How to link Adwords and Google Analytics

If you are running an AdWords campaign you must have a Google Analytics account. We will show you how to link these two accounts so you can unleash the full reporting potential of both platforms. 1. Why should you link Analytics and AdWords? When you link Google Analytics and AdWords, you can: See ad and site performance data in the AdWords reports in Google Analytics. Import Google Analytics goals and ecommerce transactions directly into your AdWords account. Import valuable Analytics metrics—such as bounce rate, avg. session duration, and pages/session—into your AdWords account. Take advantage of enhanced remarketing capabilities. Get richer data in the Google Analytics multi-channel funnels reports. Use your Google Analytics data to enhance your AdWords experience. 2. How to link Google Analytics and AdWords The linking wizard makes it easy to link your AdWords account(s) to multiple views of your Google Analytics property. If you have multiple Google Analytics properties and want to link each of them to your AdWords account(s), just complete the linking wizard for each property. Sign into your Google Analytics account at www.google.com/analytics. Note: You can also quickly open Google Analytics from within your AdWords account. Click the tools tab, select analytics, and then follow the rest of these instructions. Click the admin tab at the top of the page. In the account column, select the analytics account that contains the property you want to link to one or more of your AdWords accounts. In the property column, select the analytics property you want to link, and click AdWords Linking. Use one of the following options to select the AdWords accounts you want to link with your analytics property. Select the checkbox next to any AdWords accounts you want to link with your analytics property. If you have an AdWords manager (MCC) account, select the checkbox next to the manager account to link it (and all of its child accounts) with your analytics property. If you want to link only a few managed accounts, expand the manager account by clicking the arrow next to it. Then, select the checkbox next to each of the managed AdWords accounts that you want to link. Or, click all linkable to select all of managed AdWords accounts under that MCC. You can then deselect individual accounts, and the other accounts will stay selected. Click the continue button. In the link configuration section, enter a link group title to identify your group of linked AdWords accounts. Note: Most users will only need one link group. We recommend creating multiple link groups only if you have multiple AdWords accounts and want data to flow in different ways between these accounts and your analytics property. For example, you should create multiple link groups if you need to either link different AdWords accounts to different views of the same Google Analytics property or enable auto-tagging for only some of your AdWords accounts. Select the Google Analytics views in which you want the AdWords data to be available. If you've already enabled auto-tagging in your AdWords account, skip to the next step. The account linking process will enable auto-tagging for all of your linked AdWords accounts. Click advanced settings only if you need to manually tag your AdWords links. Click the link accounts button. Congratulations! Your accounts are now linked. If you opted to keep auto-tagging turned on (recommended), Google Analytics will automatically start associating your AdWords data with customer clicks. For a deeper view and debugging you should also read the Google Analytics guide. Have any questions on setting this up? Get in touch and we'd be happy to help!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

2016-11-24

Who visited my website? Find out with Google Analytics

In every retail business, knowing your customers is vital to succeeding. All decisions you make about business and marketing strategies must begin from the user's perspective. Let's find out how we can build the user persona with the data that lies in Google Analytics. Even though Google's user profile is not as fancy as Facebook's, you can still have a pretty good idea about your customers. Let's start with the basics, and ask the most basic questions: How many of my customers are men or women? What is the age range of my customers? What devices do they use to access my website? How often do they visit my website? What are their interests? What makes them convert? For the first two questions, you should already have enabled Demographics and Interest reports in your Google account. If not, go to Admin > Property Settings > Enable Demographics and Interest reports. The split of age and sex can be seen in Audience > Demographics. The most interesting thing here is that you can add a second dimension to compare and see how people are different based on more than one vector. If you add a second dimension, such as Device Category, you will get a split like this: You can see from the above screenshot that females prefer mobile and are the majority user. Also when females are on desktop, they are more likely to spend more time on the website. You can go into more depth and analyse the conversion rate also. You can find out the behaviour of new vs. returning customers from the report, New vs. Returning under Audience. Add a second dimension "Gender" and you will see who's more likely to come back to your website. Based on the above screenshot, women are returning about 25% of the time, while men return about 21% of the time. Also, men have a higher bounce rate. Under Audience, you will also find the Frequency & Recency report and the Engagement report. If you create two new segments by gender: female and male, you will find who your most loyal visitors are. The interests (Google reads them from the user behaviour online) can be found under Audience > Interests. It is best to split the report based on females and males. You will now have a full view of your customers. And for the final and most important question: what makes them convert?, you can find this out by going to Aquisition > Channels. Add a second dimension by gender, age or interests and analyse the traffic for each channel. Find out what channel brings the most important users. In the screenshot below, you can see that woman are more likely to buy if the website is referred. This means that the reputation of the website is a big factor in their decision. Don't be shy when creating custom reports because you can drill down the data to multiple levels of understanding. Applying second dimensions has its limitations and you can see only a part of the information at once. If you still need a more detailed view of what each customer does on the website, we strongly recommend the User Explorer menu. We found it useful to find out how different touch points are important and how long the path is for a valuable customer. Also, it was useful in debugging and creating a marketing strategy based on the customer's flow. The bottom line is that you can answer "who is your customer?" with Google Analytics through its reports if you learn to see the report from different perspectives. Feel free to drop us a line if you use any other report that is relevant to this article!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

