Acrisure: Exploratory Research

🏢 Company Overview: Acrisure is the fastest-growing FinTech company in history and top-10 largest, having grown from $50 million to approximately $3 billion in revenue in a few short years. Learn more about Acrisure.

🧢 My Role: As the Principal Product Designer (and only), I was responsible for coordinating and conducting generative exploratory research and executing those insights with design experiments and testing. My role involved understanding the nuanced needs of the insurance industry and implementing grounded theory to develop a focused, data-driven approach to our challenges.

🕑 Timeline: June 2020 (6-8 months)

About Acrisure

Acrisure's humble beginnings reflected the typical insurance brokerage story - build your book, create strong carrier relationships and deliver the best products to your customers... and GROW. Going from $50 million to $3 billion in revenue in a matter of years is no small feat and one largely due to their aggressive M&A strategy by acquiring ~100+ insurance agencies a year.

A House of Brands

With over 500 agencies across the globe, Acrisure's secret sauce is autonomy and the status quo. Whenever an acquisition happens, Acrisure takes the "hands-off" approach and allows the acquired company to keep their name, pay structure, and even policy management systems in place... the only change is that the bottom line goes to Acrisure.

A house of brands, not a branded house.

With 500 agencies practically doing their own thing, it makes it really challenging to make wide-sweeping improvements... the key is to solve a problem that is so painful that each agency can't ignore the solution.

Problem

Acrisure's growth, powered by its M&A strategy, led to a highly autonomous but fragmented operational model. The challenge was to identify and solve a universally painful problem that would unify these diverse agencies under a more streamlined, efficient process without disrupting their successful local operations.

Goals

The primary objective was to discover key factors that make top insurance producers successful and identify where they see challenges and opportunities to improve the end-to-end insurance sales and management journey.

Methods

I adopted a design thinking approach, grounded in Grounded Theory, to gain deep insights into the insurance domain. This approach helped in selecting appropriate research methods and collecting a large amount of raw data from various sources.

The UX research we do — and the UX research we don't do — ripples through everything else we do.

Before starting any field research I always like to capture the definition of success for the project from my stakeholders. This helps to ensure all stakeholders are aligned with what is expected of such an initiative and the desired outcomes.

After I had alignment from my stakeholders, the plan was to get as close to our primary and secondary users with a mixed-method approach using quantitative methods such as surveys and qualitative methods like 1-1 interviews.

Setting Up a UX Repository to Capture and Store Everything

Research can inherently be a messy sport, setting up a process for planning, storing, and analyzing our findings amongst team members is crucial for scalable research efforts.

I've experimented with a few tools like Airtable and UserbitApp, but for this project, I used Dovetail as our repository service.

Needs Gathering & Quantitative UX Methods

Disrupting an industry one interview at a time

In an effort to get to know my users and their problems I set out on an ambitious goal of meeting as many users as possible.

This was supposed to do 2 things, first, it was supposed to allow us to capture wide-sweeping pain points across the Acrisure network, and second, help me build relationships for continuous discovery.

Producer On Finding New Businesses to Prospect

So for us to manually sit there and go website by website, by website, by website to find new businesses, which we had somebody do for a couple of months, it's just so tedious. It's ridiculous.

Producer On Inaccurate Prospect Data

We'll put it in the sales parameters for businesses that do $15 million in sales to make sure we're targeting busineses that drive premium... and after a good amount of time prospecting them we'll find out the data is just not up to date, and the company does $250,000, not $15 million, so getting the correct data sometimes is challenging and can lead to a waste of time.

Creating Personas

While interviews commenced, I organized my findings for participants into personas. This allowed me to compare different segments of people objectively and to further clarify our view of their problem and opportunity space.

Producer On Their Responsibilities

My main concern is to keep my existing clients happy by helping them reduce their costs and mitigate their insurance-related risks... Next is driving growth to the agency with new business accounts... but that's given I have the time to prospect that month.

Definition of a Producer: Someone who works within the agency that 'produces' sales, typically through the form of insurance policies (Property & Casualty, Work Comp, Employee Benefits, Cyber, etc.) and the premium received. Producers need both the insurance technical aptitude and the ability to build trusted relationships with their clients.

Definition of an Account Manager (or Servicer): Someone who assists with front or back-office agency activities such as answering client calls, quoting new business, managing renewal paperwork, etc. AMs need a fundamental knowledge of insurance concepts and the ability to consistently execute on the details for policy management.

User Segmentation and Focusing on Our Core Users

You can't be all things to everyone or you'll be no things for no one.

In order to learn and test quickly, I shifted the research and experiments to focus just on the core segment of users.

By analyzing our array of users, I prioritized them by the desired business impact, value, and product usage - this left me with our primary, secondary and tertiary users.

