Prompt

compare usage by role plan company size

Technology / Analytics & BI1 observationLast seen Oct 15, 2026

Latest observation

Oct 15, 2026OpenAI APIWeb search: off

Here’s a practical way to compare usage by role, plan, and company size.

1) Usage by role

Look at how different job functions use the product.

Common roles to compare:

  • Admin / IT
  • Manager / Team lead
  • Individual contributor
  • Executive / VP
  • Operations / Support
  • Sales / Marketing

Useful metrics:

  • Average logins per user
  • Feature adoption by role
  • Time spent in product
  • Actions per active user
  • Retention / repeat usage

What to look for:

  • Which roles are most active
  • Which roles use advanced features
  • Whether admins are more active than end users
  • Whether executives are low-frequency but high-impact users

2) Usage by plan

Compare behavior across subscription tiers.

Typical plan segments:

  • Free
  • Starter
  • Pro
  • Business
  • Enterprise

Useful metrics:

  • Active users per account
  • Feature usage rate
  • Conversion from trial to paid
  • Expansion/upgrade rate
  • Churn by plan

What to look for:

  • Whether higher-tier plans drive deeper usage
  • Which features are reserved for premium plans
  • Whether free users are active but limited
  • Whether enterprise customers use the product more broadly across teams

3) Usage by company size

Compare usage across customer organization size.

Common buckets:

  • Small: 1–10 employees
  • SMB: 11–50
  • Mid-market: 51–250
  • Large enterprise: 251+

Useful metrics:

  • Seats used vs seats purchased
  • Active users per account
  • Usage frequency per user
  • Team-wide adoption
  • Department-level penetration

What to look for:

  • Small companies may have higher per-user usage
  • Large companies may have more users but lower individual engagement
  • Mid-market may show the best balance of breadth and depth
  • Enterprises may need onboarding to improve adoption

Best way to present the comparison

Use a table like this:

SegmentMetric 1Metric 2Metric 3Key insight
Role
Plan
Company size

Or a matrix:

SegmentHigh usageLow usageNotes
RoleManagerExecutive
PlanEnterpriseFree
Company sizeMid-marketLarge enterprise

Recommended analysis approach

  1. Define “usage” clearly
  2. Segment users by role, plan, and company size
  3. Compare core metrics side by side
  4. Normalize by account size or active users
  5. Highlight the biggest differences and trends

If you want, I can also turn this into:

  • a dashboard spec
  • a SQL query
  • a presentation slide
  • or a short executive summary

Observation history

How did Obsurfable measure this prompt?

Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.

Which AI systems does Obsurfable collect answers from?

OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, Meta AI, Qwen.

How can brands improve their AEO?

Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.

Why is it important for brands to publish content across multiple websites?

Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.

Want this interpreted for your brand?

Explorer is the free public corpus. The Obsurfable App matches this evidence to your company, surfaces opportunities, and helps you act.