analyticsROItooling

Measuring True Value: KPIs to Detect Underused Collaboration Platforms

qquickconnect

2026-02-04

9 min read

Detect underused collaboration platforms with DAU/MAU, engagement per seat, seat utilization, and integration metrics to drive consolidation and cut cost.

Hook: Your collaboration stack is costing more than you think — and metrics will show it

Teams add communication platforms to move faster. Months later the org is juggling licenses, duplicate integrations, and unhappy users — while finance still signs the renewal. If you’re a technology leader, developer, or IT admin asked to reduce cost and complexity in 2026, you need objective signals that separate indispensable platforms from shelfware. This guide defines the exact KPIs to quantify value, spot underused collaboration platforms, and make defensible retirement or consolidation decisions.

Why now: 2026 trends that make KPI-driven pruning essential

Late 2025 and early 2026 saw three shifts that raise the stakes for tooling decisions:

Vendors embedded generative-AI copilots across messaging products, increasing sticker price and vendor lock‑in risk for low-usage seats.
Enterprises doubled down on governance: SSO, SCIM provisioning, and API observability are now baseline expectations for procurement.
Economic scrutiny continues — buyers demand measurable ROI and expect clear seat utilization and cost-per-user justification.

Those trends make it pointless to rely on sentiment or random audits. You need hard KPIs that tie user behavior to cost and integration value.

The inverted pyramid: most important KPIs first

Prioritize these metrics in your governance dashboard. They give the fastest, highest‑confidence signals about underused collaboration platforms.

1. DAU / MAU ratio (stickiness)

What it measures: the proportion of monthly users who use a platform daily — a standard proxy for habitual use.

Formula: DAU / MAU

How to interpret:

> 0.30 — healthy, sticky; platform likely core to workflows.
0.10–0.30 — occasional use; needs context (project-based or team-limited use).
< 0.10 — low stickiness; candidate for consolidation or retirement.

Action: segment DAU/MAU by team and role. A low org-wide ratio can hide pockets of high-value use within specific groups.

2. Engagement per seat (activity density)

What it measures: average meaningful actions per licensed seat (messages sent, meetings created, files shared, automations run).

Formula (example): (messages_sent + reactions + files_uploaded + automations_triggered) / licensed_seats

Benchmarks & interpretation:

> 5 actions/seat/day — high engagement for messaging-first teams.
1–5 actions/seat/day — moderate; check role-based expectations.
< 1 action/seat/day — low activity; consider seat reductions or consolidation.

Action: exclude bots and system accounts. Weight actions by value (automated deployment triggers or approvals may be worth more than a react).

3. Seat utilization (licensed vs active)

What it measures: percentage of paid seats that are actively used over a defined period (30/90/365 days).

Formula: active_seats / licensed_seats * 100%

Thresholds:

> 75% — efficient license consumption.
50%–75% — review provisioning and onboarding flows.
< 50% — over-licensed; immediate license rightsizing recommended.

Action: integrate with SCIM/HR systems to auto-deprovision stale seats. Consider shared or floating licenses for contributors and contractors.

4. Cost per active user (total spend efficiency)

What it measures: how much you pay for each active user — ties monetary spend to actual usage.

Formula: total_platform_cost / average_active_users

Action: calculate monthly and annualized views. Use this KPI to compare similar platforms (e.g., two chat tools). If cost per active user is much higher for one platform with similar engagement, it’s a consolidation candidate.

5. Integration usage and automation metrics

What it measures: how often integrations and automation APIs are invoked, and which integrations create business value.

Key sub‑metrics:

Integration invocation rate: number of integration calls per week/month.
Automation run rate: proportion of automations with >0 runs in the last 90 days.
Coverage: % of core systems with a working, used integration.
Redundancy: number of integrations that duplicate the same data flow across different platforms.

Action: rank integrations by business impact — e.g., deployment notifications, incident alerts, or sales pipeline updates. Low-use integrations with high maintenance cost are prime targets for removal. See a related case study on scaling automation for examples of integration-focused prioritization.

6. Overlap and redundancy score

What it measures: functional overlap between platforms (messaging, file sharing, meetings, task management).

How to compute a simple score:

List core capabilities (chat, voice, video, file storage, tasks, integrations).
For each platform, assign 1 if it supports a capability and is actively used for it; else 0.
Overlap score for capability = number_of_platforms_used_for_that_capability.

Action: capabilities with overlap score > 1 indicate consolidation opportunity. Prioritize retiring the platform with lower engagement and higher cost per active user.

How to implement these KPIs: data sources, queries, and dashboards

Collecting the right data requires instrumenting multiple sources: vendor usage APIs, SSO/SCIM logs, billing systems, and integration platforms (iPaaS, webhook logs). Below are practical steps and example queries.

Data sources to connect

Vendor usage APIs (messages, files, meetings, integrations triggered).
SSO and provisioning logs for last authentication and provisioning dates.
Billing and procurement data for seat counts and contract dates.
Integration platform logs (Zapier, Workato, internal middleware) for invocation counts.
HR system for FTE counts and role-based segmentation.

