Insurance Brokerages & Agencies

Independent agencies and brokerages are sitting on a goldmine of data. Every policy, every renewal, every account your producers have written over the years is recorded in your AMS. You know which clients have homeowners but not auto. You know which commercial accounts have three lines and which have one. You know which producers write a lot of new business but struggle to retain it, and which ones hold accounts forever but never round them. The data is all there. What almost no agency has is a systematic way to turn that data into a daily action list for their producers — which accounts to call, what to offer, and why right now. That's what we build.

Why This Problem Is Bigger Than It Looks

Most agency principals have a general sense that their book has untapped potential. What they usually don't have is a precise number. In our experience working with agencies, somewhere between 40 and 60 percent of accounts are mono-line — a single policy with no cross-sell conversation ever documented. A meaningful portion of those accounts have profiles that match your best multi-line clients exactly. They're not mono-line because they don't want more coverage. They're mono-line because nobody has called them with the right offer at the right moment.

Renewal season compounds the problem. Agencies manage renewals reactively — the X-date comes up, a producer calls, and the outcome depends almost entirely on that producer's instincts and relationship. There is rarely a systematic analysis of which renewals are genuinely at risk, which clients are candidates for a coverage review and an upgrade, and which are locked in regardless. The result is that producers spend equal energy on accounts that need no attention and accounts that are about to walk — because nobody has told them the difference.

Producer performance is the third piece. Cross-sell rates, retention rates, and premium per account vary dramatically between producers at the same agency, often by a factor of three or four. Most principals know this intuitively. Almost none have a data-driven picture of exactly where those differences come from and which specific accounts represent the gap.

The Proof

A top-20 U.S. insurance company faced a version of this problem at massive scale — thousands of call center reps talking to policyholders every day with no way to know what to recommend in real time. The company's data science team had built models that could predict what a customer was likely to buy. The problem was the last mile: getting those predictions onto the rep's screen during a live call. We built the platform that bridged that gap. It analyzed millions of policies, generated the right recommendation for each policyholder, and delivered it in under a second. The company credited the system with roughly $80 million in additional premium revenue.

The underlying dynamic is the same for an independent agency with 3,000 accounts as it is for a carrier with three million. You have the data. Your team is talking to those clients. The question is whether those conversations are informed by everything you know about each account, or whether your producers are operating on instinct and memory. One of those approaches scales. The other doesn't.

Phase 1 — Discovery

$5,000 — Two weeks

The discovery engagement for an insurance agency is not a generic workflow assessment. It is a deep analysis of your actual book of business, conducted by people who understand how agencies operate and what the data means.

We connect to your AMS — whether you're running Applied Epic, EZLynx, Hawksoft, AMS360, or another system — and pull your policy data, account history, producer assignments, and renewal schedule. We analyze what you have, how it's distributed, and what the patterns tell us. At the end of two weeks, you receive a written report that covers:

• Book segmentation: Your accounts broken down by premium volume, line of business distribution, years as a client, and estimated cross-sell potential. You'll see which segments of your book are performing and which are underserving their potential.

• Renewal pipeline analysis: Your next 90 days of renewals, each account tagged and ranked. At-risk accounts — those showing patterns consistent with clients who have historically lapsed or shopped — are flagged with the specific indicators. Cross-sell and upgrade candidates are identified based on their profile relative to your best multi-line accounts.

• Producer benchmarking: Retention rate, cross-sell rate, premium per account, and mono-line rate broken out by producer. Where there are meaningful differences between producers, we identify which specific accounts represent the gap — not to assign blame, but to understand where the opportunity is concentrated and what the best producers are doing differently.

• Priority call list: A concrete, ranked list of accounts your team should be contacting in the next 30 days, with the specific reason for each — renewal risk, cross-sell fit, anniversary of last coverage review, or a profile change that warrants attention.

• Revenue impact estimate: A bottom-up calculation of what capturing the top identified opportunities would add in annual premium and commission income. Not a generic percentage. A number built from your actual accounts.

This is a $5,000 engagement that delivers something most agencies have never had: a clear, data-driven picture of exactly where their book is performing, where it isn't, and which specific actions would move the number. Most principals find that the report alone changes how they run their weekly producer meetings. Some use it to make the case to their team for a larger investment. Some file it and return to it six months later. The point is that it stands on its own — you are buying a real analysis, not a sales pitch with a bow on it.

If we find in discovery that your data is too thin, your AMS records too inconsistent, or the numbers simply don't justify a larger build, we will tell you. We are not interested in proposing a platform that won't pay for itself.

Phase 2 — The Intelligence Platform

Based on what discovery surfaces, we build the system that puts those insights in front of your producers at the moment they need them — not in a quarterly report they'll skim, but in the interface they're already using every day.

When a producer opens an account in your AMS, they see a panel that tells them everything relevant to that conversation: the lines the client has, the lines they don't have that accounts like theirs typically carry, the renewal date and any risk flags, and a set of talking points the producer can use immediately. There is no new workflow. There is no training program. The information is simply there, in context, when the producer needs it.

The system also generates a daily and weekly priority queue — a ranked list of accounts each producer should be contacting, with the reason for each. This eliminates the "who do I call today" problem that causes producers to default to their most comfortable accounts rather than their most important ones. Managers get a parallel view: book health by producer, cross-sell rates over time, and an early warning when a segment of the book is showing retention risk.

Everything is fully managed. Your team uses it. We handle the rest.

Who This Is For

This model is built for independent agencies and regional brokerages — the firms that have a real book of business, established producer relationships, and years of account history in their AMS. It is not for captive agents with no data portability, and it is not for carriers operating at enterprise scale with existing data science teams.

The principal or owner who gets the most value from discovery is one who already suspects their book is underperforming its potential but has never had the analysis to know exactly where or by how much. If you've ever looked at your retention rate and wondered which accounts you're actually at risk of losing, or looked at your cross-sell rate and wondered why it differs so much across your producers, the discovery engagement will answer those questions with specifics — and put a dollar figure on what better answers are worth.

The agencies that see the most dramatic results from the platform are those where producers are already having good customer conversations but without the information they need to make those conversations count. The system does not replace producer judgment. It gives producers something to act on. The combination is where the premium growth happens.