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In my experience, the day of the week and hour of the day at which marketing emails are sent is often based on little more than the gut feeling of the email marketer and the performance of previous emails, rather than real data. 

As someone who could put the anal in analytics, I think that's a rather inexact science. Surely there's a more accurate way to figure out whether the assumption is really true?

There are clearly some days of the week and hours of the day that result in higher conversion rates than others. So theoretically, if you can get your email marketing to your customers' inboxes at the time they're most likely to convert, or just before, your efforts should result in better conversion rates and more revenue.

Fortunately, there is a better way to determine the optimum mailing time, rather than using gut instinct - you can do it via Google Analytics.

However, it's actually surprisingly challenging to pull this data out of GA.

In fact, it's currently not at all trivial, without resorting to some advanced segmentation and some ingenious interface hacks that allow you to use Analytics in a way in which Google never intended. 

On the plus side, no coding is required. It can all be done via your browser. 

Step 1: Create your segments

In order to find the time of the day at which your site's conversion rate is at its highest you'll need to create some advanced segments to separate transactions into time period segments

You can make as many of these as you want, but for a reasonably accurate picture three or four ought to suffice. I went for morning (7am-12am), afternoon (12am-5pm) and out of hours (5pm-7am). 

If you notice that the out of hours segment seems to provide particularly good conversion rates you may want to add an additional segment for the evening, splitting the day into quarters, giving you slightly more precision. 

To create these advanced segments click Advanced Segments > All Visits > Create a new advanced segment. Then click Dimensions > Visitors > Hour of the day and drag the bar to the "dimension or metric" placeholder at the top. Click the "and" link and drag a second Hour of the day bar to the "dimension or metric" placeholder.

Enter the time periods into each field to segment the traffic up according to the time period. Or, to save yourself the time and effort, just click the links below and the segments will automatically be added to your Google Analytics account. 

Step 2: Finding the best time

Go to Advanced segments > All visits > Custom segments, then check each of the segments you just added or created, then click Apply.

Now click the Ecommerce button on the left hand navigation. At the top you should see the All visits conversion rate, and the three conversion rates for the time segments you just added. If one of them is better than the others, then that is when you should send your email.

Use the date widget to check different weeks, months or extend the length to cover a year or more, if you've got sufficient data, so you can double-check that the data you're observing is consistent.

Once you've identified your peak conversion rate time window, it's worth drilling-down a bit further, so go back to the advanced segments tool and create some extra segments for the time periods that fall within.

This will allow you to determine whether the highest conversion rates occur at 7-9am, 9-10am or 10am-12am. You'll want to time your mailing so that it covers all of the peak conversion rate times.

Step 3: Hack your browser

Given that we've just made advanced segments to visualise time periods with relative ease, you'd think it would be straightforward to do the same for days of the week. But you'd be wrong.

Finding the best day of the week is the particularly tricky bit! I scratched my head for quite a while on this one, and I don't think it's even currently possible to do this in GA at the moment - at least not without some browser witchcraft.

The current interface of Google Analytics doesn't allow you to compare data for specific days of the week to see which one provides the best historic conversion rate, because there's no dimension for it.

Weirdly, the day of the week dimension functionality does appear to exist within the GA software, but it appears not to be enabled.

However, it is possible to hack the GA interface to get at the dimensions Google doesn't provide in the current version, which allows you to analyse data in ways the average GA user wouldn't be able to do.

This sounds really complicated, but you can actually pull it off very easily using Firefox and a couple of browser plugins: Greasemonkey and Google Analytics Report Enhancer from ROI Revolution.

Simply install Greasemonkey, restart your browser then click this Google Analytics Report Enhancer link and Greasemonkey will install a browser hack. When you next visit the Google Analytics site you should see an additional logo next to the GA one at the top left.

Step 4: Finding the best day of the week

To find the day of the week that has the highest conversion rate, go to Traffic Sources > Search Engines, then click the Sources button in the first column of the table. This will open a mega menu style drop down and you should see a link called "Day of the week" under "Custom variable keys". Click it, then click the Ecommerce tab.  You should now see a list of days of the week, along with the metrics for each one - including the all importance ecommerce conversion rate. Pick the one with the highest conversion rate, or the one which spans a few days with high conversion rates. Combine this with the hour of the day data from the earlier steps and you've now pinpointed the theoretical optimum time to send your email marketing.

