Upload campaign cost data into Google Analytics: a new free tool available

Import cost data into Google Analytics

Importing click and cost data for non-Google search engines and campaigns into  allows to compare performance data for Google and non-Google campaigns.

OWOX, a Partner, has created a free add-on that helps you quickly and easily import data from Google Sheets into Google Analytics. It is not the first tool for this scope, but it’s worth mentioning because it is free and easy-to-use.

Here are few simple steps to take to see your non-Google campaign cost data (for example Facebook Ads, Twitter, Linkedin or Bing Ads) into GA Views.

Here is a step-by-step guide:

  1. Create a Cost data schema on GA
  2. Download the schema (Excel template) as guidance. A typical format is:
    ga:datega:mediumga:sourcega:impressionsga:adClicksga:adCost
     ga:campaign ga:adGroup ga:adContent
  3. Export cost data from Facebook Ads
  4. Install the Google Chrome Add-On, it will be available on Google Sheet (you need to access with a Google account that has been granted GA editing rights)
  5. Copy and past FB cost data into Google Sheet making sure that it matches columns of the GA schema (point 2)
  6. Start the Add-On from the menu and upload

Once done, cost data will be visible under GA / Acquisition / Cost Data enabling interesting business metrics.

Two final notes:

If something goes wrong data can be re-uploaded, they will be overwritten.

The cost data has to be daily, and the format of its first column (date) needs to be yyyymmdd.

Last but not least, a perfect correspondence between Facebook Ads URL parameters (medium, source, campaign and content) and the cost data spreadsheet is needed to match data on Google Analytics. Differently, you will find a mismatch between uploaded metrics and Sessions. Ideally, you can add two columns for medium and source while for the others, it’s advised to use the same name both in the URL parameters and in the FB Ads level (for example Adgroup matching Ad set).

 

 

Discrepancy between conversions on Google Analytics and Facebook advertising reports: VTC vs CTC

Digital Marketing Conversions

A digital customer journey: which channel will get (most of) the credit for a conversion? (Image credit: DigitSix.com)

Have you ever encountered a discrepancy between performance reports by channel and what’s reported by advertising platforms’ reports, for example, ? The former is usually less generous than the latter, and you don’t know who’s telling the truth, right?

Let’s imagine a situation when you have been running promoted posts through Facebook and the outcome has been ten conversions according to the Report (measured through the Facebook Conversion Pixel), four Assisted Conversions according to Google Analytics (Multi-Channel funnel report) and no Direct Conversion (still according to Google Analytics). What measure can be considered more reliable?

It depends on what you are trying to sell. If you want to know what is the best target audience, then go for the Facebook report. If you want to know what is the best channel to generate leads go for the Assisted Conversions report. Differently, if you are offering something that should not require much thinking before a conversion, then focus on the Direct Conversion report – where usually Search Marketing performs much better than , in particular if targeting branded keywords.. a quick win!

The difference is explained by the methodology adopted to identify a conversion: Google Analytics takes into account only CTC (Click-Through-Conversions) while other platforms in their reports also show (or only) VTC (View-Through-Conversions).

offers both options, but CTC (more meaningful for search marketing than for display) are deducted from VTC.

Some advertising platforms (like Adroll) make a clear distinction between the two measurement methods, while others (like Facebook) state it in a more subtle way:

Facebook (then) matches that conversion event against the set of people an ad was served to/or that clicked on an ad so that we can provide you with information that helps you understand the return on investment for your ad spend.“

(source: https://www.facebook.com/help/435189689870514)

However, even on Facebook, you can still compare both methods also on Facebook report through the Attribution Window settings (image above).

Facebook Advertising report: Attribution Window settings

Facebook Advertising Report: Attribution Window settings

 

Another aspect to consider is the time frame. Facebook offer three options: 1, 7 and 28 days, while in Google Analytics Multi-Channel Funnel report you have 90 choices, from 1 to 90 days before conversion. Every platform has its options therefore if you don’t synchronise the method, you will get different results.

VTC methodology considers a digital channel like an offline channel (e.g. TV) since it takes into account all conversions completed after someone has seen an ad but has not clicked on it. Some way, it makes sense because a person might discover a brand or a product through a promoted post and still do not take any immediate action (e.g. click, comment, share, etc.) but search for it later through other channels.

