Best Practices for Utilizing Predictive Analytics in Insurance Sales

At its core, using predictive analytics in insurance sales means leveraging statistics, historical data, and machine learning to glean information about insurance trends and sales outcomes. 

In short, predictive analytics takes the guesswork out of insurance sales prospecting. Data-driven insights can reshape your prospecting efforts, increase sales engagement, and help you retain the customers you worked so hard to get. 

We’re sharing 5 best practices for using predictive analytics in insurance sales. We’ll wrap up with a couple of success stories.

Shortcuts:

Understanding Predictive Analytics in the Insurance Industry

• Why Are Predictive Analytics Important in Insurance Sales?
• Leveraging Predictive Analytics in Insurance Sales: Core Benefits

Best Practice #1: Establish Clear, Sales-Driven Objectives

• Figuring Cost Per Acquisition

Best Practice #2: Use High-Quality, Relevant Data

Best Practice #3: Segment Leads More Strategically

• Utilizing Predictive Modeling
• Ways to Segment Leads
• Tailoring Outreach Efforts

Best Practice #4: Personalize Outreach and Timing

Best Practice #5: Track, Monitor, and Refine

Leveraging Screen-Sharing: Reeling in the Sale While the Interaction is Hot!

• Salesgenie
• Bee Digital

Predictive Analytics: An Essential Tool in Insurance Sales

Understanding Predictive Analytics in the Insurance Industry

Broadly speaking, insurance products have changed little over the last century. Insurance companies have tweaked policy wording, but the basic policies are much the same as they’ve always been. 

What has changed dramatically is how insurance salespeople sell insurance. Virtual selling and predictive analytics have become the norm. 

As the insurance industry embraces technology, predictive analytics plays a central role in insurance sales, as it helps to predict insurance sales trends. 

Why Are Predictive Analytics Important in Insurance Sales?

A key reason predictive analytics is important in insurance sales is that it identifies patterns. 

Patterns tend to repeat. Repetition helps predict outcomes. 

Predictive analytics can also indicate patterns changes. That’s something that can help you switch gears in your marketing strategy earlier in the sales process. 

Predictive analytics can help you create data-driven sales strategies in the coming months and years. 

Here’s how:

• Near future sales:  Assists with upcoming expiration dates and cold-calling
• Distant future sales: Assists with understanding broader insurance trends, like customer behavior and buyer trends

Overall, predictive analytics keeps you in the loop of the type of insurance products consumers are likely to buy at any given time. That’s valuable insight for today’s insurance agents, compared with the old sales tactics of the non-digital age. 

Leveraging Predictive Analytics in Insurance Sales: Core Benefits

Here’s a look at the core benefits you can expect when you leverage predictive analytics:

• More accurate lead segmentation
• Improved cross-sell/upsell potential
• Higher conversion rate
• Higher retention rate
• Less wasted time on cold leads
• Informed decision-making
• Improved resource allocation
• Long-term growth and profitability

As you can see, while you’ll need to put in some time and effort on the front end, you’ll typically see the fruits of your labor on the back end. 

Now, let’s get into the 5 best practices for utilizing predictive analytics in insurance sales. 

Best Practice #1: Establish Clear, Sales-Driven Objectives

You probably already established monthly and annual sales goals. The key to optimizing sales is to align your sales and analytics goals. 

For example, your sales goals may include:

• Improving your closing rate
• Increasing your sales activities
• Increasing the sales growth rate
• Increasing the average sales size
• Increasing overall revenue

To accomplish this, you decide on the following analytics goals:

• Improving lead quality
• Improving timing of callbacks
• Improving average commissions
• Shortening your sales cycle
• Decreasing your cost per acquisition (CPA)

Figuring Cost Per Acquisition

You can generate more revenue by paying attention to your CPA rate. 

The formula for CPA is:

Total campaign cost ÷ number of acquisitions = cost per acquisition

As an example, if you allocated $10,000 for a marketing campaign that gave you 100 new customers, the CPA would be $100 for each lead. 

