Track Identity and Access Management Market Share with Primary-Sourced Deployment Data

Cybersecurity is changing faster than most dashboards can refresh. Nowhere is that truer than in the identity layer—the digital front door where authentication, authorization, single sign-on, and multi-factor checks shape every access decision. For years, professionals looking to understand market share and adoption in this space relied on static reports, lagging disclosures, and anecdotal commentary. They were left waiting weeks or months to spot a shift. Today, a new wave of primary-sourced, high-cadence datasets puts real-time visibility within reach, enabling precise tracking of deployments, install bases, and usage volumes across identity platforms.

Historically, market researchers and operators pieced together intelligence from conference chatter, press releases, infrequent financial filings, and one-off case studies. Before modern external data pipelines existed, teams tried to extrapolate adoption from community forums or generic web traffic trends—imperfect proxies that often led to overconfidence or missed inflection points. Even public procurement notices were difficult to unify, living across fragmented portals and published on unpredictable schedules.

Before there was any reliable digital trail at all, practitioners leaned on vendor roadshows, trade magazines, and personal networks. This meant coverage was patchy, biased, and slow. Security leaders couldn’t quantify how many organizations had switched to federated identity, where passwordless was gaining traction, or whether a wave of renewals hinted at platform consolidation. In an ecosystem as critical as identity and access management, that opacity made strategy feel like guesswork.

The proliferation of cloud software, ubiquitous logging, and connected applications has changed the game. Authentication events leave machine-readable fingerprints. App marketplaces list integrations and enterprise deployments. Procurement platforms publish award-level details, often with daily cadence. Modern web crawling can recognize code-level technology signals that map to specific identity providers, federation protocols, and MFA methods. The result is a rich tapestry of primary-sourced indicators that can be aggregated to illuminate market share, deployment growth trends, and usage volumes—globally or segment by segment.

Equally important, the best of these datasets are collected at a monthly or even daily frequency. That means teams no longer need to wait for quarterly updates to understand the trajectory of single sign-on (SSO) adoption or to see multi-factor authentication (MFA) usage volumes shift after a regulatory change. With consistently refreshed feeds, you can watch install bases expand, monitor public-sector awards in near real time, and correlate login activity spikes with product launches or security incidents.

In this guide, we’ll explore the most impactful categories of data for understanding the identity layer. We’ll focus on primary-sourced signals—no surveys or reviews—that are available globally or have strong US and EU coverage and are accessible at a monthly or higher cadence. For each data type, we’ll cover where it comes from, how it has evolved, and exactly how it can help you quantify market share, track deployment volumes, and map usage patterns across the identity ecosystem. We’ll also highlight how modern data search tools streamline discovery, and where emerging approaches, including AI-assisted curation, can accelerate insight.

Web Technographics and Technology Fingerprinting Data

What it is and how it evolved

Web technographics refers to datasets that identify which technologies are deployed on public-facing websites. Early efforts focused on simple pattern matching—spot a library string in HTML, infer the technology. Over time, advances in headless browsing, JavaScript rendering, and network interception made it possible to inspect deeper layers: script contents, HTTP headers, cookie names, DOM structures, and calls to authentication endpoints. Today’s technology fingerprinting can detect identity widgets, federation protocols (like SAML or OIDC), and even specific flows tied to enterprise single sign-on.

This data is inherently primary-sourced: crawlers directly collect, parse, and classify the code and network signals emitted by websites. Unlike surveys, this approach scales globally and updates continuously, often at a monthly or faster cadence. As cloud adoption increased and identity moved into the center of digital experiences, fingerprints multiplied—login pages, embedded SDKs, and redirect URIs create rich signals that map to real-world deployments and active integrations.

Who uses it and why it’s accelerating

Historically, technographics were the domain of sales and marketing teams prioritizing accounts. Today, cybersecurity market researchers, competitive intelligence analysts, investors, and product strategists rely on this data to quantify install bases and track changes in near real time. The shift to web-first interfaces and the rise of federated identity make public-facing signals especially telling. As more organizations standardize on SSO and MFA—and publish login portals accessible to the web—the volume and precision of detectable signals keep expanding.

