The Integration Adoption Report: what 1,000+ teams connect first to their analytics stack (2026)

We see the choice of first integration as a tell. It reveals what a team thinks its analytics problem actually is. A founder who connects Google Sheets first is solving "I have data in a spreadsheet and need it in Slack." A mid-market RevOps lead who connects HubSpot first is solving "the CEO keeps asking me about pipeline."

This report summarizes the first-source-connected data from 3,100+ Chartcastr workspaces(sample) that completed at least one source connection in Q1 2026. Full per-cell numbers and methodology live on the integration adoption benchmark.

The headline distribution

For workspaces with company-size metadata, the first-source distribution looks like this:

The pattern is clean enough to be a useful frame for any team thinking about where to start.

Why Google Sheets dominates the early funnel

Google Sheets is the de facto database of small teams. Founders track signups, customers, contracts, and sometimes finances in a spreadsheet long before they consider a "real" data tool. When that team starts pushing metrics to Slack, the sheet is where the data already is.

This is not a temporary state. Plenty of 30-person companies still run their core dashboards out of Sheets, and they're not wrong to — the tool fits the problem. The shift to BigQuery happens when the volume of data outgrows the spreadsheet, not when the team feels guilty about not having a "real" warehouse.

If you're a small team wondering whether to skip Sheets and go straight to BigQuery: usually don't. The Sheets layer remains useful even after BigQuery arrives — most of our enterprise workspaces use Connected Sheets to BigQuery as the rendering surface for warehouse data.

The 50-employee inflection point

Between 11–50 and 51–200 employees, the distribution flips. Google Sheets drops from the dominant first source to a co-equal one; BigQuery and HubSpot rise.

The mechanism is mostly hiring. Around 50 employees, most companies hire their first data person — a BI lead or RevOps senior — and that person almost universally moves the analytics surface off Sheets. They want SQL. They want a warehouse. They want lineage. BigQuery is the default landing point because it's cheap, fast, and natively integrates with the Google tooling these teams already have.

The interesting consequence: the first integration in the workspace flips, but the workflow doesn't change as much as you'd think. The pulses are still going to Slack. The metrics are still daily revenue, MRR, pipeline coverage, and AR aging. Only the source has moved.

HubSpot, the universal second source

The most stable pattern in the data is HubSpot's role as second connection.

In every company-size bucket, HubSpot (or, for non-HubSpot teams, the equivalent CRM — Attio, Salesforce-via-warehouse) is the most common second integration. The reason: once the metric is in Slack, the next question is why did it change, and "why" lives in the CRM.

A typical sequence we see:

1. Connect Google Sheets, send daily revenue to Slack.
2. Two weeks later, connect HubSpot, add pipeline coverage to the same Slack channel.
3. A month later, connect a billing source (Stripe via BigQuery, or Xero), add MRR roll-up.
4. Quarterly: add product analytics (PostHog or Mixpanel) for activation/retention.

The shape is consistent. Revenue context arrives before product context, every time. This contradicts a common product-team intuition that "everyone wants to see DAU/MAU first." DAU/MAU is what product teams build first; it's not what companies connect first.

What this means by industry

Size isn't the only axis. When we slice by industry (inferred from email domain + workspace metadata):

• E-commerce teams skew heavily toward Shopify as the first source, regardless of size. A 200-person Shopify Plus store and a 5-person Shopify Lite store both start there.
• Agencies start with whichever client tool they manage most — Google Ads, Meta Ads, or a multi-source combination. The "first source" is fluid because the workspace structure mirrors the client portfolio.
• SaaS is the bucket the headline numbers describe most cleanly. The Sheets → HubSpot → BigQuery → PostHog progression is mostly a SaaS phenomenon.
• Finance / Accounting firms start with Xero (or the accounting equivalent) and add nothing for months. Pure delivery automation, no expansion of the source set.

What it doesn't measure

Two important caveats.

This is data about Chartcastr customers, not the SaaS market generally. We see teams who have chosen to push their data into Slack. Teams who use traditional BI exclusively, or who don't yet send any reports, are not in the denominator. So treat the percentages as descriptive of the push-analytics-adopting cohort, not the universe.

It also doesn't measure depth. "First connection" tells you what a team plugs in; it doesn't tell you what they actually pulse on a daily basis after the first month. Some workspaces connect everything immediately and only use one or two sources actively. We'll publish a depth-of-use companion benchmark next quarter.

Destinations, briefly

We didn't put destinations in the headline because the answer is boring: Slack is the destination, by an order of magnitude over every alternative. Across every size bucket, every industry, every region, Slack accounts for >70% of pulse deliveries.

Email is a distant second. Google Chat is rising but still small. WhatsApp is concentrated in agency and ecommerce workspaces, mostly outside North America. Microsoft Teams will be the interesting one to watch when the integration ships — we expect it to take meaningful share from Slack in enterprise.

How to use this

If you're picking where to start: the data agrees with intuition. Small team → Sheets first, CRM second. Mid-market → CRM first, warehouse second. Enterprise → warehouse first, CRM second, product analytics third.

If you're picking what to write — content marketers building integration guides, comparison pages, or use-case docs — the lesson is to weight your coverage by adoption density. A great post on "Google Sheets → Slack" reaches more teams than a great post on "Snowflake → Discord", even though the latter sounds more sophisticated.

We'll refresh this report quarterly. The benchmark page at /benchmarks/integration-adoption-by-team-size is the canonical numbers page. This post is the interpretation.

The broader frame for all of this is push analytics — the model that treats reporting as a delivery problem, not a dashboard problem. The choice of first source is the choice of what the team is willing to put on a schedule. That choice tells you everything about how the team thinks about their data.