Obviously, VTC is more generous towards the platform than CTC, which is a situation that requires the converted user to click on an ad, within a particular period of time. On Google Analytics, Multi-Channel Funnels take into account only CTC.

To make the story short, in a logic sequence, the highest performance regarding Conversion Rate, , , etc. is measured considering VTC, and then CTC (Multi-Channel) and eventually CTC (Direct or last-click).

Digital Conversions: VTC vs CTC

VTC will always include CTC

Digital agencies usually tend to show the best performance in their reports, but despite it might sound obvious to some people, it is always good to ask for a clear “legend” where it’s well explained what is intended by “conversion”.

The methodology applied should always be explicit and come before any attribution model. The best approach, therefore, is to produce different columns to outline the outcome of each methodology applied to determine conversions.

 

MoreMetrics imports additional Social Media metrics into Google Analytics

 * The service MoreMetrics has been discontinued * 

MoreMetrics is a new free service provided by the Italian startup Bryo to help you importing some core Social Media metrics like Facebook fans or Twitter followers into any Google Analytics property.

Wouldn’t be nice to have Facebook Page Fans stats in Google Analytics? Tired of checking your KPIs on different sites? Do you love Google Analytics as much as we do? Let’s give MoreMetrics a try.

At the moment of launch there are the following options: Facebook Likes/Fans, Twitter Followers and Youtube Views/Subscribers. MailChimp is expected soon.

more metrics options

MoreMetrics options available (June 2014)

Once such data is imported into your GA, you can then create a Widget in a custom GA Dashboard to show a timeline of your SM trends.

Here is a step-by-step guide:

  1. Click on Dashboards, choose a dashboard and click on Add Widget.
  2. Give a Widget title matching the type of SM metric, for example “Facebook fans”
  3. Choose Standard/Timeline
  4. Choose “Event Value” in Graph the following metric over time
  5. Filters using the following three conditions:
    a. Only show Event Category Exactly matching MoreMetrics
    b. Only show Event Action Exactly matching the type of metric you want to show (e.g. FB Fans)
    c. Only show Event Label Exactly matching the [Event Label]
  6. Save

Some additional notes:

  • normally such metrics are not available in Google Analytics, not even in the Acquisition/Social report.
  • data are sent once a day therefore data will be available in about 24 hours
  • Universal Analytics is needed since the tool uses Measurement Protocol
  • Event value is the sum of all likes (or followed) day by day therefore you need to look at the daily value, not its aggregate: you need a dashboard widget to explore such data into Google Analytics

Update – some examples of GA dashboard widgets built through MoreMetrics:

more-metrics-google-analytics-social-media-facebook-likes-twitter-followers

Timeline and daily amount

 

more-metrics-google-analytics-social-media-facebook-fans-twitter-stats

A comparison between Facebook and Twitter

Try MoreMetrics now.

Did you know Google+ Ripples? It helps you monitor shares of a post on Google Plus

Google+ Ripples

+ Ripples for a very popular post by Matt Cuts: “The decay and fall of guest blogging for

UPDATE: Google+ Ripples has been terminated on 20th May 2015.

 

Last 20 January, the Google webspam team leader Matt Cutts posted about decay and fall of guest blogging for SEO. Whatever he says in his blog sound like the Bible for the SEO industry. Despite some times (like the above case) he might change his mind.

The above screenshot taken directly from Google+ Ripples shows the public shares of such popular post on Google+.

Google+ Ripples (in Italian Google+ Eco) creates an interactive graphic of the public shares of any public post or URL on Google+ to show you how it has rippled through the network and help you discover new and interesting people to follow.

Ripples shows you:

  • Who has publicly shared a post or URL and the comments they’ve made
  • How a post or URL was shared over time
  • Statistics on how a post or URL was shared

A link to Ripples for web pages / posts shared through Google+ is now available also in under “Acquisition / Social / Data Hub Activity”

Google+ Ripples accessible directly through Google Analytics

Google+ Ripples accessible directly through Google Analytics

You can see Ripples for each post just by adding its URL at the end of this one, in your browser bar:

https://plus.google.com/ripple/details?url=_________

and SEO are getting closer day by day and guest blogging apparently is decreasing in popularity – if Matt has said so, it’s true.

