Most B2B Insurtech companies rely on firmographics or observable enterprise characteristics to define their Ideal Customer Profile (ICP).
A typical ICP might read something like this: “US-based P&C insurers with more than $1 billion in gross written premium, operating in commercial or specialty lines with more than 500 employees.”
While firmographic data is a useful way to define a B2B market, it is a poor predictor of how and what a target account will buy. For example, two carriers can both be in the same firmographic bucket yet have very different technical needs. One may run on a cloud-native core, while the other operates on a legacy, batch mainframe. Similarly, one carrier might already have in place the right API surface and data infrastructure to implement an Insurtech’s offering, while another won’t be able to do so for several years.
Segmentation should do more than classify prospects based on convenient data fields; it should sharpen targeting, improve account prioritization, and lead to more effective sales strategies.
How to leverage technographic data for sharper targeting
Technographic segmentation groups enterprises according to their technology infrastructure. By mapping out a prospect’s core systems, cloud infrastructure, APIs, data platforms, and third-party software, Insurtech vendors can consider whether a prospect’s technical profile is compatible with their solution.
Technographic data can also be used to inform sales strategies. For example, new cloud footprints and new SaaS onboarding can signal changes in the enterprise tech stack and describe momentum behind digital transformations that are underway. Security and procurement can add quarters to sales cycles, so sales team should plan accordingly.
Four infrastructure archetypes for commercial action
Simon-Kucher analyzed technographic data to identify the technical factors influencing how insurance and financial institutions evaluate, adopt, and implement third-party technology solutions.
Insurtech firms can use the four archetypes below as a starting point to sharpen Go-to-Market (GTM) segmentation, sales design, and white-space analysis. Each archetype reflects the prospect’s risk tolerance, integration capacity, technical readiness, and buying behavior. They inform the sales motion most likely to succeed.
| Cloud-native core | Hybrid modernizer | |
Stack Modern policy or ledger core in public cloud, API-first, heavy third-party SaaS adoption | Stack On-premise core wrapped in cloud middleware and an integration layer, migration programme live | |
Buying behaviour Runs a technical evaluation early, tolerates a fast POC, decides in quarters not years | Buying behaviour Buys against an existing transformation roadmap and its named milestones | |
Motion it needs Lead with architecture fit and time to first integration | Motion it needs Attach to the programme in flight and show the co-existence path | |
| Monolithic on-premise | Mainframe legacy | |
Stack Single vendor monolith or in-house legacy core, minimal SaaS, long release trains | Stack Batch mainframe of record, custom integration required for anything, no SaaS habit | |
Buying behaviour Change is governed by release cycles and vendor dependencies, pilots are contained | Buying behaviour Security, procurement, and integration gates dominate and lengthen the cycle | |
Motion it needs Scope a narrow, side-by-side pilot that does not touch the core | Motion it needs Sell a data-level use case with no core change, or deprioritise | |
Cloud-native core
- Enterprises in the cloud-native core archetype typically have high technical readiness to adopt third-party SaaS solutions. They operate modern policy or ledger cores, expose APIs for integration, conduct technical evaluations early, and make vendor decisions in quarters instead of years.
GTM Strategy: lead with architectural fit and speed to integration supported by a LIVE API-based proof-of-concept, and usage-based commercial terms.
Hybrid modernizer
These enterprises are moving up the technical readiness spectrum. These organizations might have an on-premise core wrapped in cloud middleware and an integration layer. While a legacy infrastructure is still in place, modernization is underway.
GTM Strategy: hybrid modernizers tend to buy against a transformation roadmap and its named milestones. Vendors should demonstrate a co-existence path and attach to the program that is already in flight.
Monolithic on-premise
These enterprises are moving up the technical readiness spectrum. These organizations might have an on-premise core wrapped in cloud middleware and an integration layer. While a legacy infrastructure is still in place, modernization is underway.
- GTM Strategy: lead with architectural fit and speed to integration supported by a LIVE API-based proof-of-concept, and usage-based commercial terms.
Mainframe legacy
At the other end of the spectrum, mainframe legacy archetypes will have limited SaaS adoption, require custom integration, and involve security and procurement hurdles.
GTM Strategy: security, procurement, and integration gates dominate and lengthen the sales cycles for these accounts. Lead with narrowly defined data-level use cases that can be implemented without changes to the core system. Expect a long buying cycle.
| Cloud-native core | Hybrid modernizer | Monolithic on-premise | Mainframe legacy | |
|---|---|---|---|---|
| Messaging | Speed to first integration | Coexistence with the migration in flight | Contained pilot beside the core | Data-level use case, no core change |
| POC1) scope | Live sandbox against production APIs | Single line of business in the new layer | Read-only extract, offline scoring | Batch file exchange, fixed scope |
| Integration story | Native API, self-serve connectors | Through the existing integration layer | Middleware bridge, vendor coordination | Custom interface, long lead time |
| Pricing and commercial terms | Usage-based, short initial term | Phased ramp tied to migration milestones | Fixed-fee pilot, then enterprise licence | Services-heavy, milestone-gated |
| Partner selection | Cloud and platform partners | Systems integrator running the migration | Incumbent core vendor | Specialist integration partner |
Technographics can sharpen sales strategies and identify execution risk
Technographic segmentation can help sales leaders focus resources where they are most likely to generate returns.
Sales territories can be structured around accounts requiring similar sales motions and assigned to representatives with expertise in that integration narrative. Pipeline forecasts can incorporate differences in expected sales-cycle length, while win-loss analysis can reveal where the sales teams are overinvesting in technically challenging accounts and underinvesting in segments with a higher likelihood of conversion.
Technographic segmentation can also identify accounts that present high execution risk. For example, selling into an enterprise with an incompatible core represents signification execution risk compared to a prospect with a shared core pattern, compatible API surface, and overlapping data model.
Signaling technology transformation
Technology environments are not static. A carrier adding cloud infrastructure, new SaaS platforms, or hiring data-engineering talent may be signaling that a broader transformation is underway. Those changes can indicate that budget, executive sponsorship, and implementation capacity are already in motion.
In a recent Simon-Kucher pilot examining 12 leading US specialty carriers, and MGAs, dated technology-install records helped the team predict modernization windows and identify organizations actively migrating platforms. The pilot also signaled legacy systems that had gone dark without an apparent successor, and companies pursuing distinctly different build-versus-buy strategies. These signals help vendors improve targeting, identify windows of opportunity, and tailor messaging. They also support more accurate sizing of addressable, serviceable, and obtainable markets.
Moving beyond traditional B2B segmentation
Segmentation approaches based on company size, geography, premium volume, or other variables are poor predictors of technical compatibility. Supported by technographic data, Insurtech firms can optimize sales resources, prioritize accounts and monitor signals that predict when digital transformation will occur. This gives firms an advantage by enabling them to initiate contact, lead with sales narratives that resonate with an archetype, and disqualify incompatible prospects early.
