Analyzing Conversion Rates

If you can tell me the conversion rate of a female, mobile user in Wells, Nevada visiting your website via LinkedIn on a Saturday, then you understand how to find conversion rates that actually matter.

As Google Analytics expert Avinash Kaushik says, “All data in aggregate is crap.” That goes double for analyzing conversion rates.

As an example: Somewhere there’s a search marketer telling their boss, “For visitors coming from Google, our eCommerce conversion rate is 4.5%.”

Let’s congratulate this person on re-vomiting data without giving any insight. Insight requires that you ask, “Why?” And from there you’ll begin segmentation of your data.

How it works: The 4.5% conversion rate number is just an average of a bunch of other numbers.

In this example, let’s say that the company whose conversion rate from Google is 4.5% sells flowers. When we dig into their search traffic data, we find that the visitors are evenly divided between people who are looking for purple flowers, pink flowers, red flowers, yellow flowers, and blue flowers.

We know these are the visitors’ search terms because we can see the web page URL that they landed on. If they landed on a page where they can only buy yellow flowers, and yellow flowers is in the title tag, they must have been using search phrases that have those keywords in them.

When we start to measure conversion rate by search term (i.e. landing page) we see that the purple flowers landing page leads the way with a 10.2% conversion rate – over 2x the average rate!

Yellow flowers on the other hand converts only 1.5% of its search traffic, 66% less than the average.

When you export this data into an excel sheet from Google Analytics, it will look something like this:

anna colibri, cort tafoya, academy x, analyzing conversion rates
Screenshot: Excel spreadsheet

Now we know what is making up that 4.5% conversion rate, and we can develop a to-do list to improve things.

Actions: Fix the landing page for yellow flowers! It’s performing terribly. Why is that? Is there not enough selection? Are their bad user reviews on this page? Maybe a button isn’t working? The good news is, based on the analysis you’ve done, you know there’s room for improvement.

On the flip side, purple flowers must be in season! You can share that content more on social media. Identify where you rank for purple flowers – what if you’re only in position 7 on page 1? With how much you’re converting, doesn’t it make sense to build backlinks to that page so you can get up to position #1? You’d be getting 10x the traffic – and you know that traffic converts much better than other search traffic.

Creating different segments in Google Analytics will help when analyzing conversion rates: What we’ve done here can be taken many steps further. What if we find out that there are even higher converting people who are located in California and they most often purchase goods at night?

If we know how to make segments in Google Analytics, we can figure this stuff out.

For information on creating segments, use Google’s own documentation as a resource. In the screenshot below, you can see that nearly any visitor segment you can think of can be created if you know how to set up the right rules and conditions.

anna colibri, cort tafoya, academy x, analyzing conversion rates
Screenshot: Google Analytics (

You can compare up to 4 segments at a time in Google Analytics. The example below shows how the data is displayed in GA.

anna colibri, cort tafoya, academy x, analyzing conversion rates 3
Screenshot: Google Analytics (

If you wanted, you could combine all of these attributes into one big segment – people who are 25-34, on their mobile device and in S.F.

Go forth and gain insights from your data by analyzing conversion rates – then take action to improve your marketing efforts!

Cort Tafoya is a branch manager and marketer for AcademyX, a software, web development and digital marketing training company with facilities in San Francisco, Sacramento, Los Angeles, San Jose and San Diego.

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