Which Keap dashboard should you build first with Make.com?

Build the dashboard that answers your most expensive unanswered question. If you don't know which lead sources produce revenue, start with the Lead Source ROI dashboard. If deals stall and you don't know where, build the Pipeline Velocity dashboard first.

Does Make.com connect directly to Keap's API?

Yes. Make.com includes native Keap modules that connect to Keap's API without custom code. These modules cover contacts, orders, opportunities, tags, campaigns, tasks, and notes—the core data entities needed for all seven dashboards described here.

What reporting tools work best as a destination for Keap data pulled by Make.com?

Google Sheets paired with Looker Studio is the most accessible combination for most teams. Google Sheets acts as a live data layer that Make.com writes to on a schedule, and Looker Studio connects to those sheets to produce visual dashboards that update automatically.

How often should Make.com scenarios run to keep dashboards current?

Most operational dashboards—pipeline velocity, lead source ROI, sales rep scorecard—run well on a daily schedule. Customer lifetime value dashboards work on a weekly cadence. Churn risk dashboards benefit from daily runs so the alert queue is fresh each morning.

7 Custom Keap Reporting Dashboards You Can Build With Make.com in 2026

By Jack DeePublished On: August 22, 2025

Keap’s native reporting gives you a high-level view—but not the granular, cross-system intelligence that drives real decisions. Make.com fills that gap by extracting, transforming, and routing your Keap data into custom dashboards that reflect your actual KPIs, updated automatically without manual exports.

If you’ve ever exported a Keap report to a spreadsheet and spent an hour reformatting it, you already know the problem. Native CRM reporting tools are built for the average user—not for the operator who needs to cross-reference lead source efficiency with customer lifetime value, or track which automation sequences actually close deals. For that level of visibility, you need to move data out of Keap and into a purpose-built reporting layer.

Make.com scenarios are the most practical way to build that layer. They connect Keap’s API to spreadsheets, databases, and visualization tools—on a schedule, or triggered by events in real time. Before you build anything, though, it pays to run a discovery audit on your current data flows so you’re pulling the right fields from the start. And if you’re weighing automation platforms, the Make vs. Zapier comparison for 2026 makes a strong case for why Make.com handles data transformation work like this more cleanly.

Below are seven specific dashboards worth building—what each one tracks, how the Make.com scenario works, and why it produces better decisions than anything Keap shows natively.

Dashboard	Primary Data Source in Keap	Recommended Destination	Update Frequency
Lead Source ROI	Contacts + Tags + Orders	Google Sheets / Looker Studio	Daily
Pipeline Velocity	Opportunities + Stage History	Google Sheets	Daily
Email Sequence Performance	Campaigns + Email Stats	Looker Studio	Daily
Customer Lifetime Value	Orders + Contacts	Google Sheets / BI Tool	Weekly
Tag-Based Segment Health	Tags + Contacts	Google Sheets	Daily
Sales Rep Activity Scorecard	Tasks + Notes + Opportunities	Google Sheets / Looker Studio	Daily
Churn Risk Early Warning	Orders + Tags + Last Contact Date	Google Sheets + Slack Alert	Daily

1. Lead Source ROI Dashboard

This is the dashboard most Keap users need first and build last. It answers a single question: which lead sources are producing revenue, not just contacts?

Keap tracks the lead source field on contact records and associates orders with those contacts. But the native view doesn’t combine them into a revenue-by-source summary automatically. A Make.com scenario solves this by pulling all orders created in the last 24 hours, joining each order to its associated contact record, extracting the lead source field, and appending a row to a Google Sheet that aggregates revenue by source over time.

Once that sheet feeds a Looker Studio dashboard, you get a live view of cost-per-lead versus revenue-per-lead by channel—the kind of data that tells you where to increase ad spend and where to cut it. This is one of the clearest examples of data synchronization creating direct business value.

Make.com scenario structure: Schedule trigger (daily) → Keap: Search Orders (date filter: last 24 hours) → Iterator → Keap: Get Contact by ID → Google Sheets: Add Row (lead source, order value, date).