Advances in machine learning and pattern recognition have boosted detection accuracy, reducing false positives and enabling granular classification. The result: a clearer view of which identity platforms are deployed, where, and how deeply they’re integrated across industries and regions.

How to use technographics to track identity adoption

For identity market research, technographics provide a credible way to estimate deployment counts and growth trends. By crawling target domains and subdomains, you can identify the prevalence of specific authentication widgets, protocol handlers, and identity provider redirects. Tracking these signals over time reveals install base growth, churn, and new deployments—insights that are difficult to glean from traditional disclosures.

Because crawls can be scheduled at monthly or faster intervals, you can measure the velocity of change. That means catching momentum shifts early—such as an uptick in passwordless flows or adoption curves in a new geography—and segmenting by vertical markets like financial services, healthcare, or education.

Specific use cases and examples

Install base tracking: Count websites with detectable SSO or MFA components to estimate deployment volumes across regions and industries.
Market share by segment: Compare the presence of identity integrations across verticals (e.g., public sector vs. private sector) and company sizes.
Growth trend analysis: Monitor month-over-month increases in identified deployments to spot acceleration or deceleration.
Competitive displacement: Detect changes in technology fingerprints that suggest migrations between identity platforms.
Protocol adoption: Track the prevalence of SAML, OIDC, and OAuth flows to understand federation and authorization trends.

When combined with other primary-sourced feeds, technographics can anchor robust market share models and provide a defensible baseline for deployment counts and adoption velocity.

Public-Sector Procurement and Government Contract Awards Data

From paper trail to real-time signal

Public procurement used to mean paper notices and scattered bulletins. Even as award postings moved online, discoverability and standardization lagged. Today, government portals across the US, EU, UK, Canada, Australia, and many states publish award-level contract details digitally and with rapid cadence—often daily. This makes public-sector contract data one of the most objective, primary-sourced indicators of identity platform adoption.

These datasets are compiled directly from official procurement portals and registers. They provide structured fields for award dates, contracting authorities, suppliers, contract values, and sometimes scope details that indicate identity categories such as access management, SSO, MFA, or directory services. Because awards, renewals, and framework call-offs are posted continuously, market researchers can track momentum without waiting for quarterly press releases.

Why it matters for identity market research

Public-sector technology purchases are large, visible, and compliance-driven, often requiring robust identity controls. Tracking awards across agencies reveals adoption patterns, renewal cycles, and the pace at which identity standards spread across education, healthcare, municipal, and federal entities. Even where sensitive details are redacted, metadata and award narratives provide actionable signals.

Crucially, this intelligence is primary-sourced and available at daily or weekly cadence. With consistent pipelines, analysts can build rolling time-series views of contract counts and values, correlate award spikes to policy changes, and identify which regions are increasing MFA and SSO coverage fastest.

Operationalizing procurement data

To translate procurement postings into market share insights, unify award-level data across jurisdictions, normalize supplier names, and tag awards by identity function. Map resellers and value-added integrators to ultimate platform vendors to reveal true market penetration. Over time, renewal and extension notices help estimate customer retention and contract longevity, while new award patterns surface greenfield deployments.

Specific use cases and examples

Public-sector market share: Aggregate award counts and values tied to identity solutions across agencies and countries.
Renewal tracking: Monitor expiring agreements and extensions to infer retention rates and net expansion.
Policy impact analysis: Correlate MFA mandates or zero-trust initiatives with increased award volume for identity components.
VAR mapping: Link awards made to resellers with the underlying platform to measure true vendor penetration.
Competitive intelligence: Identify where incumbents are displaced during re-tenders, signaling shifting preferences.

With a strong normalization layer and monthly or faster refreshes, public-sector procurement data becomes a reliable backbone for deployment and contract volume tracking.

Commercial Terms and SaaS Pricing Intelligence Data

From file cabinets to structured contract intelligence

Inside enterprises, software contracts and order forms capture the commercial reality of identity deployments—license counts, SKUs, term lengths, and pricing tiers. Historically, these documents lived in filing cabinets or siloed procurement systems, making competitive benchmarks and volume estimates elusive. The shift to digital procurement, cloud-based CLM (contract lifecycle management), and structured line-item extraction has changed that landscape.

