Calculating True Conversion Rate in Google Analytics

Whenever I get a new account the first thing that I do is dramatically improve the conversion rate of the website along with campaign performance, visitors’ engagement and content consumption.  You may say, “We all do that eventually”. But there is a difference. I do it a bit faster….say within few seconds and that too without spending any time or money on website usability and other business issues.

The answer is simple, by abandoning Global Analytics. Yes Global analytics, the notorious brother of Google Analytics.  For example: following is the classical definition of Goal Conversion Rate in Google Analytics:

Goal Conversion Rate = (104,269 Goal Completions / 140,266 Visits)*100 = 74.34%

Similarly, in Google Analytics the e-commerce conversion rate is calculated as

E-Commerce Conversion Rate = (1,411 Transactions/140,317 Visits) * 100 = 1.01%

Now problem with such type of computation is that, we take every person on the planet into account while calculating conversion rate. The website in question sells clothing only in the US but get visits from around the world because of solid SEO and huge social media presence.

Since people from other countries won’t/can’t buy, you can’t hold them responsible for your conversions. Can you? But Google Analytics consider every person who has visited your website as your potential client and hence put everyone in the conversion funnel while calculating conversion rate.

There are more than 15000 visits from UK alone. These visits will never improve the bottom-line of my client’s business as they are not our target market. So what the people, who generated these visits, do on our website is irrelevant for tracking conversions, visitors’ engagement and content consumption. They are simply not our target market. No matter what you do, you can never generate sales and leads through them.  So they should be filtered out from the conversion funnel along with all those people who came from other countries.

So how do you calculate the True conversion rate?

Now let us calculate the real conversion rate of the website in question.

Step: 1 – Create an advanced segment in your analytics account which shows metrics only from your target market. For e.g.

Here I have created an advanced segment called ‘Real Data’ which include traffic only from my target market that is ‘United States’.

Step-2: Apply ‘Real Data’ advanced segment to your analytics reports and then determine your conversion rate and other metrics.

You can see how every metrics in your analytics reports has changed now. You are looking at the real data, the data which until now only handful of  super analytics ninjas were able to see.  All the metrics you see now is related only to your target market. Check the new and real Goal conversion rate: 77.11% earlier it was 74.34%. Congratulations you improved your conversion rate by 2.77%

Similarly, you can now calculate your real e-commerce conversion rate:

Real E-Commerce Conversion Rate = (1,411 Transactions/58,292 Visits) * 100 = 2.42%

So your real e-commerce conversion rate is actually more than double of what you analyzed earlier. This advanced segment not only help you with your conversions but also help you with all other important SEO metrics. You can now measure real campaign performance, real visitors’ engagement and real content consumption.

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Hi Himanshu,

I think in the end what matters is that the way you use to calculate the conversion rate must always be the same, but with this you have something more “real.”

Good post!

• http://www.seotakeaways.com/ Himanshu

Hi Natzir! I am afraid i have to disagree with you. The old way of calculating the conversion rate will give you poor insight about your target market. You need to consider only those visits which are from your target market because only they have the potential to convert at some point.

You’re right and in fact I usually have severals profiles where I filter traffic from each country. Sorry if I explained badly.

I wanted to say that with the new way you have more accurate data, but this doesn’t mean you will increase your conversions.
The important thing is that these KPIs must be always calculated the same way because otherwise data could be misinterpreted.

My earlier comment was only an advise, I didn’t disagree with you

• AnalyticsNerd

Thank you for posting this great article. Data segmentation is the key to analytics nirvana. I love the way you talked about conversion rates in this post but never mentioned the words ‘data segmentation’ anywhere. I think most marketers don’t really understand what these words mean and just overlook them everytime it is mentioned in an analytics post.

I would also highlight the importance of context in conversion rate. A CR by itself doesn’t give any useful insight. But when you measure trends of your CR over a period of time you get its context like whether conversions are going up or down over a period of time. Your definition of CR is more accurate than the traditional definition but it can certainly be improved. Since not every visit results in conversion, the CR should be calculated as goals/visitors-from-your-target-market. Again not evert visitor leads to conversion, so more accurate formula for CR should be goals/unique-visitors-from-your-target-market. Keep up the good work.

• http://www.seotakeaways.com/ Himanshu

Great comment and thank you. I agree with you and yes i am totally aware of what you think about conversion rate calculations. But i am deliberately giving anaytics doses in small quantity so that marketers get ample time to think and adapt. I have seen analysts giving a heavy dose in conferences and on blogs and it just didn’t work. I think even this small level of data segmentation can make a huge difference in the way marketers analyze their online campaigns and take business decisions.

• http://www.ayoso.com Cody Boyte

Good article. We actually implemented this a slightly different way.

As a SaaS company, once we convert a visitor into a new member, I can’t convert them again. So, over time, our conversion rates were dropping as random visitors were turning into new members but they would continue to visit and log-in to the site.

At first my boss didn’t understand what I was talking about, but with some custom variables dropped by the tech team, we were able to filter out the different types of members from all of the non-member visitors. That allows us to focus strictly on ‘convertible visitors’ as opposed to all visitors. Frankly as much as I like our members, I can’t convert them into a new lead so I don’t care about them from a Google Analytics perspective.

Again, thanks for the article.

• http://www.lattimore.id.au Alistair

Himanshu,

While I completely agree that you should apply segmentation to web analytics to get additional insight, I really think you’ve misrepresented yourself when you say ‘you dramatically increase their conversion rate’.

You’re not increasing your customers conversion rate at all, you’re not generating them more leads, getting more sales or revenue – you’re reporting their existing conversion rate a different way.

Despite my nitpicking above, I think you’re article has a lot of merit and anyone that isn’t segmenting their analytics data is missing out on a lot of opportunity to better understand their customers.

Al.

• http://www.seotakeaways.com/ Himanshu

Hi Alistair! I agree with what you are saying. But unfortunately we live in an analytics world of ‘what you see is what you get’. What you report to your client/boss or what they see in their analytics reports, is what they believe (most of the time). So for them it is an improvement in their conversion rate, it is an improvement in the way they look at data and take business decisions

• http://www.poweredbysearch.com Dev Basu

I like your approach Himanshu. Segmentation is the key to making good analytics hypotheses and by focusing on ‘real’ data, you can focus on making ‘real’ decisions that can improve conversion rate. For example, some of Canadian clients serve both English and French markets. By segmenting only to Canada and ignoring the rest of the world, we may find that the French market’s conversion rate is poor because there is a poor multi-lingual user experience. By improving that, we can improve conversion rates too

• http://www.seotakeaways.com/ Himanshu

I agree with you Dev. There can be many facets of data segmentation. I have presented only one in this post.

• Pavan

hi Himanshu,

I see u are google certified. please help me how i prepare for this exam and which are the technique u use for clear this exam …

• http://www.edutechnology.net Rafi

Nice article but it is also a complicated topic. Thanks for sharing

• Jctelo

Hi! I know this is an old topic, but I have a doubt about your segmentation. I work on a online store in Portugal, but some of our clients access the website on other country and use an address in Portugal for the delivery. If I make the segmentation you suggest i will eliminate this clients, and i think this thinking can be applied to most ecommerce websites. Do you agreed with this?

• seohimanshu

Well if your clients can be anywhere from Europe then you can’t remove them from your conversion rate calculations. Buy you certainly should remove all those people who can access your website but would never use your service like people from Australia, New Zealand, China, India, Japan etc.

• anu

Hello Himanshu, Which is considered as real conversion in Google analytic

• optimizesmart

Conversion which has the ability to impact the business bottomline.

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