Let’s plug the numbers into the formula:

$10,000 ÷ 100 = $100

Remember to set specific, measurable goals. For example, you may set your CPA at a specific dollar amount or shorten your sales cycle from six calls to four. 

Sales managers can also use these metrics to highlight areas for improvement in teams and individuals. Data can also be used to create effective sales incentive programs.

Best Practice #2: Use High-Quality, Relevant Data

Whenever you use data, you need to be sure that it’s trustworthy. Poor-quality data that is irrelevant to your purpose is useless. 

The best data for sales is clean data. Clean data means:

• Error-free
• Consistent
• Unduplicated
• Accurate
• Complete
• Reliable

Why is it so important to use clean data? 

• Efficiency: Reduces wasted time on duplicate and cold leads
• Personalization: Allows you to accurately personalize communications
• Targeting: Helps narrow customer segments
• Insights: Identifies customer buying behavior
• Costs: Reduces marketing costs and improves ROI
• Compliance: Ensures compliance with insurance regulations

Unclean, inaccurate data will produce misinformation, which often leads to poor marketing decisions and poor results. 

Implementing multiple strategies, along with your CRM records, policy histories, purchasing patterns, and digital engagement data, gives you more accurate data than your CRM or memory alone.

Best Practice #3: Segment Leads More Strategically

When you have a strategic plan for segmenting teams, you can focus your energy on areas that will produce the best results. 

Utilizing Predictive Modeling

Predictive modeling is taking the data you’ve collected and using it to forecast whether certain leads or lead segments will convert.

It allows you to score leads based on the customer’s intent and the likelihood that they’ll buy. 

To score leads, give extra points for customers who engage, such as visiting a landing page or responding to a social media ad. 

Take points away for negative actions, such as unsubscribing from emails or text messages.  

Lastly, set point values for hot, warm, and cold leads, and pursue them in that order. 

Predictive modeling is a much more effective sales process than making as many contacts as you can in the course of your day. 

Ways to Segment Leads

In addition to the data you’ve already collected, there are a few other things you can consider to optimize the segmenting process. 

Consider the customer’s life stage, need for a specific insurance product, behavior patterns, and potential risks they may face. 

Check out the following examples:

• Life stage: Those who are becoming senior age may need information on Medicare, younger marrieds, and homeowners may need umbrella insurance. 
• Insurance need: Younger individuals may need to increase their limits, and new business owners will need commercial insurance. 
• Behavior patterns: Leads who repeatedly visit your site or have a high email open rate are likely open to hearing from you.
• Potential risks: Parents with teen drivers and homeowners with swimming pools or trampolines may need umbrella liability insurance.

Tailoring Outreach Efforts

You’ll find that well-defined leads will highlight which insurance products will suit them, and when they’ll be the most receptive to hearing from you. 

From there, it’s a matter of fine-tuning your messaging, tone, and timing according to each group’s needs. 

Plan to send personalized quotes to high-scoring leads. You can warm up lower-scoring prospects by sending periodic educational information and updates on insurance trends.

Best Practice #4: Personalize Outreach and Timing

One easy way to improve engagement and drive more sales is to personalize your outreach and connect with buyers when they’re ready to buy. 

Predictive modeling provides insight into when prospective buyers typically answer calls or emails. It helps narrow down the ideal contact windows for reaching warm leads. It takes the guesswork out of when to contact prospects. 

For example, a customer with an upcoming renewal may be interested in getting quotes. Prospects who have revisited your quote or landing pages several times are likely ready to buy. 

To fine-tune the timing of sales calls, pay attention to:

• Site visits
• Email opens
• Quote activity
• Renewal timelines

You can improve your response rates by paying attention to this type of data. 

As you home in on the appropriate timing, it’s important to coordinate your messaging with the customer’s needs or motivations. 

For example, it may be appropriate to create messaging geared toward one or more of the following:

• Cost savings
• Convenience
• Coverage gaps
• Family protection
• Cross-selling or add-ons

Customers and prospects typically respond positively to messages tailored to their needs. Small acknowledgements give your communications a human touch. Use their name, mention a previous interaction, or reference an upcoming expiration date. 