Modern commercial intelligence datasets are assembled from actual transaction documents, delivering a primary-sourced window into the pricing and scale of identity rollouts. Extracted fields can include license quantities, feature bundles (e.g., SSO, MFA, lifecycle management), renewal dates, and uplift terms. While personally identifiable information is excluded, aggregated and anonymized records reveal the shape of real deployments and contract volumes.

Who uses it and why cadence matters

Procurement teams, finance leaders, and market researchers use this data to benchmark pricing, plan negotiations, and estimate market size. For identity market research, license counts and SKU mixes are particularly valuable proxies for install base and feature adoption. Because renewals and true-ups happen throughout the year, monthly or higher-frequency updates are essential to capture trends and seasonality.

The volume of available data is expanding as more organizations digitize contracting and as extraction tooling becomes more accurate. This growth translates into sharper segmentation—by company size, industry, and region—improving the fidelity of market share estimates.

How to apply commercial intelligence

Use license quantities to estimate seat counts and align SKU mixes with feature adoption (e.g., the proportion of contracts including MFA). Track renewal cohorts to assess retention and expansion. Analyze price-per-user and discount bands to understand competitiveness and to model revenue trajectories by segment. When paired with technographics and procurement awards, a coherent picture of deployments and commercial momentum emerges.

Specific use cases and examples

License volume modeling: Convert SKU and license counts into estimated active user volumes by industry and region.
Feature adoption: Measure the share of contracts that include SSO, MFA, passwordless, or lifecycle management modules.
Renewal momentum: Track renewal dates and uplifts to model net revenue retention and customer stickiness.
Pricing benchmarks: Compare price-per-user across segments to gauge market competitiveness and discount trends.
Expansion signals: Identify contract amendments and add-on purchases as indicators of deployment growth.

Because these insights are derived from real contracts rather than surveys, they provide a defensible basis for market share estimation and deployment volume tracking.

Digital Authentication Telemetry and SSO/MFA Usage Data

From logs to market-level signals

Every login attempt, second factor prompt, and federated redirect produces a machine event. Aggregated across enterprises and services, those events provide a powerful, primary-sourced view of authentication activity. Privacy-preserving telemetry—compiled from network sensors, endpoint agents, or application-side logs—can reveal volumes of authentication flows, the prevalence of MFA, and the growth of SSO across industries and geographies.

Unlike one-time reports, modern telemetry feeds update at a monthly or even daily cadence, enabling near real-time monitoring of usage trends. These datasets are especially valuable for capturing actual activity rather than just deployments on paper. A platform may be installed, but usage volume—and the mix of authentication factors—tells you how deeply it’s embedded in daily operations.

Why usage data matters for identity market research

Install base counts identify where a platform is present. Usage telemetry shows which platforms are winning share of authentication events, where MFA usage is rising fastest, and how SSO adoption varies by region. For market researchers, that difference is crucial. Activity-based share can diverge from seat-based share, especially during migrations or consolidation cycles.

Because this data is generated by systems of record—access logs, identity gateways, and application endpoints—it’s primary-sourced and resistant to perception bias. With thoughtful aggregation and segmentation, it becomes a high-fidelity indicator of market momentum.

Turning telemetry into insight

Build baselines of total login activity by sector, then segment by authentication method. Track the ratio of single sign-on events to direct logins. Monitor the share of logins that trigger second factors, and the distribution of factor types (push, OTP, hardware token, biometrics). Watch for seasonal and policy-driven shifts, such as spikes following regulatory deadlines or security incidents.

Specific use cases and examples

Authentication volume share: Estimate market share based on percentage of total logins by platform, updated monthly.
MFA penetration: Measure the proportion of sessions protected by MFA, by industry and geography.
SSO adoption trajectory: Track growth in SSO-covered applications within enterprises to infer consolidation on a central identity provider.
Risk response analysis: Correlate breach headlines with changes in MFA usage and step-up authentication.
Migration monitoring: Detect shifts in login routing patterns that signal platform transitions.