2016-11-17

What are custom dimensions in Google Analytics?

By default, Google Analytics allows you to segment traffic by standard dimensions such as visitor location, screen size, or traffic source. You can view smarter reports by adding custom dimensions specific for your business. Give me an example Let's say when your members register they add a job title. Would you like to see reports on the site activity for a particular job title, or compare conversion for one job title versus another? In which case you would set a custom dimension of 'Job Title' and then be able to filter by just the 'Researchers' for any Google Analytics report. Or if you run a blog / content site, you could have a dimension of 'author' and see all the traffic and referrals that a particular author on your site gets. How do I set this up? First, you need to be on Universal Analytics, and then you need to tag each page with one or more custom dimensions for Google Analytics. This is more easily done with Google Tag Manager and a data layer. It may be that the information is already on the web page (like the author of this post), but in many cases, your developer will need to include it in the background in a way that can be posted to Google Analytics. Then you will need to set up a custom report to split a certain metric (like page views) by the custom dimension (e.g. author). Please contact our specialists if you want more advice on how to set up custom dimensions!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

2016-11-16

Exclude fake 'bot' traffic from your site with Google Analytics

Ever wondered why so few visitors convert on your site? One answer is that a big chunk of your traffic is from search engine spiders and other web 'bots' which have no interest in actually engaging with you. Google Analytics has a great new feature to exclude this bot traffic from your site. All you need to do is check a box under the Admin > View > View Settings. The new option is down the bottom, underneath currency selection. It uses the IAB /ABC Bots and Spiders list, which is standard for large publishers, and updated monthly. Warning: you will see a dip in traffic from the date you apply the setting. If you're looking for a more comprehensive method to exclude spam and ghost referrals, check out our how-to guide! Have some questions about this? Get in touch with our Google Analytics experts!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

2016-11-15

What are Enhanced Ecommerce reports?

In May 2014 Google Analytics introduced a new feature: Enhanced Ecommerce tracking. If you run an ecommerce operation, this gets you much more detailed feedback on your checkout process. What will I see? Shopping behaviour: how are people converting from browsers to purchasers? Checkout behaviour: at what stage of your checkout do buyers abandon the process Product performance: which products are driving your sales, and which have a high return rate Real campaign returns: see your real return on marketing investment including promotional discounts and returns How do I set this up? The bad news is it definitely requires an experienced software developer for the setup. The reports require lots of extra product and customer information to be sent to Google Analytics. You can read the full developer information on what you can track, or our own simpler guide for tracking ecommerce via Tag Manager. However, if you already have standard ecommerce tracking and Google Tag Manager, we can set Enhanced reports up in a couple of days with no code changes on your live site - so no business disruption or risk of lost sales. Is it worth implementing? Imagine you could identify a drop-off stage in your checkout process where you could get a 10% improvement in sales conversion or a group of customers who were unable to buy (maybe due to language or browser difficulties) – what would that be worth? Many businesses have that kind of barrier just waiting to be discovered…   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

