Use Case March 10, 2026 8 min read

Microsoft Clarity for Agencies: Automated Client Reporting

Agencies managing 10, 20, or 50 client websites face a reporting challenge: clients want clear, actionable insights about their site's UX — not raw data dumps. Microsoft Clarity provides excellent behavioral data for free, but turning it into professional client reports is a manual, time-consuming process. Here's how to set up Clarity across client sites and automate the reporting that keeps clients happy.

Why Agencies Should Use Clarity

For agencies, Clarity solves a specific problem: it provides high-value UX insights at zero cost per client. When you're managing margins across dozens of accounts, paying per-seat or per-session fees for heatmap tools quickly becomes unsustainable.

Here's what makes Clarity compelling for agencies:

Multi-Project Setup for Agencies

Clarity uses "projects" to separate different websites. Each project has its own dashboard, recordings, and data. For agencies, the recommended setup is:

One project per client domain

  1. Log into Clarity with your agency Microsoft account
  2. Create a new project for each client website
  3. Name projects consistently: "ClientName — domain.com"
  4. Install the project-specific tracking code on the client's site

Team access management

Clarity lets you add team members to specific projects. For agencies, this means:

Tip: Create a naming convention early and enforce it. When you have 30+ projects, "John's site" and "test project 2" become impossible to manage. Use "ClientName — primarydomain.com" consistently.

What Clients Actually Want in Reports

This is where most agencies struggle. You have access to rich behavioral data in Clarity, but clients don't want:

What clients do want:

Building a Client Report from Clarity Data

Here's a practical framework for a monthly or bi-weekly client UX report using Clarity data.

1. Executive summary (1 paragraph)

Write 2-3 sentences covering the overall site health: total sessions, engagement rate trend, and the single most important finding this period.

2. Key metrics dashboard

Metric This Period Previous Period Trend
Total Sessions12,45011,200+11%
Engagement Rate62%58%+4pp
Avg. Scroll Depth47%44%+3pp
Rage Click Rate4.2%5.1%-0.9pp
Dead Click Rate8.7%8.3%+0.4pp

3. Top issues found (3-5 items)

For each issue, include:

4. Page-level analysis

Cover the client's 5-10 most important pages individually. For each, report scroll depth, frustration signals, and any notable behavior patterns from recordings.

5. Impact of previous recommendations

If the client implemented fixes you recommended last period, show the before/after data. This demonstrates ROI and justifies continued UX work.

The Manual Reporting Problem

The framework above produces excellent reports. The problem is time. For a single client, building this report takes:

That's roughly 90 minutes per client. With 15 clients, you're spending over 22 hours per month just on Clarity reporting. At agency billing rates, that's a significant cost — and most of the time is spent on data gathering, not analysis.

Automating the Data Collection

Clarity offers a data export API that can pull metrics programmatically. This eliminates the manual dashboard-checking step, but has limitations:

To build a complete picture, you need to collect data daily and accumulate it over time. This is feasible with a script but requires infrastructure to run reliably.

Basic automation approach

# Daily collection script (simplified)
import requests
import sqlite3
from datetime import date

PROJECTS = {
    "client-a": "project_id_1",
    "client-b": "project_id_2",
    # ... all client projects
}

for client, project_id in PROJECTS.items():
    response = requests.get(
        f"https://www.clarity.ms/export-data/api/v1/"
        f"project-live-insights",
        headers={"Authorization": f"Bearer {API_TOKEN}"},
        params={"projectId": project_id, "numOfDays": 1}
    )
    # Store in database
    save_to_db(client, date.today(), response.json())

White-Label Reporting

Agency clients expect reports that look like they come from your agency, not from a third-party tool. White-labeling Clarity data means:

How ClarityInsights Solves the Agency Problem

ClarityInsights was designed with multi-project workflows in mind. Instead of manually pulling data from each client project, it automates the entire pipeline:

For an agency with 15 clients, this replaces 22+ hours of monthly reporting work with a setup that takes 30 minutes once.

Client Onboarding Checklist

When adding a new client to your Clarity-based reporting workflow:

  1. Create Clarity project: Use your naming convention (ClientName — domain.com)
  2. Install tracking code: Add the Clarity snippet to the client's site, ideally through their tag manager
  3. Configure masking: Set appropriate content masking mode (especially important for e-commerce or form-heavy sites)
  4. Identify key pages: List the 5-10 most important pages for this client (homepage, pricing, checkout, top landing pages)
  5. Set up custom tags: If the client has specific user segments (logged in vs. anonymous, plan types), configure custom tags
  6. Baseline report: Wait 2 weeks for data, then generate a baseline report before making any changes
  7. Define KPIs: Agree on which Clarity metrics the client cares about (engagement rate, frustration signals, scroll depth on key pages)

Tip: Send the first report with a 15-minute walkthrough call. Once clients understand what the metrics mean and how to read the report, they'll look forward to receiving them — and they'll trust your recommendations more.

Pricing Your UX Reporting Service

Since Clarity is free, the cost of offering UX reports is primarily your time. Agencies typically price this in one of three ways:

With automated reporting, the marginal cost of adding another client approaches zero — making this a high-margin service for agencies at any pricing model.

Stop analyzing Clarity data manually

ClarityInsights sends you AI-powered weekly reports with per-page analysis, frustration signals, and prioritized recommendations.

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