Helpful tips

  • Create advanced segments for distinct time periods and drill-down where required in order to get greater precision.
  • Use Google Analytics Report Enhancer to add extra functionality to Google Analytics. 
  • Determine the best time of day and day of the week based on the best e-commerce conversion rate for your site. Chances are, it will differ from site to site. 
  • Check your data before acting upon it. Look at multiple months, just in case it's a seasonal effect. 
  • Use GARE to check the best days of the month. Does conversion rate go up around pay day?
  • Do a split test on your email database to see if there's any improvement in its performance. If it works, and you can repeat the experiment successfully, go with it.
  • If you spot a pattern, also consider trying a similar thing with PPC ads. Bid up when conversion rates are high. Reduce bids when they're low.
Matt Clarke

Published 19 April, 2011 by Matt Clarke

Matt Clarke is E-commerce Manager at Swell Uk and a contributor to Econsultancy. Follow him on Twitter , Google + or connect via LinkedIn

5 more posts from this author

Comments (25)

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David

Great tips!
Love it!

Best regards,
David

over 5 years ago

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amandine

Can this be done for facebook as well?

over 5 years ago

Matt Clarke

Matt Clarke, Ecommerce Director at B2B

Yes, you could apply it to pretty much anything. I've used it very successfully on our PPC advertising and have had a big boost to revenues and ROI.

over 5 years ago

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hcabbos

Excuse my ignorance, but is this article only good for ecommerce sites? Step 2 dives into the ecommerce section of Analytics.

over 5 years ago

Matt Clarke

Matt Clarke, Ecommerce Director at B2B

@hcabbos Yes, this is designed for ecommerce sites. If you run a content site, which doesn't have ecommerce tracking, you could look at engagement metrics instead.

Which day/period gives you the most goal scores? Which day/period has the lowest bounce rate? Which day/period results in the longest time on site, or the most pageviews per visit?

While money isn't involved, you should still be able to get an indication of the best day/time to send, however, it's possible that the results might not be quite so clear cut as they tend to be on ecommerce sites, when conversion rates can differ markedly according to the time or day.

over 5 years ago

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Claire

Really useful and very clever. Love it!

over 5 years ago

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emma

Hello

I'm getting stuck between Step 1 and 2!

I can't see: "Go to Advanced segments > All visits > Custom segments, then check each of the segments you just added or created, then click Apply"

When I click on Advanced Segments, I can see "All visits" under Default Segments, but it says it's "Not applicable" and I'm not sure that's the "All visits" you mean anyway.

Could you tell me where I'm going wrong please?

Thanks!

over 5 years ago

Tom Summerfield

Tom Summerfield, MD at Togs + Clogs

This is a brilliant topic and tutorial! I've been monitoring and recording email open and click rates manually using my MailChimp analytics and this report is a perfect partner for that.

Can anyone advise where there are more examples of reports to pull off GA?

over 5 years ago

Matt Clarke

Matt Clarke, Ecommerce Director at B2B

Thanks for your feedback.

@Emma The new version of Google Analytics was made available to non-beta-testers just after I published this, so it's possible you might be using the new interface. The interface has a different layout, which could be the cause of your confusion.

Just to clarify, on the old-style interface you first need to create your segments (or click the links I provided which will automatically add the segments to your account). Once you've done that, look for the Advanced Segments dropdown just above the date-picker on the top-right hand side of the interface. Click that to expand the list. On the Custom Segments panel, scroll down to the bottom and select the three time segments. Then click Apply.

On the new interface click Advanced Segments (now on the top left hand side of the main panel), then click the time segments. You can ignore the All visits bit here. The new version of GA no longer requires All visits to be selected when three segments are used, which many saw as a bug or restriction of the previous release.

I've not yet tried using GARE in the new-style interface. It's possible that it may no longer work as intended. If so, you may need to jump back to the old version of GA. If they haven't already done so, I'd imagine ROI Revolution will be working on a workaround for using GARE on version 5 of GA.

Hope this helps.

over 5 years ago

John Swinburn

John Swinburn, Digital Campaign Manager at Benenden Health

Matt,

That is brilliant!. Thank you for the step by step process to do this.

over 5 years ago

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Sekhar Saha

Thanks for the share. It will be of great help for us. One question I must ask that whether we can do the text mining out of the result. I mean is there any option to do the text and/or data mionig for a particular website. Data analysis will give more insights over a particular industry.

over 5 years ago

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Sarita

Hi Matt,

I am also getting stuck after creating the segments, I suppose I have the new interface. I cannot see 'Time Segments' on left hand side panel.