Sample SQL for key metrics

Assume a usage_events table: (user_id, event_type, platform, event_time)

-- DAU per day
SELECT event_date, platform, COUNT(DISTINCT user_id) AS dau
FROM (SELECT DATE(event_time) AS event_date, user_id, platform FROM usage_events)
GROUP BY event_date, platform;

-- MAU (last 30 days) and DAU/MAU
WITH mau AS (
  SELECT platform, COUNT(DISTINCT user_id) AS mau
  FROM usage_events
  WHERE event_time >= CURRENT_DATE - INTERVAL '30 days'
  GROUP BY platform
),
 dau AS (
  SELECT platform, COUNT(DISTINCT user_id) AS dau
  FROM usage_events
  WHERE DATE(event_time) = CURRENT_DATE
  GROUP BY platform
)
SELECT d.platform, d.dau, m.mau, ROUND(d.dau::numeric / NULLIF(m.mau,0), 3) AS dau_mau
FROM dau d
JOIN mau m USING (platform);

-- Engagement per seat (30 day window)
SELECT platform,
  (SUM(CASE WHEN event_type IN ('message','file_upload','reaction','automation_run') THEN 1 ELSE 0 END)::float)
  / NULLIF(licensed_seats,0) AS engagement_per_seat
FROM usage_events u
JOIN platform_licenses p ON u.platform = p.platform
WHERE u.event_time >= CURRENT_DATE - INTERVAL '30 days'
GROUP BY platform, licensed_seats;

Dashboard layout and alerts

Build a single-pane view with these panels:

DAU/MAU by platform + trend line (90/180 day).
Seat utilization heatmap by department.
Cost per active user and contract renewal dates.
Integration invocation leaderboard and stale integrations list.
Overlap matrix: capabilities vs platforms.

Set alerts for:

DAU/MAU drops > 20% quarter-over-quarter.
Seat utilization < 50% for > 60 days.
Automations not run in 90 days but still maintained.

Decision framework: retire, consolidate, or keep?

Use a weighted scoring model combining the KPIs. Example weights (adjust to your org):

DAU/MAU: 30%
Engagement per seat: 25%
Seat utilization: 15%
Cost per active user: 15%
Integration usage & business impact: 15%

Compute a composite score (0–100). Suggested action thresholds:

> 70 — keep and optimize.
40–70 — consider consolidation or targeted rightsizing.
< 40 — candidate for retirement; start a sunset plan.

Sunset checklist for retiring a platform

Map active integrations and data flows — export configuration and retention policies.
Notify stakeholders and identify alternate platforms for affected workflows.
Plan data migration or archival (retain audit logs for compliance).
Gradually reduce licenses and monitor user impact for 30–90 days.
Terminate contract after validation and ensure account deprovisioning.

Real-world example (anonymized & condensed)

Company X had three collaboration tools across engineering and sales. Using the KPIs above they found:

Tool A: DAU/MAU = 0.42, engagement/seat = 6, cost per active user = $8/mo — core to engineering.
Tool B: DAU/MAU = 0.09, engagement/seat = 0.8, cost per active user = $24/mo — used by a small marketing group.
Tool C: DAU/MAU = 0.18, engagement/seat = 2.1, cost per active user = $12/mo — used for meetings and one integration.

Overlap showed both B and C used for announcements and light file sharing. Integration metrics showed the single valuable integration lived in Tool C. After scoring, Company X:

Retired Tool B, saving 30% in annual spend.
Consolidated necessary meetings into Tool C and migrated the integration to Tool A for better maintainability.
Saved engineering time by removing duplicate webhook handlers and reduced vendor count from 3 to 2.

Security, compliance, and governance signals

KPI decisions must include non-usage factors:

SSO adoption: platforms not supporting SSO/SCIM complicate provisioning — downgrade score.
Data residency & retention: legal requirements may force keeping a tool even with low usage. See guidance on sovereign cloud controls for architects.
Audit logs: platforms with robust logs reduce risk and may deserve higher weight despite lower engagement.

Action: Add binary gates to your decision model for critical compliance requirements. If a platform fails a gate, escalate instead of retiring silently.

Advanced strategies for 2026 and beyond

Leverage these next-level tactics as vendor APIs and observability improve:

Instrument the work graph: correlate events across tools to see end‑to‑end workflows (ticket ➜ chat ➜ deploy). This reveals hidden value not apparent in single-platform metrics. Tie this to an evolving tag architecture so you can trace cross-tool flows.
Score integrations by business outcome: tie automation runs to SLOs such as incident MTTR reduction or lead response time improvements. Case studies on automation can help you map integration impact.
Use anomaly detection: train models on historical usage to spot sudden drops or growth that need fast response.
Negotiate outcome-based contracts: with clear KPIs to pay for impact, not just seats.

Common pitfalls and how to avoid them

Relying on sentiment only: surveys help but must be validated with behavioral data.
Ignoring power users: a platform with low org-wide DAU/MAU can still be mission-critical for a small team. Use role segmentation.
Failing to account for seasonality: project-based tools may show low utilization outside active windows — evaluate over 6–12 months.
Not automating rightsizing: manual license audits are slow and error-prone. Use SCIM-driven automation for deprovisioning.

Actionable roadmap: 90-day plan to detect and retire underused platforms

Week 1–2: Inventory all collaboration platforms, contracts, and licensing models.
Week 3–6: Connect vendor usage APIs and SSO logs into a centralized analytics store.
Week 7–8: Populate KPI dashboard (DAU/MAU, seat utilization, engagement per seat, integration usage).
Week 9–10: Score platforms using the weighted decision model and identify candidates.
Week 11–12: Run stakeholder reviews, plan sunsets, and begin staged deprovisioning.

“Objective metrics remove politics from tool decisions and free engineering time for real work.”

Key takeaways

DAU/MAU is your primary stickiness indicator — segment by role.
Engagement per seat and seat utilization turn behavioral signals into license optimization actions.
Integration metrics reveal hidden business value or maintenance burden.
Use a weighted scoring model and include compliance gates before retiring platforms.
Automate audits and rightsizing with SCIM/SSO integration to sustain savings.

Call to action

Ready to turn your collaboration stack into measurable ROI? Start by instrumenting DAU/MAU, seat utilization, and integration metrics — and let QuickConnect help automate data collection, rightsizing rules, and sunset workflows. Request a demo to see a prebuilt KPI dashboard tailored to engineering and IT teams.

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