2016-11-14

How to track time on page with Google Tag Manager

Our script for accurate tracking of time on page beats Google's default measurement to give you an accurate picture of how long users are spending on your page open and in focus. This post translates the approach into Google Tag Manager. The setup consists of two tags (one custom), one firing rule and two variables. Step by step: 1. Add the timer script as a custom HTML tag <script><br /> /*<br /> Logs the time on the page to dataLayer every 10 seconds<br /> (c) LittleData consulting limited 2014<br /> */<br /> (function () {<br /> var inFocus = true;<br /> var intervalSeconds = 10; //10 seconds<br /> var interval = intervalSeconds * 1000;<br /> var eventCount = 0;<br /> var maxEvents = 60; //stops after 10 minutes in focus<br /> var fnBlur = function(){inFocus = false; };<br /> var fnFocus = function(){inFocus= true; };<br /> if (window.addEventListener) {<br /> window.addEventListener ('blur',fnBlur,true);<br /> window.addEventListener ('focus',fnFocus,true);<br /> }<br /> else if (window.attachEvent) {<br /> window.attachEvent ('onblur',fnBlur);<br /> window.attachEvent ('onfocus',fnFocus);<br /> }<br /> var formatMS = function(t){<br /> return Math.floor(t/60) +':'+ (t%60==0?'00':t%60);<br /> }<br /> var timeLog = window.setInterval(function () {<br /> if (inFocus){<br /> eventCount++;<br /> var secondsInFocus = Math.round(eventCount * intervalSeconds);<br /> dataLayer.push({"event": "LittleDataTimer", "interval": interval, "intervalSeconds": intervalSeconds, "timeInFocus": formatMS(secondsInFocus) });<br /> }<br /> if (eventCount>=maxEvents) clearInterval(timeLog);<br /> }, interval);<br /> })();<br /> </script> 2. Add two variables to access the data layer variables One for the formatted time, which will feed through the event label And one for the number of seconds in focus since the last event, which will feed through the event value 3. Add the firing rule for the event 4. Add the tag that reports the timer event to Google Analytics Options and further information You can change the timer interval in the custom HTML tag - the reporting will adjust accordingly. Choosing the interval is a trade-off between the resolution of the reporting and the load on the client in sending events, as well as Google's 500 hit per session quota. We've chosen ten seconds because we think the users who are in 'wrong place' and don't engage at all will leave in under ten seconds, anything more is some measure of success. If you'd like assistance implementing this or something else to get an accurate picture of how users interact with your site, get in touch!   Get Social! Follow us on LinkedIn, Twitter, and Facebook and keep up-to-date with our Google Analytics insights.

2016-11-14

Accurate tracking of time on site

There’s a flaw in the way Google Analytics measures ‘time on site’: the counter only starts from the second page visited, so all one-page visits are counted as zero time on site. If a visitor comes to your page, stays for 10 minutes reading – and then closes the window… that’s counted as ZERO time. With landing pages that have lots of interaction, or the call to action is a phone call rather than a click, this can be a real problem. Pasting the Javascript below onto all the pages of your site will fix the problem. The script logs an event to Google Analytics for every 10 seconds the visitor stays on the page, regardless of whether they bounced or not. But it won't affect your bounce rate or time on site for historical comparison *. We suggest you look closely at how visitors drop off after 10, 20 and 30 seconds to see which of your web content could be improved. Paste this into the source of your all your pages, after the Google Analytics script <!-- Time on Site tracking (c) LittleData.co.uk 2014 --><script>(function(e){var t=true;var n=0;var r=true;var i=function(){t=false};var s=function(){t=true};if(window.addEventListener){window.addEventListener("blur",i,true);window.addEventListener("focus",s,true)}else if(window.attachEvent){window.attachEvent("onblur",i);window.attachEvent("onfocus",s)}var o=function(e){return Math.floor(e/60)+":"+(e%60==0?"00":e%60)};var u=window.setInterval(function(){e=e+10;if(t){n=n+10;if(typeof _gaq==="object"){_gaq.push(["_trackEvent","Time","Log",o(n),n,r])}else if(typeof ga==="function"){ga("send",{hitType:"event",eventCategory:"Time",eventAction:"Log",eventLabel:o(n),eventValue:10,nonInteraction:"true"})}}},1e4);window.setTimeout(function(){clearInterval(u)},601e3)})(0)</script> What you'll see In Google Analytics go to Behaviour .. Events .. Top Events and click on the event category 'Time'.                               Searching for a particular time will find all the people who have stayed at least that length of time. e.g. 0:30 finds people who have stayed more than 30 seconds. FAQs Does this affect the way I compare bounce rate or time-on-site historically? No. The script sends the timer events as 'non-interactive' meaning they won't be counted in your other metrics. Without this, you would see a sharp drop in bounce rate and an increase in time on site, as every visitor was counted as 'non-bounce' after 10 seconds. If you prefer this, see below about adapting the script. Will this work for all browsers? Yes, the functions have been tested on all major, modern browser: IE 9+, Chrome, Safari and Firefox. What if I upgrade to Universal Analytics? Don’t worry – our script already checks which of the two tracking scripts you have (ga.js or analytics.js) and sends the appropriate log. Will this max out my Google Analytics limits? The script cuts off reporting after 5 minutes, so not to violate Google’s quota of 200 – 500 events that can be sent in one session Can I adapt this myself? Sure. The full source file is here. Need more help? Get in touch with our experts!

