Data Analysis for Insurance Agencies
New to data analysis? Then this is the post for you.
This blog will be discussing what data analysis is, how to use it, what stats to pay attention to, and, ultimately, why it’s important. It is also important to note that this is a comprehensive overview filled with suggestions and tactics; what works for one person won’t necessarily work for another. Analytics is a learn-as-you-go subject—each time you’ll gain more insight and clarity.
So, let’s start with the basics.
What is data analytics?
According to TechTarget, data analytics is as follows:
“The process of examining data sets in order to draw conclusions about the information they contain, increasingly with the aid of specialized systems and software.”
The data you will be analyzing will likely be raw data or “big data”. It can be about anything (amount of visitors to a coffee shop every day, hours of tv watched, number of adds or terms a month, etc.). Basically, it’s just a bunch of numbers gathered together. However, without analysis, big data is meaningless and pretty mind numbing.
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When looking at data analytics, there are three main classes of analysis as described by Dr. Michael Wu.
Descriptive is the simplest and most common class of analysis. In fact, roughly 80% of all business analysis, most notably social analysis, is descriptive analysis. The purpose of descriptive analysis to summarize and tell you what happened. It can be as simple as applying filters on your data to get a better view of it and narrow it down.
“Most raw data, especially big data, is not suitable for human consumption, but the information we derive from the data is.”
For you, descriptive analysis could be measuring ROI on lead sources or tracking the number of touchpoints you have with a lead. You can pull the data to better understand your current endeavors to see how everything is working and if you need to be making any changes for the future.
Predictive analysis helps you to make predictions about the future. The simplest and most familiar predictive analysis is a trend line. Essentially, this class of analysis is looking at what’s been happening to help clue you into what might happen next. (Think weather predictions.)
"The purpose of predictive analysis is NOT to tell you what will happen in the future. It cannot do that. In fact, no analytics can do that. Predictive analytics can only forecast what might happen in the future, because all predictive analytics are probabilistic in nature."
Use the descriptive analysis you gathered and project into the future. If you continue the number of touch points you have now with leads, how will that affect your overall conversion rate? Or, how are certain lead sources performing (money vs. conversion)?
Prescriptive analysis is a type of predictive analysis. It is understanding the descriptive and predictive analysis and using that to decide your next action. You can also use it to predict different outcomes to see which would be the best option for you
“Prescriptive analytics is a type of predictive analytics. It’s basically when we need to prescribe an action, so the business decision-maker can take this information and act.”
Analyze what you’ve learned through your descriptive and predictive analysis for the ROI on your lead sources or conversion rate. Discern from what you’ve learned to determine your next moves. These could include more touchpoints, more/fewer dollars spent on a certain lead source, research of another lead source, etc. Look at your options and analyze how those will play out, then choose which is the best for you.
Think of prescriptive and predictive like medicine. You have an ailment which your doctor predicts it will get worse as time goes on. She/he prescribes a medicine that will help make it better. The doctor is using the predictive analysis he/she has made to make a prescriptive analysis of what would be the best course of treatment.
So it’s just looking at a bunch of data?
Yes and no.
Yes, you’re looking at a bunch of data, but it is much more than that. Data analysis is interpreting reason from the data. It is drawing from that information to create conclusions, generalities, and facts as to the current health of your insurance agency: where you’re going, and what that means for the future. It’s turning your “big data” into “smart data”. Here's how Wired describes "smart data":
“Smart Data” means information that actually makes sense. It is the difference between seeing a long list of numbers referring to weekly sales vs. identifying the peaks and troughs in sales volume over time. Algorithms turn meaningless numbers into actionable insights. Smart data is data from which signals and patterns have been extracted by intelligent algorithms. Collecting large amounts of statistics and numbers bring little benefit if there is no layer of added intelligence.”
Smart data is combining the three classes of analysis from above. Using your data to narrow down, understand, and act—being smart about how you’re using the data. It sounds complicated, but converting your big data to smart data isn’t that hard. Convince & Convert wrote an article about how to do so in 5 easy steps which I’ve briefly summarized here (check out our free eBook What is Smart Data? to learn more about applying each step to your insurance agency) :
- Define & Search. Figure out what you’re looking for. Hone in on one particular question.
- Filter the Data. Apply the necessary filters so that you will only see the data that pertains to the question you asked in step one.
- Analyze the Data. What insights can you gather from the data to better understand and extrapolate an answer to your question. (Descriptive Analysis)
- Use the Data. Make a plan. What did you learn? What is your next step? How does that correlate with your goals? (Predictive & Prescriptive Analysis)
- Combine the Data. Repeat these steps with your other questions to get an even more detailed view into the health of your insurance agency.
