How to Combine Stripe and Google Analytics Data on One Dashboard

The Problem: Two Dashboards, One Question

Every SaaS founder has the same question: which traffic is actually driving revenue?

Stripe tells you how much money came in. Google Analytics tells you how many people visited and from where. But neither tool tells you how they connect. You can see that revenue went up last month and that organic traffic went up last month, but was it the organic traffic that drove the revenue? Or was it the email campaign you ran? Or the Product Hunt mention?

To answer that question, you need both datasets on the same chart, on the same time axis, with comparable scales.

What You'll Learn From Combining This Data

When you overlay Stripe revenue with Google Analytics traffic data, several patterns typically emerge:

• Lag time. Most businesses see a 1-3 week delay between traffic increases and revenue increases. Visitors don't convert on day one. Understanding your specific lag helps you set realistic expectations for marketing investments.
• Channel effectiveness. If organic traffic correlates strongly with revenue but paid traffic doesn't, that's a clear signal about where to invest. Many founders are surprised to find that their highest-traffic channel isn't their highest-converting one.
• Seasonal patterns. Traffic and revenue may have different seasonal curves. E-commerce tends to see traffic rise before revenue (window shopping vs buying). SaaS tends to see them move more closely together.

Setting Up the Stripe Connection

Option 1: CSV Export

The fastest way to get started is with a CSV. Export your Stripe revenue data with dates and amounts. In TotalKPI, create a new data source and import the CSV. The parser auto-detects currency symbols and date formats.

Option 2: API Polling

For live, auto-updating data, connect to the Stripe API. Create an API data source in TotalKPI with your Stripe API endpoint. Set the authorization header with your API key, configure a JSONPath expression to extract the value you want (e.g., MRR, new customers, or payment volume), and set a polling interval.

TotalKPI polls the endpoint on your schedule and appends new data points automatically. Your revenue chart is always current without manual exports.

Importing Google Analytics Data

CSV Export

Export your Google Analytics session data or traffic-by-source data as a CSV. The key columns are date and the metric you want to track (sessions, users, pageviews, or a specific channel's traffic).

API Connection

Connect to the Google Analytics Data API to pull traffic data automatically. Configure the endpoint, authentication, and JSONPath extraction for the specific metric you want. Set polling to daily for traffic data.

Creating the Combined View

With both data sources in your workspace:

1. Click "Add Combined View"
2. Select your Stripe revenue source and your Google Analytics traffic source
3. TotalKPI immediately renders both on the same chart

The magic happens automatically. Your $45,000 MRR and your 150,000 monthly sessions are normalized to a 0-100% scale so the patterns are directly comparable. The Pearson correlation coefficient is calculated and displayed.

What the Overlay Reveals

The Revenue Lag

Most SaaS businesses see a lag between traffic changes and revenue changes. When you overlay the data, look for whether traffic peaks consistently appear 1-3 weeks before revenue peaks. If they do, you've found your acquisition-to-conversion cycle time.

This is incredibly valuable for planning. If you know that a traffic increase takes two weeks to show up in revenue, you can plan your content calendar and ad spend accordingly. You'll also stop panicking when you see a traffic spike that hasn't converted yet.

Which Traffic Converts

If Google Analytics lets you export traffic by source, create separate data sources for organic, paid, referral, and direct traffic. Overlay each one separately with Stripe revenue. The one with the highest correlation is likely your most effective acquisition channel.

Many founders discover that organic traffic has a much stronger correlation with revenue than paid traffic, despite paid traffic being more expensive to acquire. That's actionable intelligence for budget allocation.

Anomaly Detection

Overlaying the data makes anomalies stand out. If traffic stays flat but revenue drops, the problem is likely conversion or churn, not acquisition. If traffic drops but revenue holds steady, your existing customers are stable but your acquisition pipeline has a problem.

These patterns are invisible when the data lives in separate dashboards.

Using This Insight

Once you've identified the relationship between traffic and revenue:

• Double down on what converts. If organic traffic correlates strongly with revenue, invest more in SEO and content.
• Set realistic timelines. If there's a 3-week lag, plan campaigns 3 weeks before you need the revenue impact.
• Add annotations. Mark campaign launches, product changes, and pricing updates on your chart. Over time, you'll build a visual history of what moved the needle.

Try It With Your Own Data

Start a free trial and connect your Stripe and Google Analytics data. The overlay takes about 5 minutes to set up and the insights last as long as you track them.

Or explore the live demo to see combined charts in action.