How do I ensure that the Time segments created have been applied?

Let me know

Thanks

over 5 years ago

Gary Baker

Gary Baker, Managing Director at Swagger & Swoon

That's interesting Matt, thanks for the guide. You could take this a step further if you're already using Google's utm tracking code by checking the conversion rates for each segment for your email mailing list under Traffic Sources. You may well find that your emails convert differently to the rest of the site.

over 5 years ago

Matt Clarke

Matt Clarke, Ecommerce Director at B2B

Thanks for the feedback.

@Sekhar - I'm really sorry, but I'm afraid I don't understand your question. If you're asking whether you can export these data to Excel (or similar), then yes, you can do this via the GA interface.

@Sarita - Sorry. I'll add more screenshots next time to make it a bit clearer. If you've added the segments, or created them manually, you should see some "Time: Morning", "Time: Afternoon" and "Time: Out of hours" in your list of custom advanced segments. If not, you'll need to create them first. It only takes a minute to do each one.

@Gary - Yes, you're right. The only snag with this, though, is that ours have historically always been sent out on a particular day, so that skews the results we'd get.

If you always send on a Friday, chances are, your utm_campaign tracked data would reveal Friday as the best day, when visitors might actually convert better on a different day of the week. That was really the reason I focused specifically on conversion rate in general, rather than just looking at conversion rate from email.

over 5 years ago

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Martin

Interesting article... but how do the 'Time of Day' segments differ from looking at conversion rates over a time period, broken down by hour?

over 5 years ago

Matt Clarke

Matt Clarke, Ecommerce Director at B2B

@Martin - Yep. That's an alternative and easier way to get individual conversion rates. I'd gone for advanced segments for time periods to allow me to analyse other things in addition to CR.

over 5 years ago

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Tim

Interesting article and I like the approach of breaking the day down using advanced segments.

However, with regards to 'Day of the week', doesn't this exist as a dimension in custom reporting?

You could then just include the 'Day' dimension in a custom report - granted it doesn't let you include 'Ecommerce conversion rate' as a metric but it will let you include Transactions and Visits and then it's a matter of just extracting that and calculating offline.

Cheers,
Tim.

over 5 years ago

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Jim Moody

Excellent article, really helpful.

However, I have put the exact same time frame in for my segments but the out of hours part is showing no results.

For the out of hours I put:

Greater than 17
and
Less than 7

Any ideas?

over 5 years ago

Matt Clarke

Matt Clarke, Ecommerce Director at B2B

@Jim - Google Analytics uses a 24-hour clock style for hours, so you need to put 07, rather than 7. I think that should fix it. It works for me.

over 5 years ago

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Jim Moody

@ Matt - I have just checked and did have '07' as the value.

One thing I have noticed is that in the example it states 'Hour of the Day' however all I can see is 'Hour'.

The 'Morning' and 'Afternoon' filters work fine.

over 5 years ago

Oliver Wood

Oliver Wood, Search Operations Director at GroupM

Great article, thanks very much.

In reference to the earlier comment, for non ecommerce sites you could simply look at bounce rate by day determine best day.

One challenge I still have is to find the best day/time of day combination.

For example, applying these methods to one client gave me Friday and then afternoons as the best day and time of day respectively. This results in 'Friday afternoon' being the optimal time, which for obvious reasons is unlikely to be the case.

Thoughts?

over 5 years ago

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Chris Corney

Just been re-reading this fantastic article again, wondering if there are any more suggested metrics for a non-ecommerce site? Any examples of goal conversions etc originating from email sends and the best ways to report on them?

almost 5 years ago

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Thibaud

Hi Matt,
Thanks a lot for this article, I'm testing it at the moment and hopefully will see some good results. One extra 'problem' I'm having is trying to segment the day and time by Country (or Continent) as we operate globally and would of course want to send out e-mails when it's best for that specific timezone. I don't seem able to do this in GA combined with the advanced segments and Day of Week metric. Do you have any thoughts on this?

Thanks again!

almost 5 years ago

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Mclean

Buenas a todos!!

about 4 years ago

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Kirsty Trainer, Online Marketing Exec at toinfinity

Is there anywhere I can find an up-to-date version of this?

Many thanks

almost 3 years ago

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