Industry Voice: Powering customer centricity through data analytics
Jason Keck, Co-Founder and CEO of Broker Buddha, on leveraging customer databases, artificial intelligence algorithms, and driving customer satisfaction
Did you know that it costs seven to nine times more for an insurance agency to attract a new customer than to retain one? So, in order to succeed, it’s essential that agencies find customers… and keep them.
While traditional blanket marketing approaches may have worked in the past, the key to success now lies in customer centricity: placing the individual policyholder at the heart of every decision.
One crucial customer-centric strategy for agencies is to leverage their customer databases to improve the customer experience. By delving into the wealth of information they possess, agencies can unlock a deeper understanding of their customer base, unveil hidden segments with unique needs and preferences, and angle their business to fulfil these.
Here I explore how insurance agencies can harness data analytics to become customer-centric organisations poised for success in the ever-evolving market.
Discovering customer segments through data analytics
Insurance agencies have historically relied on conventional methods like customer surveys to understand their customer base for decades. While these methods have their place, they often need more nuance and depth to truly grasp today’s insurance consumers’ diverse needs and behaviours. Fortunately, the vast amount of data that agencies collect presents a golden opportunity to unearth customer segments and power customer centricity.
Agencies sit on data goldmines stored across various repositories. For example, agencies can tap into their internal data on policy details, demographic information, and exposure information and combine them with external sources, like socioeconomic trends and online behaviour, to paint a broad and holistic picture of their customers. Once they consolidate this data, they can clean and organise it to ensure its accuracy and usefulness for analysis.
Given the complexity of analysing massive datasets, agencies often partner with third-party vendors specialising in artificial intelligence (AI) and machine learning (ML) tools. AI/ML algorithms can identify and classify customer segmentation beyond basic demographics, including specific criteria such as risk profiles, purchase patterns, and insurance preferences, uncovering hidden patterns in previously unknown customer segments.
For instance, AI and ML algorithms could unveil low-risk drivers, claims-prone customers, and potential high value customers.
One crucial customer-centric strategy for agencies is to leverage their customer databases to improve the customer experience
Many leading customer relationship management (CRM) platforms incorporate AI features like data cleansing and normalisation, customer segmentation, and next-best-action recommendations to help identify these insights. CRMs that offer these features include Salesforce Einstein AI, Oracle CX Unity with Oracle Marketing Cloud AI, and Microsoft Dynamics 365 Customer Insights.
Organise your agency around discovered segments
After identifying customer segments through their data, agencies can now organise their staff, expertise, and services around these.
One of the best ways agencies can segment their commercial customers is through industry verticals, such as retail, construction, and manufacturing.
For example, a construction company has different insurance needs from a software development firm. Segmenting by industry allows agencies to specialise in coverage addressing industry-specific risks and regulations. This expertise translates into better advice, more comprehensive policies, and, ultimately, greater peace of mind.
In addition, being aware of where the largest proportion of your customer base lives and being in the same time zone or local region improves efficiency, as there is no delay in communication. Agents residing and operating within the same geographic region as their clients are also more inclined to grasp the local intricacies, regulations, and obstacles encountered by their clients.
For example, a farmer in Montana needs to adjust their automotive insurance policy after purchasing a new farm vehicle used primarily for work-related purposes. Local agents, particularly those specialising in agriculture, are more likely to be aware of the typical usage patterns of farm vehicles and can tailor coverage options accordingly.
Grouping customers according to risk profiles is another option, as it personalises premiums, risk management strategies, and loss prevention offerings. Segmenting this way allows agencies to create tiered coverage options and pricing models, ensuring high-risk businesses pay a fair rate without penalising lower-risk companies within the same segment.
McKinsey & Company research shows that businesses that tailor their offerings to customer segments earn 10–15% more revenue than those that fail to personalise their messaging.
Once agencies have identified their customer segments, determining how to approach them is essential. For example, an agency would allocate resources differently for an established segment than they would for a growing segment. This ensures that they create the best customer experience based on the needs of the segment.
Strengthening relationships and driving customer satisfaction
Once agencies have identified and grouped their customer segments, they can start powering a customer centric approach with this new wealth of data.
One of the key benefits of segmentation is targeted communication. Agencies can ditch the generic, one-size-fits-all approach and start crafting personalised messaging, marketing campaigns and customer service interactions that resonate with each segment. This could involve tailoring email content, website messaging, and
even call scripts to address each group’s unique concerns and interests.
Agencies can also focus on segment-specific marketing campaigns, ensuring customers only receive information and offers relevant to their needs. This targeted approach reduces information overload and increases customer engagement.
Another advantage for agencies is offering an omnichannel experience. Customers today expect a seamless journey across all touch points, from online portals to mobile apps to in-person interactions. Data analytics can help agencies understand how different segments prefer to interact with the agency, allowing them to optimise each channel accordingly.
A 2023 McKinsey survey found that while life insurance customers interact more through agents, websites are more popular among property and casualty (P&C) customers. So, knowing each segment’s specific concerns and communication preferences empowers customer service representatives to provide more personalised and efficient assistance. This customised approach fosters trust and builds stronger relationships with customers.
Once agencies have identified their customer segments, determining how to approach them is essential
In conclusion, data analytics isn’t just about numbers; it’s about unlocking the human element within customer data. This journey, outlined through unveiling customer segments, reorganising around customer groups, and delivering exceptional customer experiences, empowers agencies to transform from one-size-fits-all providers to trusted partners for each unique customer group.