Paired with technographics and contract intelligence, usage telemetry closes the loop from presence to activity, turning identity market research into a living, real-time discipline.

Certificate Transparency, DNS, and TLS Telemetry Data

A quiet gold mine in the identity layer

Behind every secure login lies a chain of DNS lookups, TLS handshakes, and certificates. Public Certificate Transparency (CT) logs, passive DNS, and TLS telemetry form a rich, primary-sourced layer of signals useful for identity market research. CT logs reveal new certificates for login subdomains and identity endpoints; DNS patterns expose federation and redirect infrastructure; TLS fingerprints can hint at platform-level services.

Over the last decade, widespread HTTPS adoption and CT log mandates dramatically increased the volume of observable identity-adjacent events. This has transformed what used to be a niche data source into a scalable, high-cadence lens on how organizations structure authentication and access endpoints—often updating daily.

What it shows and who benefits

Security researchers and threat intelligence teams pioneered these techniques for asset discovery and risk monitoring. Today, market researchers can repurpose the same signals to infer the presence and evolution of identity architectures. For example, new certificates for “login,” “auth,” or “idp” subdomains may precede a rollout; changes in CNAME patterns can reveal vendor-hosted identity services; shifts in TLS configurations may suggest platform migrations.

As companies expand globally, the density of identity endpoints grows, increasing the observability of change. Monthly or higher-frequency snapshots enable trend lines that align with procurement awards and deployment milestones.

From telemetry to tracking

Start by building dictionaries of identity-related subdomain patterns and known federation endpoint paths. Monitor CT logs for cert issuance events tied to these patterns. Augment with passive DNS to follow CNAME chains to managed identity platforms. Use TLS metadata to cluster similar service endpoints. When combined, these signals offer time-stamped breadcrumbs that map to real deployments.

Specific use cases and examples

Early deployment detection: Spot certificate issuance for new auth subdomains as a leading indicator of upcoming rollouts.
Vendor-hosted mapping: Identify CNAMEs pointing to managed identity providers to estimate platform adoption.
Migration tracking: Detect changes in DNS and TLS patterns that correspond to provider switches.
Global footprint: Measure the geographic spread of identity endpoints to understand regional adoption.
Change velocity: Track the monthly cadence of new or updated certificates to gauge deployment momentum.

These network-layer signals are objective, machine-generated, and continuously updated—making them a potent complement to application-layer technographics and contract-centric datasets.

How These Types of Data Work Together

Build a multi-signal model for market share

Each dataset illuminates a different dimension of identity adoption: technographics reveal presence on the web, procurement shows awarded contracts, commercial intelligence quantifies license volumes, authentication telemetry measures actual usage, and certificate/DNS data exposes infrastructure changes. When stitched together with consistent entity resolution and time alignment, they form a robust, primary-sourced model of market share.

Because each source updates at monthly or faster cadence, you can maintain rolling views that capture acceleration, deceleration, and seasonal patterns. Blending signals reduces single-source bias and increases confidence—especially critical in high-stakes cybersecurity decisions.

Operational best practices

Cadence alignment: Normalize all feeds to a common monthly time base for trend analysis.
Entity resolution: Unify domains, legal entities, and agency names to avoid double counting.
Feature tagging: Classify signals by identity function (SSO, MFA, lifecycle, governance) for richer segmentation.
Privacy-by-design: Use aggregated, anonymized data and respect legal constraints when handling logs and contracts.
Model validation: Cross-check telemetry-based estimates against contract volumes and known deployments.

Discovery is easier than ever thanks to modern data search platforms that unify access to multiple primary-sourced feeds across the identity ecosystem.

Beyond the Core: Additional Datasets That Enrich Identity Insights

Integration marketplace and partner ecosystem data

Identity platforms often operate at the center of vast integration ecosystems. App directories, partner listings, and marketplace ratings (not surveys) provide primary signals about the breadth and depth of integrations. Monthly snapshots of new connectors and customer logos can signal product-market fit and enterprise traction.

