Insurance companies have long been leveraging data in order to predict potential risks and outcomes, value insurance plans, and inform customer interactions. Previously, this process relied heavily on internal information collected during member onboarding and a lot of manual work to put this information together into usable data sets. Today, data continues to drive insurance decisions but with improved tech and AI there is a much larger volume of information available and many different avenues that this information can be gathered from. In addition to data that can be retrieved internally about the consumer (zero and first party), there is data available on the consumer that can be collected by partner companies such as search engines and social platforms (second party data). There is also third party data made available by companies that gather and aggregate data from a variety of available sources.
Why insurers are investing in third party consumer data
In comparison to other data types, third party data has unparalleled breadth and scale. It is consistent (little to no gaps) and geographically stratified, meaning it covers a wide range of markets. At Manifold, our data is modelled down to the postal level and is available at any higher geographic level including custom geographies across Canada. Our structured, clean, and granular data can be integrated into risk assessment and pricing models or simply used for model validation to ensure your existing models deliver accurate results. Our data science team is always up for a discussion on how to leverage our products to ensure the best and most accurate output. Another upside to investing in third party consumer data is that it can be easily appended to existing or prospective client data in order to build detailed consumer profiles and allow for better targeting.
Better consumer targeting is becoming more important as the insurance industry is becoming increasingly competitive. The days where insurance companies were able to compete based on the strength of their insurance plans alone are long gone. At this day and age, customers expect transparency and exceptional experience and service throughout their membership lifecycle. Therefore now more than ever, it is important to take a customer focused approach and leverage consumer data to satisfy their craving for greater personalization. Taking this customer focused approach will improve ROI and reduce ineffective marketing spend by attracting the right clients, and building the trust of existing clients. The result? More happy and loyal long term clients.
Some useful insights for insurance from our data products
In addition to our comprehensive demographics and consumer behaviour data sets which can be leveraged for better understanding existing and potential insurance clients, we created several data products with information particularly relevant for the insurance industry.
Our new data products can be used to identify your best prospects, tailor communication and support actuarial decisions for many types of insurance, including health, life, auto, travel, and long term care or long term disability insurance.
| Data Product | Consumer Insurance Behaviour | Consumer Healthcare Patterns |
| Number of Variables | 300+ | 2000+ |
| Description | Learn the consumer’s knowledge, abilities and behaviour concerning their insurance. It has good coverage of different insurance related variables. | Gain a comprehensive picture of your consumers’ healthcare needs, health-related spending, healthcare patterns, and health conditions. |
*Click on the Data Product Title for more information
What kind of insights can be drawn from these data products?
Finding the risk level of existing and target clients. Determine a threshold for low, medium and high risk clients and find prospects or existing clients that meet those criteria. Our consumer healthcare patterns data set allows for more targeted health risk assessments. For example, you can find variables that may indicate the level of risk for getting into a car crash by
- Number of KM driven per year [Consumer Insurance Behaviour]
- Driving and Safety Behaviours such as driving while using a hands free device, talking or texting on a cell phone, feeling tired, under the influence of alcohol or other illicit substances [Consumer Healthcare Patterns].
Informing interest in preventative insurance plans. Find prospects and existing clients that can benefit from or would be interested in plans that include preventative care. Consumer Healthcare Patterns contains variables that help understand what kind of preventative care the prospect or existing client may benefit from. For example, the general health section of this data product answers the following relevant questions
- How does the consumer perceive their general health, mental health, life stress, work stress and oral health?
- How satisfied are they with their oral health? Or with their life in general?
- To what degree do specific health problems limit them? Health problems covered by this index include pain, cognition, emotion, mobility, hearing, vision, speech.
Informing on cost sensitivity. Both Consumer Insurance Behaviour and Consumer Healthcare Patterns have information that details the consumers’ cost sensitivity. This informs whether offering a pricier plan to a client is appropriate or simply frustrating for them. For example, consumers that agree with statements like
- When I buy products I am looking for convenience, not price [Consumer Insurance Behaviour]
- Avoided going to a dental appointment because of cost, barrier to improving health is that it’s too costly, stopped refilling prescription medication due to cost, had difficulty seeing a specialist, getting a non emergency surgery, getting routine or immediate care, or had other unmet healthcare needs due to cost [Consumer Healthcare Patterns].
Understanding market size and insurance switching patterns. Our Consumer Insurance Behaviour and Consumer Healthcare Patterns data contains variables that describe the type of insurance that clients or prospects are currently subscribed to such as:
- Private or group life insurance, private or group disability insurance, travel, home, auto, and mortgage insurance [Consumer Insurance Behaviour]
- The specific benefits that are included in the healthcare plans such as prescription meds, long term care costs, dental, home care services, eyeglasses/contacts, as well as who is covering that specific benefit (employer, government, private, etc.) [Consumer Healthcare Patterns]
Consumer Insurance Behaviour also has variables on those that switched insurance in the past two years. The likelihood of switching insurance is particularly useful since it can inform which clients should be checked in with more to ensure they are satisfied and avoid their switching. From our analysis of switching insurance patterns, we know it is more likely for people to switch insurance after a significant life event happens. Keep an eye out for our next post to learn more about how people change behaviours after significant life events!
Want to learn more about these data products? Interested in some of our other demographics and consumer behaviour data?