practice recommendations can be made to agents, underwriters dealing with agents and agency relationship managers. Obviously, where the insurer is supporting exclusive agents, how specific or mandatory a best practice should be can vary by agent experience and company strategy. When working with independent agents, insurers need to be very careful when offering best practices so that they’re not viewed as too intrusive, but rather as guidelines that agents can leverage (or ignore), but are based upon what the insurer is seeing across its larger books of business as being successful.
With the shrinking agency market, insurers want to be seen as proactive partners with the agent, partners that are trying to make the job of selling insurance easier. The benefit to the insurer is longer agent relationships with high-quality, profitable books of business.