Job listings and talent signals

Hiring data—scraped from company career pages—shows demand for skills tied to specific identity technologies. Because postings update daily, they offer a rapid indicator of platform expansion, migrations, or new feature adoption. This is primary-sourced content published directly by employers and can be segmented by region and industry.

Support documentation and release notes

Although more qualitative, change logs, deprecation notices, and admin guide updates—published by vendors—can be parsed at scale to create structured signals of capability rollout. When you need to build models or classifiers for text, consult best practices for training data collection and curation.

Combined with the big five categories above, these enrichment sources improve feature-level adoption estimates and help explain inflection points in SSO and MFA usage trends.

Conclusion: Turning Identity Research Into a Real-Time Discipline

The identity and access management landscape is too dynamic for quarterly snapshots. By leaning into primary-sourced, high-cadence datasets—technographics, public procurement, commercial contract intelligence, authentication telemetry, and certificate/DNS signals—organizations can track market share, install base volumes, and usage patterns as they evolve.

Once fragmentary and slow, the data has become timely and precise. No more waiting months to spot a shift in MFA adoption or to see which regions are consolidating on SSO. With monthly or even daily updates, the identity market becomes a living timeline that can inform strategy, investment, and execution.

For business professionals, this is more than measurement—it’s competitive advantage. The ability to quantify deployments, model license volumes, and observe real usage creates a foundation for smarter pricing, targeted product development, and sharper go-to-market programs. As organizations grow more data-driven, the identity layer is a prime candidate for continuous monitoring and analysis.

Discovery is the first step. Modern data search makes it simpler to find, evaluate, and integrate the exact feeds needed for your identity research agenda. Exploring diverse categories of data ensures you don’t miss critical signals or over-rely on one source.

Data monetization is also reshaping the landscape. Many enterprises hold decades of procurement, telemetry, or deployment metadata that can be cleaned, aggregated, and made privacy-safe. Increasingly, organizations are looking to responsibly monetize their data, creating new streams of high-value intelligence that elevate market visibility for everyone.

Looking ahead, expect richer usage telemetry, deeper integration metrics, and standardized contract schemas to open new analytical possibilities. As AI techniques progress, entity resolution and signal fusion will become more automated, turning previously scattered identity breadcrumbs into crisp, decision-grade insight. The winners will be those who integrate these feeds early, validate continuously, and act decisively.

Appendix: Who Benefits and What Comes Next

Investors and financial analysts

Quant funds and fundamental analysts gain objective views of identity platform momentum with monthly updates. Installation counts, public-sector awards, and authentication volumes help triangulate revenue trajectories and customer growth. Procurement renewal data supports cohort modeling and retention estimates.

Consultants and market researchers

Advisory firms can replace anecdote with data, benchmarking SSO adoption by industry, mapping regional MFA penetration, and evaluating vendor consolidation patterns. With multi-signal models, analysts can defend their conclusions with hard numbers and transparent methodologies.

Cyber insurers and risk assessors

Insurers need to understand control maturity. Telemetry on MFA usage, presence of federation, and passwordless trends provides quantifiable indicators of reduced breach risk. This supports underwriting and pricing models that reflect the true state of controls in the insured portfolio.

Enterprise security leaders and procurement

CISOs and sourcing teams can benchmark pricing and license volumes, validate roadmap priorities against market adoption, and assess whether current deployments align with peer trends. Public-sector awards can inform vendor viability and long-term support considerations.

Product managers and go-to-market teams

PMs can track feature-level adoption (e.g., MFA mix or lifecycle management uptake), while sales leaders identify verticals with rising SSO penetration. Monthly cadence helps teams respond quickly to shifts—reallocating resources to geographies or segments showing the highest deployment growth.

The role of AI and the future of discovery

Decades-old documents, policy PDFs, and unstructured contract narratives still hide valuable signals. Advances in AI are making it practical to parse, normalize, and connect these artifacts to modern feeds—accelerating insight without sacrificing rigor. As you assemble training corpora for classifiers or entity resolution, follow best practices for sourcing high-quality training data. Ultimately, the organizations that excel will be those that embrace a culture of continuous discovery—scouting multiple types of data, validating against ground truth, and integrating new sources as they emerge via modern external data platforms.