2. Pipeline Velocity Dashboard

Pipeline velocity tells you how fast deals move from first contact to closed—and where they stall. Keap tracks opportunities and their stages, but it doesn’t calculate average time-in-stage or flag deals that have gone stagnant.

A Make.com scenario runs nightly, pulls all open opportunities, reads the current stage and the date the opportunity was created, and writes the data to a Google Sheet. A second column uses a formula to calculate days-in-stage. A Looker Studio dashboard then visualizes average velocity by stage and highlights deals that have been in the same stage for more than a threshold number of days.

This dashboard is particularly useful for sales managers who are currently learning about stalled deals through weekly one-on-ones rather than through data. The same logic that makes certain automation builds faster with AI assistance applies here—the scenario structure is straightforward enough to set up without a developer once you understand the module sequence.

Make.com scenario structure: Schedule trigger (nightly) → Keap: Search Opportunities (status: open) → Iterator → Google Sheets: Update Row or Add Row (opportunity ID, stage, created date, owner).

3. Email Sequence Performance Dashboard

Keap shows open rates and click rates per email. It does not show you how a full sequence performs as a funnel—what percentage of contacts who receive email 1 ultimately purchase after email 5, segmented by the tag they carried when they entered the sequence.

Building this requires two Make.com scenarios working together. The first pulls daily email statistics from Keap’s campaign reporting endpoints and writes them to a staging sheet, tagged by sequence and send date. The second pulls order data and matches purchases to contacts who received specific campaign emails within a defined window. The resulting dataset lets you build a Looker Studio funnel view that shows sequence-level conversion rates—not just email-level engagement metrics.

This is the reporting layer that separates teams running email marketing from teams optimizing it. For context on what full-stack automation looks like when applied to recruitment workflows, Nick’s case study on eliminating manual handoffs shows a similar pattern of connecting data sources that don’t natively talk to each other.

Expert Take

The single biggest mistake teams make when building Keap reporting is pulling data at the contact level and stopping there. The insight is almost always in the join—contacts to orders, emails to purchases, tags to outcomes. Make.com’s iterator and aggregator modules exist precisely for this: they let you walk through a list of records, fetch related data from a second Keap endpoint, and combine the results before they ever reach your spreadsheet. Build the join into the scenario, not the spreadsheet formula, and your dashboard stays clean no matter how many records accumulate.

4. Customer Lifetime Value Dashboard

Customer lifetime value (CLV) is one of the most cited metrics in business and one of the least actually calculated. Most Keap users have the raw data to compute it—order history, contact records, acquisition source—but no automated way to aggregate it per customer over time.

A weekly Make.com scenario pulls all orders from the last seven days, groups them by contact ID using an aggregator module, and writes a summary row per contact to a Google Sheet that includes total revenue to date, number of orders, average order value, and days since first purchase. A second scenario runs once a week to recalculate CLV cohort averages by lead source and product category.

The output is a dashboard that shows not just who your best customers are, but which acquisition channels produce customers with the highest lifetime value—a fundamentally different question than which channels produce the most leads. Understanding how to build a single source of truth for business data is the foundation this kind of dashboard requires.

Make.com scenario structure: Schedule trigger (weekly) → Keap: Search Orders (date filter: last 7 days) → Aggregator (group by contact ID, sum order value) → Google Sheets: Add or Update Row.

5. Tag-Based Segment Health Dashboard

Tags are the backbone of Keap’s segmentation system. Most businesses accumulate hundreds of tags over time—some active, some orphaned, some applied by automations that no longer run. Without a dashboard, there’s no way to know how many contacts carry each tag, whether tag populations are growing or shrinking, or whether critical behavioral tags are being applied at the expected rate.

A Make.com scenario runs daily and loops through a defined list of strategic tags. For each tag, it queries Keap to count the number of contacts currently carrying that tag and writes the count to a date-stamped row in a Google Sheet. Over time, this sheet becomes a time-series dataset that shows tag population trends—which lets you spot when a lead nurture sequence stopped applying its entry tag, or when a churn-risk tag population suddenly spikes.