By personalizing your interactions, you will increase efficiency and build trust. More importantly, your prospects and customers will start tuning in and stop tuning out. 

Best Practice #5: Track, Monitor, and Refine

Predictive analysis works optimally when you view it as an ongoing, adaptive process, rather than setting it up once and putting it on the back burner. 

With everything in place, you need to start tracking your findings. This means monitoring your lead scores, conversion rates, and forecasts. Active monitoring will give you a heads-up when a strategy is underperforming. 

A/B testing, also known as split testing, refers to simultaneously sending two similar but different scripts. The idea behind A/B testing is to determine which performs better. 

In the same way, you could use A/B testing to send the same message at two different times to evaluate the best time to contact a particular segment. 

A/B testing results will tell you what resonates most with each segment. You can use that feedback to refine your model. 

Every salesperson knows you need to strike when the iron is hot. Screen-sharing can help you convert the hottest leads without delay.  

Leveraging Screen-Sharing: Reeling in the Sale While the Interaction is Hot!

Are you ready at all times to quickly switch gears from a prospecting activity to making a sale if an opportunity comes your way?

When you’re in full-on prospecting mode, it’s easy to get into a static rhythm where you repeat the same tasks over and over. The risk is that you may miss a green light indicating a prospect is ready to buy immediately. 

The solution is screen-sharing software. With CrankWheel, you can share a link with customers to make an on-the-spot presentation or have them sign documents electronically. Customers can use almost any electronic device to access the link, without downloading anything. 

Read the following case studies for proof that screen-sharing can help improve your sales.   

Salesgenie

Salesgenie is a lead-generation platform to help salespeople get leads.

Salesgenie’s salespeople regularly use CrankWheel’s Instant Demos feature. A widget captures leads and finds an available agent to call the customer back right away. The agent can then share their screen seamlessly. 

A Lead Response Management study showed that a lead is 21 times more likely to express interest within the first five minutes of a call. Early interest will help you shorten your sales cycle. 

The CrankWheel advantage is that it allows salespeople to engage with prospects quickly and meaningfully. Salesgenie highlights simplicity and ease of use as the CrankWheel’s greatest strengths. 

Bee Digital

Bee Digital helps small businesses gain online visibility, so more customers can find them. They also manage social networks, design websites, and more. 

Originally, Bee Digital salespeople conducted in-person appointments. The pandemic made in-person sales appointments impractical, if not impossible. The company quickly pivoted to telephone sales.

Their sales teams found that CrankWheel’s screen-sharing software allowed them to give the same presentation during virtual appointments.

A huge benefit for salespeople is that their customers don’t need any digital knowledge to see their presentation. 

The end result is that Bee Digital salespeople are 79% more likely to close the sale on the first call. 

Predictive Analytics: An Essential Tool in Insurance Sales

Overall, predictive analytics is an essential strategy for modern insurance marketing that can help you improve your sales numbers. 

Clean, updated data from multiple sources will help you align your sales strategy with your sales goals. 

As the leads start streaming in, you can utilize screen-sharing to get sales while they’re hot. 

Contact us today to get a free trial of CrankWheel and see for yourself how it can help you improve your sales numbers. 

Blog FAQ

1. What is predictive analytics in insurance sales? Predictive analytics uses historical data, statistics, and machine learning to identify patterns in customer behavior and forecast which prospects are most likely to buy insurance products.

2. How does predictive analytics improve insurance lead quality? It scores and segments leads based on intent, behavior, and risk factors, allowing sales teams to focus on high-probability prospects instead of wasting time on cold leads.

3. What type of data is needed for effective predictive analytics? Clean, accurate, and relevant data such as CRM records, policy histories, digital engagement, and purchasing behavior are essential for reliable predictions and better sales outcomes.

4. How can predictive analytics shorten the insurance sales cycle? By identifying the right prospects and the best time to contact them, predictive analytics enables more personalized outreach and faster conversions—especially when paired with tools like screen sharing for real-time demos.