Let’s imagine a link between number of shares and author(ship) rank for each of such shares. It would certainly give an idea of the weight of such an important ranking factor like Google+ activity.

Here is my Google+ Author Rank measured with the experimental tool by Virante that calculates a score based on the content linked to my Google+ profile via Authorship. It does not currently include any measure of authority due to my actions within Google+.

Google+ Author Rank

Google+ Author Rank

You can monitor Author Rank for any of your (Google+) friends.

UPDATE: Google+ Ripples has been terminated on 20th May 2015.

periodic table of google analytics

Google Analytics under a chemical perspective: the periodic table (free pdf download)

Can periodic tables be considered infographics? Whatever your answer is, what I am going to present here reminds me of the SEO periodic table published some time ago (and constantly updated).
It is an useful overview that can help beginners to spot whatever has not been considered into their work/analysis/knowledge. 
Have a look at the elements of such an interesting visual guide about Google Analytics main features seen from a ‘chemical’ perspective. It has been made and published by the certified GA expert Jeff Sauer @ Jeffalytics.
GA elements have been splitted into four main categories: Product, Metrics, Reports, and Features.
Are you aware of all its elements? Anything missing?

Little update – On 20th Feb Google Analytics has  redesigned its UI again. Accounts are now listed on a dropdown menu placed in the top right corner.

Import Google Analytics conversion goals into AdWords

Google Analytics conversion goals now available on AdWords

Import Google Analytics conversion goals into AdWords

Google Analytics conversion goals now available on AdWords

In a post published on 29 April 2013, Google announced that

Starting in mid June, you’ll be able to import your Google Analytics goals into AdWords shortly after they’re configured. As usual, data for those goals will be available about two days later.

Google suggests that it’s better to track Goals through Analytics rather than AdWords for the following reasons:

Google Analytics Conversion Goals

AdWords Conversion Tracking

  • More complex, but provides more information about where your clicks are coming from.
  • Ideal if you’re interested in the entire flow of customers through your site, not just conversions.
  • Can include conversions from non-AdWords sources, so it’s a great comparison tool.
  • Less complex, but provides less information about where your clicks are coming from.
  • Ideal if you’re interested only in conversions.
  • Tracks conversions only from AdWords sources.

GA Goals will still be uniquely manageable from GA Admin. There can be discrepancies between the two, as Google explains here together with everything needed to let GA goals appear under your AdWords campaigns conversions list.

You can use both, they will not interfere each other so no need to change configuration.

Google Analytics custom filters to tidy up your metrics: how to split up social media from referrals

Note: The Google URL Builder has been updated therefore I advice to have a look to this interesting guide written by Prateek Agarwal.


This post is about adding a custom filter to refine your Medium report on Google Analytics.

I am not going to talk about the “direct / none” aggregate that unfortunately include also visits that are not direct accesses like a user typing your URL or a bookmark, but any other session missing server data information. There is a wide literature about, but the problem remains unsolved.

Let’s talk about another medium category, referrals, that includes also visits coming from social media. Why not taking social media visits away from referrals?

Custom filters are a very useful tool for aggregating or adjusting some metrics before they appear on reports. In this post I’ll show you how to use custom filters to assign all visits coming from social media sources to a Medium category called “social“. Just follow this step:

Filter to separate social sources from referral on GA

Filter to separate social sources from referral on GA

The source for visits from FB mobile is “m.facebook.com” whilst Twitter is “t.co”. You can add all social media together by using Regular Expressions (RegEx). In this case you might need to do some testing. A RegEx for social filter can be this one:

(facebook.com|m.facebook.com|facebook|vk|vk.com|t.co|twitter|hootsuite|tweetdeck|plus.url.google.com|youtube|linkedin|reddit|digg|delicious|stumbleupon|myspace|flickr|popurls|friendfeed)

Remember to add also “field b = referral” because you don’t want to tas as social whatever is tagged not referral, for example a CPC campaign run through Facebook or LinkedIn.

