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Understand where software delivers value.

Application Intelligence shows you exactly where applications create friction and hidden cost, and where your people struggle to get work done.

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Understand where software <span class="gradient">delivers value.</span><br />

Application Intelligence

Traditional analytics show logins and clicks. Application Intelligence shows you what drives value, what creates friction, and how to fix it.

App Discovery
Map every application and track actual usage.
HEART Analytics
Understand if applications deliver value or create friction.
Portfolio Overview
Prioritize actions to optimize your entire software portfolio.

App Discovery

See which applications actually get used

Map every application your people touch – including shadow IT and unauthorized tools. Spot vendor consolidation opportunities, identify duplicate subscriptions, and flag AI tools that may pose compliance risks.

  • License utilization analysis showing inactive seats
  • Shadow IT identification to surface unauthorized services
  • Vendor consolidation opportunities across similar tools
  • AI tool detection across the browser for governance and risk management

Find out which tools and AI applications your teams actually use, which sit idle, and where your budget goes to work that never happens.

Portfolio Overview

Prioritize actions across all applications

Roll up adoption, cost, and risk data across your entire software estate. Get a ranked list of actions: which licenses to cut, which workflows need help, which processes need fixing, and which applications deliver measurable ROI.

  • Cross-application performance dashboard
  • Budget allocation recommendations
  • Risk identification across your portfolio
  • ROI tracking for software investments

Whether you’re a CIO optimizing enterprise spend, a CFO proving technology value, or a department leader managing a function’s tools, see the complete picture and make decisions backed by usage data.

HEART Analytics

Understand the value your software delivers

Userlane’s HEART Analytics tell you whether applications justify their cost. By correlating user attributes – like user roles and departments – with real-time usage patterns across workflows and applications, HEART uses intelligence-led insights to help you understand what’s working and where to focus next.

  • Happiness scores from in-app surveys
  • Engagement tracking across features and workflows
  • Adoption measurement against expected usage
  • Retention analysis showing which users return
  • Task success rates for critical processes

See which applications help people get work done and which create friction that increases support costs. Find out where training resources are misallocated and where software investments pay off. HEART works across any browser-based application, including AI tools – so you can measure adoption of software and AI across teams, roles, and sites.

The impact of Application Intelligence

Application Intelligence doesn’t just report activity – it reveals actionable insights for all stakeholders:

  • IT justifies technology decisions with data.
  • Finance defends budget allocation with proof.
  • Department leaders demonstrate software value with usage metrics.


From data to decisions:

  • Instead of guessing which applications work, you know.
  • Instead of renewing everything by default, you make data-backed decisions.

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Frequently Asked Questions

Application Intelligence is Userlane's analytics layer that shows how enterprise software is actually being used. It combines App Discovery (which apps are in use), HEART Analytics (how well they're adopted), and Portfolio Overview (where to invest or cut). Leaders get one view to identify unused licenses, measure adoption, and prove software investments deliver value.

Application Intelligence correlates user attributes (role, department, tenure) with real-time behavioral data (logins, feature usage, task completion, errors). AI analyzes these patterns to show which user segments succeed, which struggle, and where in workflows friction occurs — you can target interventions and allocate budgets accordingly rather than guess.

HEART Analytics provides a neutral, standardized score (0–100) measuring software adoption across five dimensions: Happiness, Engagement, Adoption, Retention, and Task Success. Use it to benchmark applications against peers, track value creation over time, and measure the business impact of changes - a new rollout, training program, or process improvement actually moved the needle.

Application Intelligence measures the gap between purchased licenses, assigned licenses, and active users. AI flags applications with significant gaps, typically identifying 5–15% license optimization opportunities. Portfolio Overview ranks these by savings potential.

Application Intelligence tracks whether training changes behavior by correlating completion data with subsequent HEART scores. Instead of "500 completed training," you can measure whether trained users actually complete tasks faster with fewer errors. Segment-level analysis reveals which approaches work for which audiences.

Application Intelligence measures five outcomes: time and cost to learn (user productivity), error rates (accuracy), support ticket volume (help desk burden), usage and adoption (feature utilization), and software spend efficiency (license optimization). HEART Analytics scores each at portfolio, application, and team levels - proving value and showing where to focus next.

Application Intelligence captures behavioral patterns - not passwords, form-field input values, keystrokes, or screen recordings. Customers control what is captured through analytics privacy settings. User attributes are pseudonymized and aggregated for segment analysis - sensitive data is replaced with identifiers. You see that "nurses in cardiology" struggle with a workflow, not which individual. Data collection complies with GDPR.

Most tools count clicks and logins. HEART measures outcomes and uses AI to provide insights across five dimensions, normalized against peer cohorts. Key differences: cohort-based scoring (HR systems compared to HR systems), segment-level correlation (which groups struggle and why), and confidence transparency (flags incomplete data).

Measuring AI adoption requires visibility into three things: which AI tools people actually use, how usage varies by team and role, and whether people stay engaged over time. Application Intelligence covers all three. App Discovery maps the AI services employees use in the browser, sanctioned or not. HEART and segment analysis show adoption by department, role, and location. Measurement covers browser-based AI tools, which include the web versions of most enterprise AI services.
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