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Aug 31, 2022

How to “Insure” That Your Marketing Spend Targets the Right Customer

Rising costs due to inflation, supply chain disruptions and severe weather events are among several economic and natural events hitting the insurance sector hard. On one hand, passing along cost increases and risk to new or renewed customers in the form of premium hikes creates acquisition and retention challenges. On the other hand, for existing customers – particularly those with a policy through a multi-line insurer – fixed premiums prevent insurers from making up the difference when claims payouts surpass short-term financial forecasts.

According to a July report from PolicyGenius, goods and services in the U.S. increased 8.6 percent year-over-year between May 2021 and May 2022, with home insurance premiums increasing 12.1 percent in the same timeframe. Travelers attributes rising rates to several factors, among them an 18.6 percent increase in material goods for new residential construction, asphalt roofing materials up 16.3 percent, lumber and wood products up 6.2 percent, and 20 separate $1 billion or more loss events (in 2021).

Instability creates uncertainty, which is forcing insurance companies to be more strategic in distributing leads, working with underwriters and ultimately generating profitable policies. The mass advertising approach of the past is being phased out, replaced by tailored, data-driven marketing campaigns to both acquire and retain profitable customers.

Know Your Customer

Being data driven applies both to marketing to prospects and to retain existing customers. For prospects, it’s important to know everything there is to possibly know about an individual. If an insurer knew, for instance, that the prospect was making steep monthly payments on a high-end auto with traditionally expensive repairs, perhaps the insurer offers a high deductible plan or denies coverage outright.

For another example, consider a multi-line customer with combined auto and homeowner policies. If an insurer knew the household had children reaching driving age and had been searching for used cars, it could upsell the customer much more effectively. Conversely, a different marketing campaign might be in store if that same customer had just filed a claim for an extensive home repair.

Compiling as much first-party data on a prospect or customer as possible is the key to making sound decisions based not on a law of averages or an educated guess but on specific behaviors of an individual or household. Identity resolution is a foundational capability for generating data-driven insights and orchestrating a next-best action relevant for an individual in the context of the individual’s customer journey, either as a prospect or as an existing customer.

A Real-Time Element

Being relevant to a specific customer entails more than aggregating multiple data sources, it also contains a real-time element. More even than being aware of and reacting to various life stages, real-time entails moving with the customer through various channels in the context of an individual customer journey. When a prospect or customer appears online, contacts the call center, visits a branch, etc., an insurance company should know where that customer is in a customer journey – do they have an expiring contract, are they in the market for an annuity, have they recently filed a claim?

What the customer searches for online, for example, and attaching that online session to an identity graph is just as important to delivering consistent relevance as knowing the customer has teenage children about to start driving.

Knowing a full breadth of transactions and behaviors allows an insurer to carry on a consistent conversation with a prospect or customer over the course of a journey, and be more proactive in engaging with that customer with the most relevant information or content.

Identity Resolution Use Cases

Advanced identity resolution capabilities with Redpoint rg1 provides insurance companies with several key benefits:

  • Using a combination of deterministic (rule-based) and probabilistic (analytics-based) matching, advanced identity resolution minimizes or eliminates interacting with duplicate records and other waste.
  • Better understanding of a customer (household/entity) – Identity resolution in the building of a unified customer record is key to understanding channel preferences and behaviors of customers in order to target them more effectively.
  • Implementing controls – Frequency capping and suppression rules placed on a unified customer profile helps eliminate sending messages, offers or content that annoys or confuses customers.
  • Extending relationships to new devices and contexts – Identity resolution that brings in updated, real-time data ensures a customer record always reflects an up-to-date, complete profile of an individual/household/entity, allowing for consistent, personalized experiences across channels and devices, applied consistently and in line with customer expectations – online and offline.

Identity Resolution and Personalization  

Omnichannel personalization as an outcome of advanced identity resolution is becoming a competitive differentiator in the experience economy. Recent McKinsey research on the value of personalization found that 71 percent of customers expect a personalized customer experience, and 76 percent of customers become frustrated when brands fail to do this.

The value of personalization as it pertains to retention and customer loyalty underscores why data quality is a critical element of identity resolution, and why simply matching records is just the tip of the iceberg for resolving identities across all touchpoints, records, devices, channels and identifiers. Because inaccurate matching, overmatching or undermatching all result in the likelihood of introducing friction into a customer experience with irrelevant or unwanted offers or communications.

With a firm understanding of the importance of data quality, and perfecting data the moment data is ingested from multiple data sources, it becomes clear why identity resolution is a core component of a CDP. Many organizations mistakenly think of a CDP as primarily a data aggregation system meant to automate some personalization. The reality, though, is that a CDP is really only as good as its data quality processes – and when it tackles those data quality processes – in creating a complete, accurate golden record on the back of advanced identity resolution capabilities.

To learn more about how Redpoint can help provide you with the most precise view of every customer, and ultimately use a personal understanding to eliminate waste, deliver a personalized experience and drive revenue, click here.