About Analyfy

It started with a real question
That’s how Analyfy came to be

Analyfy grew out of marketing analytics projects, recurring questions and analyses worth doing again.

The first dashboard wasn’t meant to be a product. It gave clients a report they could open whenever they needed answers.

A question that kept coming up

Clients had to ask for each report and wait for an answer.

A report they could open anytime

One link gave clients the numbers they needed whenever a question came up.

A tool for deeper analysis

Useful analyses became reusable views, so the next client didn’t have to start from scratch.

Built on roughly a decade of marketing analytics experience

How we built it

A funnel chart was only the beginning

For the CRO dashboard, we needed to show stage conversion rates alongside the funnel and verify that the calculations were right.

What was the question?

How could we see the buying funnel and the conversion rates between stages in one place? Drawing the funnel was only part of the job.

How did we build it?

After comparing several approaches, we put the funnel and stage-by-stage conversion rates in one view using a single data source.

How did we check the results?

We manually verified the calculations against real data from several businesses. A good visualization still needs to show the right numbers.

Explore the CRO dashboard

Screenshot of Ecommerce CRO Dashboard — Side-by-side funnel comparison in Analyfy’s CRO dashboard

Full screenshot: Ecommerce CRO Dashboard — Side-by-side funnel comparison in Analyfy’s CRO dashboard

The value of a dashboard depends on the questions it can answer accurately.

We build tools to help people make better decisions with their data.

Founder of Analyfy

Amin Najmeddini

Marketing analyst LinkedIn profile

I built Analyfy’s tools from my work with businesses of different sizes in Iran and internationally. Every useful analysis in Google Analytics, Search Console or WooCommerce was an opportunity to improve the tools.

Aggregated data and connector limitations sometimes turned a single question into hours of research and testing. Understanding those limits is part of making analysis reliable.

Start with a real question Verify the calculations Understand the limits of the data

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