For the remainder of the research effort, we narrowed our focus on the primary users but also kept in mind our secondary users for quick-win opportunities.

Mapping the Producer Current-State Journey

With the primary users in hand, I set a course on capturing a crystal clear picture of their current-state journey. The benefit of mapping out their current state is the ability to find out what's working and what's not working for them.

The User is always on a journey...

I reviewed my existing interviews and scheduled new ones (if the persona was not represented in the UX repository) and began mapping out their journeys in Miro.

Once I mapped each primary persona's journey and I hit theoretical saturation where no additional findings (pain points & opportunities) or paths were surfacing, I took a few steps back and looked for a holistic journey that I could define.

This led me to the 10,000 ft brokerage-end-to-end "Experience Wheel".

Insights and Findings

Crafting the "10,000 ft" Experience Wheel

When leading a team and co-creating with others, alignment on the "what" that we're trying to solve and how we talk about it is extremely important.

With that, I created a master "Experience Wheel" that we as a company could point to when discussing the different problem and opportunity spaces.

Insight Statements

Sample Insight

Producers need to be seen as "Trusted Advisors" rather than just a person selling insurance, this creates a relationship based on expertise, partnership, & risk management.

I found that my research wasn't being consumed or cited as frequently or as effectively as intended...so instead, I created an "Insight Map" to help visualize our insights all along the brokerage journey ("Experience Wheel").

Sharing Actionable Insights with "Insight Maps"

The "Insight Map" is one of my favorite artifacts for sharing insights that really "stick" with the team and stakeholders.

This is one single journey that contextually maps our available insights, jobs-to-be-done, and opportunities in one document in context to their users moment in the journey. From an organizational perspective that might have teams solely focusing on certain parts of the journey, this map helped them narrow in on their respective area and access all of the research available for them.

On top of that, each insight provides a link to the UX repository and the supporting evidence so everything is traceable back to the source data 💪.

Prioritizing Research Findings For Recommendations

Research teams that consistently prioritize and focus on the right problems to solve at the right moment in time learn faster, grow larger, and move every in the same direction.

You can't solve everything at once, so it's best to choose wisely.

Aggregating Research for Key Findings

With our Atomic UXR repository, it's easy to quickly visualize and stack rank your findings by supporting evidence. Now ranking by supporting evidence can't be the sole form of prioritization since some opportunities might have less research. With that, I introduced a simple ICR UX innovation score for each opportunity (written as job stories).

ICR UX Innovation Scorecard

Impact + Confidence - Risks = UX Innovation Score

Impact: This metric is voted on by business stakeholders

Confidence: The aggregate understanding of our problem and solution space.

Risks: The amount of risk from primarily known and unknown risks.

Innovations Score: The output of our prioritization framework where typically the highest opportunities are passed along as near-term recommendations.

With our opportunities scored and prioritized, it was time to start crafting our recommendations for the subsequent quarters and planning sessions.

Crafting the Final Recommendations for Quarterly Planning

Final prioritized recommendations as hypothesis statements:

Click to see the sample hypothesis statements.

Next Steps

Once the recommendations were passed off and quarterly planning concluded, I shifted my focus toward ideation and planning out the solution experiments for each OKR and KR.

Research Adoption & Impact

Research Output

Observations & Facts: 639

Insights: 128

Thematic Insights: 42

Summary and What I Learned From This Project

Learnings

1. Avoid Shiny Object Syndrome: For discovery work, it's easy to get excited over "quick-wins", however, each distraction comes with a cost. Don't allow excited team members or stakeholders to derail your research effort, document the opportunity in your UX repository and score it as soon as possible and move on.
2. Don't Let The Process Control You: Atomic UXR and especially the process of coding/tagging data can be grueling and time-consuming work. For example, each 1-hour long interview it can take up to 3-5 hours to code/tag. Remember that the process is a means to an end (insights and recommendations) so don't let the process limit you, it's ok to skip a step if it allows for more natural research analysis.
3. Crowdsource Your Data and Have Everyone Upload Everything to the UX Repository: Most likely you're not a wizard and you can't be everywhere at once, if I'm right then it's important to make it a habit that your coworkers in Product, Eng. or even the executive team record all of their important meetings that interface with the customer or a subject matter expert. Any meeting that can teach someone something that relates to the problem being solved should be recorded and uploaded to the repository. Over time and during your analysis step you will thank me later 😊.
4. Building Relationships is More Important than Solutioning: Chances are high that your first solution won't be the best solution, with that, you'll need solid users who are willing to give up their time to help you. Build relationships before you build solutions... and it's more fun this way!

...and that's it!

I hope you enjoyed this case study, if it provoked you in any way I'd love to chat and get to know you and your story 🙂.