Man, that sounds like a lot of time…
It’s really not, and there are steps you can take to help lessen the time requirement.
Step 1: Clean your data
If you’ve never heard the term clean data before, then check out our blog Why “Clean Data Makes a Difference. Clean data means that your data is in tip-top shape, is the most up-to-date, and is organized in an understandable way. Think of it this way, clean eating better fuels your body and helps you to be more productive and reach your goals—clean data better helps you to better understand your book so you can be more efficient and reach your goals.
In a survey, CrowdFlower found that 60% (others noted that it took up to 90% of their time) of a data scientist’s time is spent organizing and cleaning the data they’re going to analyze. And that is their everyday job! So think how much time it would save you, someone who doesn’t organize and clean data for a living, to already have all of your data cleaned, organized, and ready to go.
This step is far and wide the most time-consuming task. And, depending on the state of your data, it could take a while for you to get it in order. But don’t let this scare you away, because this step is also the most necessary. If you don’t do this now, it will just make doing it later more complicated; and sooner or later you will need to do this. Clean data helps you run more efficiently, save time and money, and makes your book of business more appealing and valuable if you decide to sell it.
Many agencies hire interns to help with this so that they can focus on other aspects of the business. College kids are always looking for part-time jobs, especially if they’re on summer or winter vacation.
Step 2: Organization & Maintenance
Once you have all of your data organized, you want to make sure it stays that way. With Excel spreadsheets and paper files, this can be really, really difficult. Think of how many people have access to those spreadsheets and how many can edit them. Then, on top of that, each person saves each copy on their computer or under a different name in the shared drive. The records would be strewn about your entire office.
Or, with paper files, how many times have people updated it? Or how many copies do you have throughout the office? Printed paper doesn’t update in real time.
After you’ve figured all of that out, you will have to consolidate, correct, modify, cross-check, etc. to make sure everything is up-to-date and right. Now THAT is time-consuming. In fact, one study found that 12 hours are spent each month consolidating, modifying, and correcting spreadsheets.
You would constantly have your data going between clean and organized to a colossal mess. You would be back to spending 60-90% of your time preparing your data, else, you’ll be working off incorrect or bad data—which you do not want! Remember, you want to use this data to make more informed business decisions and potentially grow your insurance agency or prepare it for sale. Also, you want to learn from this data. It’s honestly pointless to do any of those things if you’re not working off of the most accurate and up-to-date information.
When you consider all of this, it’s really no surprise why 30% of insurance agencies are planning to adopt an agency management system (AMS) like AgencyBloc for the first time this year. An AMS like AgencyBloc helps you to keep your data in order and keep it up-to-date. Forget having to update multiple spreadsheets every time a policy changes or a contact moves. When you update information in one part of your AgencyBloc book of business, it updates the information throughout. You can be assured, then, that your data will always be up-to-date and accurate.
Choosing an industry-specific AMS that has business analytic capabilities like AgencyBloc will make a world of a difference when it comes to step three. For AgencyBloc, we call this component our Dashboard Analytics—learn more about this feature in our free eBook.
Step 3: Automation
So you’ve taken the time to go through and deep clean all of your data. You’ve transferred all of it into an industry-specific AMS like AgencyBloc to maintain it. But you haven’t even begun to analyze it. That’ll be time-consuming, right? Actually, it doesn’t have to be.
Remember what I said earlier: far and wide the most time-consuming task will be cleaning your data. You’ve already done that and you’re maintaining it! The tedious parts are out of the way. Now it’s time to start using your data.
Now, if you skipped step two and opted to not use and industry-specific AMS with an analytics component, then this may take more time. However, if you choose an AMS like AgencyBloc, this is actually quite simple. AgencyBloc’s Dashboard is your welcoming screen when you log in. On here you’ll find graphs and charts that give you a snapshot look at the health of your insurance agency. How many leads do you have? There’s a graph for that. What’s your in-force policy saturation look like? There’s a chart for that. What do you need to get done today? There’s a list for that.
AgencyBloc's Dashboard Analytics
These graphs and charts give you a high-level overview of what all is going on with your book of business. Want to learn more? Simple. AgencyBloc’s Advanced Report feature allows you to filter your data, so you only see what you need to. What to know how many leads and prospects you’ve gained in the last month? Easy. Just apply the necessary filters and press run. The whole process, if you know what you’re looking for, takes less than 30 seconds. You can also save the reports you run all the time, so you don’t have to go through and filter again.
AgencyBloc's Advanced Reporting
There, you’ve already done the analysis you needed. Now you can use what you’ve learned to make a more informed decision in the future. Consider this example:
- You’ve been putting a lot of money towards X lead source for the last 12 months, but is it really worth it?