2016-11-13

How to read the frequency report in Google Analytics

Google Analytics engagement reports can provide great insight into user behaviour on your site. However, it’s not obvious how to read them - and when you figure out how to read them, it’s not always obvious what’s good! The visitor frequency report is found under Audience > Behaviour > Frequency and recency in the Google Analytics menu. The report shows the sessions, by the number of visits for each visitor. Google’s explanation of how to read the frequency graph is nice and clear. However, their simplified example leaves out something important: returning users. In the graph, the visit count shown is for the whole user history, not just the period of the report. So if a visitor has come three times before the period their session will show in the three band. Similarly, if a user has visited the site five times in the past and then visits the site twice during the period, they will in count of sessions as 6 and 7. The example below is from a newly released site, where nearly all the visits are from the developers, who have been many times before - so there are no visitors in the 1,2,3,4 or 5 visit bands for this site in this period. The fact that the banding is based on the whole user history, not just behaviour during the period, can make the report much harder to interpret - you can't easily see the drop off in repeat visitation if an unknown number of return visitors at some point in their many visits history are also coming in. Fortunately, Google Analytic's segmentation capability comes to the rescue! For example, you can find out about the returning behaviour of visitors who came the first time during the period in question, with the segment - the settings are in the screenshot below. Note that you need to change the segment to filter users, not sessions, otherwise you will just create a more complex version of the built-in new users segment! Here’s an example of the sort of thing you might see with the segment, showing 3 segments: All Session (built in) 'User sessions = 1'  - custom segment for users having their first session in the period New Users (built in) Note: For the visit count = 1 band, the session count is the same across all three segments, For the visit count = 2 band, (and above) the number for all sessions is higher, because it includes all the users who came in on their second visit during the period. The number for the user sessions = 1 segment, is lower because it includes only the users who had their first visit during the period. The number for new users is zero because users are not new on their 2nd visit As you can see, the custom segment makes it possible to see the real return rate of new visitors in the period, narrowing to visitors who came the first time in the period in question. From this example, you can also see how misleading it would be to naively interpret the default 'all sessions' segment for, say, four sessions as the number who returned four times during the period - clearly there is a large number who have previous visits outside the period of the report. Note that none of the segments in the example actually gives the number of users who returned four times during the period - this is actually really difficult to obtain. Leaving that question aside for now, to extract some real insight from the approach of segmenting in the frequency report, combine that segment condition with a goal, say ‘transactions per user > 0’ - then you can see how many new users went on to a transaction, and how many visits they made during the period. Need help to set this up or have any questions? Get in touch with our team of experts and we'd be happy to answer any questions! This is a valuable segment to monitor and analyse - how many users have gone from first visit to a transaction this week, and how many sessions did they make along the way?

2016-11-11

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