This is the kind of operational visibility that prevents the scenario where a broken automation goes unnoticed for weeks because nobody was watching the downstream data. The same discipline applies when evaluating any Make scenario before it goes to production—you need monitoring built in from day one.

Make.com scenario structure: Schedule trigger (daily) → HTTP: Keap API (search contacts by tag, return count) → Iterator (loop through tag list) → Google Sheets: Add Row (tag name, count, date).

6. Sales Rep Activity Scorecard

If your sales team logs calls, notes, and tasks in Keap, you already have the data for a per-rep activity scorecard. The problem is that Keap doesn’t surface this as a comparative view across reps. You can look at one rep’s activity log, but you can’t quickly see that one rep completed 40 tasks last week and another completed 8.

A Make.com scenario pulls all tasks completed and notes created in the last 24 hours, groups them by assigned user, and writes daily activity totals to a Google Sheet. A separate sheet tab tracks opportunity stage changes by owner over the same period. The Looker Studio dashboard built on top of these sheets gives sales leadership a daily scorecard without requiring anyone to manually compile reports.

This connects directly to pipeline accountability. When managers can see activity data in real time, coaching conversations shift from anecdotal to evidence-based. The efficiency gains mirror what happens when manual data entry is eliminated from operational workflows—the time previously spent compiling the report goes toward acting on it.

Expert Take

Sales scorecards built from CRM data only work if the team trusts the data. Before building this dashboard, audit whether your reps are actually logging tasks and notes in Keap consistently. If they aren’t, the scorecard will show inaccurate activity levels and erode trust in the reporting system. Fix the logging behavior first—often a simple Make.com reminder automation that prompts reps to log same-day activity is enough—then build the dashboard on top of clean data.

7. Churn Risk Early Warning Dashboard

Churn risk dashboards are typically thought of as a tool for SaaS companies, but any business with repeat purchase cycles benefits from one. In Keap, the signals are already there: last order date, number of orders in the last 90 days, days since last meaningful interaction, and whether a contact carries an active engagement tag.

A Make.com scenario runs daily and queries Keap for contacts whose last order date exceeds a defined threshold (for example, 60 days for a business with a 30-day repurchase cycle). For each flagged contact, the scenario checks whether they carry an active outreach tag. If they don’t, it writes their record to a Google Sheet and sends a Slack alert to the account owner. This creates a daily churn risk queue that a sales or retention team can work through each morning.

The scenario can also apply a Keap tag to flagged contacts, triggering an automated re-engagement sequence—closing the loop between reporting and action without any manual intervention. This is the difference between a dashboard that shows you problems and one that starts solving them. For teams evaluating how deep this kind of automation logic can go, the case study on automating processes with no native Make module shows the ceiling is higher than most assume.

Make.com scenario structure: Schedule trigger (daily) → Keap: Search Contacts (last order date filter) → Filter (no active tag) → Google Sheets: Add Row + Slack: Send Message → Keap: Add Tag (triggers re-engagement sequence).

How Do You Choose Which Dashboard to Build First?

Start with the decision you’re currently making blindly. If you don’t know which lead sources are producing revenue, build the Lead Source ROI dashboard first. If deals are stalling and you don’t know where, build the Pipeline Velocity dashboard. The right order is the order that answers your most expensive unanswered question.

Before building any of these, verify that the underlying Keap data is clean. Make.com can extract and transform data, but it can’t fix missing lead source fields or incomplete order records. A quick audit of your Keap data quality—checking field completion rates on key records—will save hours of troubleshooting later. The seven questions to ask before automating anything apply directly here: garbage in, garbage out is still the governing principle regardless of how sophisticated the scenario is.

If you’re new to Make.com and this is your first data pipeline build, start with the Tag-Based Segment Health dashboard. It has a simple scenario structure—a loop through a defined list that writes counts to a sheet—and it produces immediately visible results that build confidence in the approach before you tackle more complex multi-endpoint joins.

For teams that have been using Zapier and are considering the switch, the Make.com FAQ for Zapier users addresses the most common questions about scenario structure differences. And if you want to understand whether building these yourself or working with a partner makes more sense for your current situation, the DIY vs. Make partner guide for 2026 lays out the decision criteria clearly.