After applying the filter don’t be impatient with Real-Time stats as custom filters might take a short while to apply properly.

A suggestion to speed up your RegEx learning process is to create a test profile (never play with the main profile!) and apply different filters there, assigning categories called social1, social2, etc. for different RegEx’s so you will reckon which is working and which is not by looking at the variable appearing on reports few hours after applying the filters.

Let’s go back to my proposals. Here’re the filters applied taken:

  1. visits from social media whose source is “facebook”, “twitter” or “google plus” have been all automatically categorised as “referrals” and will now be categorised as “social”
  2. using another custom filter, all medium assigned to “rss” will be renamed “feed” in order to join another existing category:  there is no need to have two different categories of the same type (distinction will be still available under Sources)

Here is what I had before (15/05/2013)

Before the filter...

Before the filter: no social!

and this is what I had after applying the filter (19/05/2013)

...after the filter

…after the filter, social appears!

Observations:

  • visits from social media are taken off from “referral” and placed into a new category called “social” that will also include all future social media activity tagged through the URL builder to be taken away from the “(none)”
  • RSS disappear and joins “feed” for more clarity
  • the site does not have benefit of any paid advertising source
  • direct/none stable (14% / 15%)
  • organic stable (11%)

Filters above apply only to Campaign Medium, but what about organising also Sources by aggregating at least the most relevant URL’s under just few categories? For example you can join www.facebook.com and m.facebook.com under just “facebook”.

Again, to be precise, you can use RegEx but mind that if you select all domains that contain the word “facebook” or “twitter” you might end up in adding sites that are not facebook and still link to you. For example think of the service “twitterfeed” which is not Twitter. My suggestion here is to narrow aggregation just to the most relevant categories: if you’re embracing let’s say 95% of your visits that could be enough, isn’t it?

A further action: tag your incoming links with the URL builder whenever possible

If you want to reduce the amount of “(none)” among your media, start tagging all your social media posting that links to your website using the URL builder. In this case, I suggest to keep “social” as Campaign Medium for non paid (e.g. a Tweet or a Facebook post on wall or tab) and “cpc” or “paid” for paid (e.g. Facebook advertising) aligning it to other paid sources if any (e.g. AdWords).

You can use URL shorteners, but be sure that they keep tags or your link end up in the meaningless “direct/none” category. To manage non-paid incoming links from your own social sources Lunametrics has built a simple but still useful Google spreadsheet, using the shortener bit.ly

Be consistent with tags

If many people have access to your social media stream and run digital campaigns you should do some efforts to align tagging policies otherwise you might end up in a mess on GA reports. I’ve seen reports including many similar tags all together such as CPC, cpc, PPC, paid, ads, advertising, social, socialmedia, facebook, fb, etc.

Why separating social from referrals?

Ok they are all referrals, but usually visits coming from social media come from piece of content that links to your website (e.g. a post on Facebook wall). I say ‘usually’ because such links might be also placed on social media areas such as notes, tabs, twitter profile description, about sections, etc. together with other links, but such places are less relevant than the mainstream. Other referrals (traditional, let’s say), most of the times are link placed on websites (e.g. blogs), either because they like you/find your content relevant/worth mentioning or because of your link building activity. I’m not engaging in a debate if it’s better to have “social signals” or referrals from a pure SEO perspective during the Penguin era. Let’s say that it’s important to be noticed both by search engines and (yes, apparently we’re still humans) real people, but this post helps you to distinguish among digital type of  place where you’ve been spotted on: making a parallel with geography, if the source is the name of the place, the medium is the type of place.

A filter also for email

Usually newsletters/DEM are tagged with “email” medium. Why not doing the same with a custom filter that attributes “email” medium to all sources that contain the word “mail”? It can be mail.yahoo.com, gmail.com, etc. You might also add other relevant email providers like outlook, hotmail, etc. with a RegEx like (mail|outlook|hotmail|etc….). Again, if you want to preserve other medium like cpc, add a field b=referral – this way you will be pretty sure that all links to your site placed on email content will be tagged with “email” medium instead of referral.

Remember: it’s never too late to tidy your reports and to adopt a consistent and constant “tagging policy”.