- Pull a report to see how many leads have come from that lead source each of the last 12 months.
- Run that against the conversions you’ve had each month to pull together an ROI (return on investment).
- Leverage the money you’ve brought in from those clients vs. the money you’ve spent on the lead source.
- Now you actually know if the lead source has been worthwhile. If it has, awesome! If it hasn’t, then maybe you should consider looking elsewhere.
Once you know what you’re looking for, pulling all these reports will take less than 5 minutes.
Is it beneficial?
Data analytics is becoming a more and more important for insurance agencies. In a report, Accenture noted that 68% of insurers marked big data and analytics as an important or very important priority with digital technologies. For that reason (and others), many insurance agencies are looking to move their books of business to a digital system. In fact, 80% of insurers currently invest moderately or significantly in new digital technologies and 61% are expecting to increase their investment soon.
“More and more companies today understand that they have to become data driven in order to remain competitive.”
Founder of Xplenty
Data analytics will also help to keep you relevant in an increasingly competitive market. The Chartered Institute of Loss Adjusted reported that 82% of industry professionals believe organizations which do not utilize big data will likely become uncompetitive.
Still feeling a bit hesitant? Consider the advice from these industry experts:
In their report “Insights Everywhere”, Intel states:
“In today’s digital world, businesses that want to master the flow of information have to address three key challenges: the explosive growth in data volumes, the need to analyze those growing volumes in real-time, and the need to deliver the resulting insights to user.”
In their blog “Harnessing the Insurance Data and Analytics Exhaust Stream”, Accenture states:
“Harnessing external data is a complex undertaking, but insurers can start by developing a comprehensive plan and then undertaking specific, high-return initiatives that build momentum and help transform the enterprise into a winning competitor in the new digital arena.”
In their report “Advanced Analytics for Insurance”, Ernst & Young states:
“In a volatile world, advanced analytics for insurance allows you to identify new growth opportunities while protecting and optimizing your enterprise.”
What are some things I should be looking at?
In their report Advanced Analytics for Insurance, EY identifies these areas as what insurance agencies can use analytics for:
- Provide early detection of opportunities and issues (think: increasing terms or falling conversion rates)
- Identify hidden revenue opportunities within your customer base (think: cross-selling)
- Retain high-value customers
- Optimize capital through a deeper and more immediate knowledge of risks (think: sinking money in certain well-performing lead sources or carriers)
- Leverage social media to deepen customer knowledge and open a new distribution channel
The Digital Insurer goes on to mark these as the key areas you should be reporting on:
- Agent Recruitment / Retention
- Design & Develop Products / Services
- Marketing Campaigns
- Assess Client Needs / Illustrate Value
- Submit & Process Applications / Orders
- Enroll New Customers / Applications / Orders
- In-Force Management
One of the most lucrative opportunities you can find with advanced analytics is cross-selling opportunities. You can manipulate your analytics to see just how many clients you could be selling additional policies to. Remember, the probability of selling to a new prospect is 5-20%, the probability of selling to an existing client is 60-70%. Your odds of selling an additional policy to an existing client is 40% higher. Learn more about using analysis and reports in AgencyBloc to identify potential cross-sell opportunities in our blog: How to Find Insurance Cross-Selling Opportunities and Act on Them Immediately.
Another opportunity you’ll find with data analytics is that you’ll be able to understand who your clients are. You can see what kinds of policies are selling best, who is your best model customer, what your audience is looking for, and what their next steps may be. A better understanding of your clients can definitely lead to growth in your insurance agency. 52% of insurance consumers classify themselves as “relationship buyers”; so if they feel like you really understand them and their needs, they’re more likely to stick around and buy more from you.
It's Never Too Late to Start
The end of the year is getting closer and every day is getting progressively more stressful for many agencies. Having a better insight into your book of business could help lessen some of that stress. You’ll know what’s going on in your book so you won’t be taking “shots in the dark” when making decisions. You’re also less likely to be pulling out last ditch efforts to make quota because you’ll already know what works and what doesn’t.
“Informed decision making is the foundation upon which successful businesses are built. As a decision maker for your business, you need access to highly visual business intelligence tools that can help you make the right decisions quickly.”
Product Manager, Dundas Data Visualization
Using an industry-specific agency management system (AMS) with integrated analytical tools and reporting features could make all the difference for Q4 this year and all the years to come.
When can I start?
Learn more about our Dashboard Analytics and Advanced Reporting features by talking to one of our industry experts. Schedule your personalized 1-on-1 demo to see how AgencyBloc could streamline your day-to-day process
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