The Financial Services industry spends over $6 billion a year on data-related programs and over 90% of insurers have data and analytics initiatives under way.  

Once measured in terabytes (a thousand gigabytes), data volumes, even for mid-sized brokers, now often run to exabytes or more.

But it isnt just data volumes that are rising. The speed at which brokers receive data and must act on it has exploded, too.

Rather than collating data on a fixed frequency, to support monthly reporting for example, now they need to cope with a continuous flow of data from different places, in different formats, and respond to customer queries fast.  

In many brokerages, agents will tell you its difficult, if not impossible, to pull any kind of useful data from their systems, let alone interpret it. Principals cant see whats going on with their employees, employees cant see opportunities for growth, and customers are frustrated by having to jump through hoops to get basic information about their policies.

Data is one of the most important assets for any broker. In fact, effective data management is central to success for the forward-looking broker.  

What is data monetization?

Brokerages already collect data at every opportunity, whether its from website visitors, sales calls, or customer service logs. This data helps them assess risk, set policy prices, and answer customer queries, but its often forgotten after the policy is issued.  

However, brokers are missing a trick if they dont think about data as a strategic asset. The process of exploiting its value is referred to as data monetization.

Definitions of data monetization vary, but theres common agreement that its a continuum stretching from internal monetization, using data for measurable business performance improvements, to external monetization, creating a new revenue stream by selling data to third parties.

In this series of articles, we focus on internal data monetization.  

Three strategies to help brokers monetize their data  

1. Enhance customer experience

Customer expectations have never been higher meaning there is a demand on brokers to improve every aspect of the customer experience.  Those who do are rewarded with better customer satisfaction ratings, more referrals, higher revenue per customer, and lower churn.

Data management helps put customer experience at the center of the business. It gives you a better understanding of customer behavior when, how, and why they interact with the brokerage meaning you can offer a personalized service, preempt problems, and tailor products in response to changing needs.  

Not only that, but enabling self-service customer portals means customers get what they want when they want it.

2. Maximize revenue growth

By combining effective data collection with powerful analytics, its possible to calculate Customer Lifetime Value the value of the cash flows you expect to generate from a customer over the length of your relationship with them. This means you can spot under-performing accounts and prioritize customers for acquisition and retention. No one likes to waste time chasing business that isnt there or is low value.

Equally important, actionable intelligence turns knowledge drawn from purchasing histories, service requests, and other behavioral patterns into prompts for the sales team. This allows them to propose personalized recommendations during sales calls a far-reaching change from relying on historic, outdated information.

3. Improve business performance

Brokers spend more than half their day on administrative tasks, time that could be better spent on client service.

Data-gathering tools that track the actual time spent working on different tasks and automatically calculate the associated costs help identify inefficiencies where time and cost are being wasted on low-value activities that can be automated or removed.  Even simple tasks emails sent, calls made, claims started can add up to a sizeable impact on the bottom line.

And dashboards and automated reports let you monitor sales & marketing KPIs, such as quote-to-policy conversions, policies sold, and new enquiries, meaning you can decide if producers are as effective as they should be, or if marketing spend is producing a good return on investment.

Implementing a data monetization business model

Careful planning and a willingness to change how the organization thinks about and uses data means implementing data monetization is possible for any brokerage.  Here are the steps you should follow to build a successful data monetization framework:

Plan for success:

Set clear objectives, priorities, and timelines. Define metrics important to your business, such as increasing revenue for a line of business or reducing costs in an operations team, and build a plan around those. If you cant see the value, enthusiasm for implementing the change will wane quickly.

Treat data as you would any other asset:  

Data should be actively managed to realize its full potential. Appoint business leaders as data owners, which will make them responsible for data quality and for defining the business rules that decide whats collected and how its used.

Collect the right data and enrich it for greater value:

Control what you collect. Too much, and youll be swamped by a data tsunami and spend more time working out what to do with it than using it.

Additionally, enriching the data with third-party credit risk or marketing lists, for example, can make the data even more valuable.

Focus on creating actionable insights:

Uncovering the real value in data is like solving a complex puzzle: its only when each piece of data is joined with others does the outcome reveal itself.

Transactional data, while mundane when viewed alone, can help identify cross-sale opportunities when combined with buying patterns over several years or recent sales enquiries. This slice and dice analysis is where the real value of your data presents itself.

Organize to take advantage of data:

Moving to a data monetization business model requires change across the organization. Managers need to lead by example and make decisions based on data and KPIs. Operating procedures need to be updated to clarify new rules, and staff need to be given incentives to follow them.

Use technology to make the hard work easy:

The two main barriers to effective data management are not having the right technology and inaccessible data because its siloed, often in different locations and formats, meaning its difficult to find and use.

Fortunately, modern broker management systems take care of the technical complexity by integrating the different elements, meaning you can focus on using the outputs to improve the business.

Benefits of data monetization

Data monetization presents a real opportunity to brokers.  Consider Howden Broking Group, who sell specialist insurance products through 135 offices in 40 countries.

Operating across borders requires a common language and consistency of measurement for tracking and reporting. Until 2015, the company had multiple, outdated, systems running in parallel, meaning it was very difficult to get a view of performance across all aspects of the business.

It was like we were driving a car without a dashboard,says Shay Simkin, managing director of Howden in Israel. You pretty much knew where you were going and in what direction, but you didnt know your speed or if your tank was full.

The Novidea cloud-based solution replaced fragmented software systems with a single integrated view of customers, channels, and business lines.

Howden offices using the system can now manage the entire insurance distribution lifecycle, with visibility into all KPIs and each employees status relative to targets.

We hope this series of articles gives you a fast track on how to achieve the same benefits.