Category : Google Analytics
Under the hood of Littledata
Littledata tool gives you insight into your customers' behaviour online. We look through hundreds of Google Analytics metrics and trends to give you summarised reports, alerts on significant changes, customised tips and benchmarks against competitor sites. This guide explains how we generate your reports and provide actionable analytics. 1. You authorise our app to access your Google Analytics data As a Google Analytics user you will already be sending data to Google every time someone interacts with your website or app. Google Analytics provides an API where our app can query this underlying data and provide summary reports in our own style. But you are only granting us READ access, so there is no possibility that any data or settings in your Google Analytics will change. 2. You pick which view to report on Once you've authorised the access, you pick which Google Analytics view you want to get the reports on. Some people will have multiple views (previously called ‘profiles’) set up for a particular website. They might have subtly different data – for example, one excludes traffic from company offices – so pick the most appropriate one for management reports. We will then ask for your email so we know where to send future alerts to. 3. Every day we look for significant changes and trending pages There are over 100 Google Analytics reports and our clever algorithms scan through all of them to find the most interesting changes to highlight. For all but the largest businesses, day-by-day comparisons are the most appropriate way of spotting changing behaviour on your website. Every morning (around 4am local time) our app fetches your traffic data from the previous day – broken down into relevant segments, like mobile traffic from organic search – and compares it against a pattern from the previous week. This isn’t just signalling whether a metric has changed – web traffic is unpredictable and changes every day (scientists call this ‘noise’). We are looking for how likely that yesterday’s value was out of line with the recent pattern. We express this as signal bars in the app: one bar means there is a 90% chance this result is significant (not chance), two bars means a 99% chance and three bars means 99.9% certain (less than a 1 in 1000 chance it is a fluke). Separately, we look for which individual pages are trending – based on the same probabilistic approach. Mostly this is change in overall views of the page, but sometimes in entrances or bounce rate. If you are not seeing screenshots for particular pages there are a few reasons why: The website URL you entered in Google Analytics may be out of date Your tracking code may run across a number of URLs – e.g. company.com and blog.company.com – and you don’t specify which in Google Analytics The page may be inaccessible to our app – typically because a person needs to login to see it 4. We look for common setup issues The tracking code that you (or your developers) copy and pasted from Google Analytics into your website is only the very basic setup. Tracking custom events and fixing issues like cross-domain tracking and spam referrals can give you more accurate data – and more useful reports from us. Littledata offers setup and consultancy to improve your data collection, or to do further manual audit. This is especially relevant if you are upgrading to Universal Analytics or planning a major site redesign. 5. We email the most significant changes to you Every day - but only if you have significant changes - we generate a summary email, with the highest priority reports you should look at. You can click through on any of these to see a mobile-friendly summary. An example change might be that 'Bounce rate from natural search traffic is down by 8% yesterday'. If you usually get a consistent bounce rate for natural / organic search traffic, and one day that changes, then it should be interesting to investigate why. If you want your colleagues to stay on top of these changes you can add them to the distribution list, or change the frequency of the emails in My Subscriptions. 6. Every Sunday we look for changes over the previous week Every week we look for longer-term trends – which are only visible when comparing the last week with the previous week. You should get more alerts on a Sunday. If you have a site with under 10,000 visits a month, you are likely to see more changes week-by-week than day-by-day. To check the setup of your reports, login to Littledata tool. For any further questions, please feel free to leave a comment below, contact us via phone or email, or send us a tweet @LittledataUK.
6 helpful Google Analytics guides
I've been improving my knowledge of Google Analytics this month but found that documentation provided by Google and other heavy research can be difficult to absorb. So here are 6 guides and tools that I found useful in the last month. How to set up campaign tracking Expertise level: Newbie Social media analytics: How to track your marketing campaigns by Cory Rosenfield. When you run an ad, email or social promotion, you want to see which channel is most effective in acquiring visitors. By gathering this information through tracking your campaigns you will be able to focus on winning strategies and make adjustments to less performing ones. Cory’s how to guide takes you through the basics of how to set up campaign tracking with relevant explanations and practical examples. It’s as easy as it gets. What metadata needs fixing Expertise level: Beginner Introducing the Meta and Rich Snippet Tester by Bill Sebald. This tester from RankTank compares your site’s meta and rich snippet data to what you have in your site’s code. You will be able to see mismatches between how you have set your titles and descriptions against what is actually displayed in search results. Want to make sure rich snippets are working correctly or Google doesn’t replace missing meta tags with something unsuitable? Then this tool is for you. How to do keyword research effectively Expertise level: Intermediate Keyword research in 90 minutes by Jeremy Gottlieb. Keyword research for improved content targeting can take a lot of time but it doesn’t have to. Jeremy’s plan splits it into a 4-stage process, full of handy tips on how to spend your time effectively. Especially useful for when planning topics for your blog posts and finding words that are most relevant to include in your product descriptions. Setting up alerts for site errors Expertise level: Intermediate Google Analytics custom alerts which you must always use by Himanshu Sharma. How can you find errors and problems on your website with minimum manual labour? Set up custom alerts in your Google Analytics account with Himanshu's guide. You can create notifications for tracking and shopping cart issues, and any unusual changes in your bounce rate and traffic. How to improve multiscreen experience Expertise level: Advanced Enabling multiscreen tracking with Google Analytics by James Rosewell. This step by step guide by James shows how to get better data on the use of your site across various mobile devices. You will be able to make informed decisions on optimising your site whilst taking into consideration screen sizes and layouts. This means improved experience for customers on bigger smartphones and smaller tablets. Source: Infinium.co What were the different variables again? Expertise level: Advanced Variable guide for Google Tag Manager by Simo Ahava. Variables in Google Tag Manager can be powerful, once you get to grips with them. Simo's comprehensive guide is a useful reference that covers everything you need to know from technical details to set ups and debugging. Source: SimoAhava.com Need some help with Google Analytics? Get in touch with our experts!
What's new in Google Analytics 2014
Google has really upped the pace of feature releases on Analytics and Tag Manager in 2014, and we’re betting you may have missed some of the extra functionality that’s been added. In the last 3 months alone we’ve counted 11 major new features. How many have you tried out? Official iPhone app. Monitor your Google Analytics on the go. Set up brand keywords. Separate out branded from non-brand search in reports. Enhanced Ecommerce reporting. Show ecommerce conversion funnels when you tag product and checkout pages. Page Analytics Chrome plugin. Get analytics for a particular page, to replace old in-page analytics. However, it doesn’t work if you are signed into multiple Google Accounts. Notifications about property setup. Troubleshoot common problems like domain mis-matches. Embeded Reports API. So you can build custom dashboards outside of GA quickly. Share tools across GA accounts. Now you can share filters, channel groupings, annotations etc easily between views and properties Tag Assistant Chrome plugin. Easily spot common setup problems on your pages using the Tag Assistant. Built-in user tracking. See our customer tracking guide for the pros and cons. Import historic campaign cost and CRM data (premium only). Previously, imported data would only show up for events added after the data import. Now you can enter a ‘Query Time’ to apply to past events, but only for Premium users. Get unsampled API data (Premium only - developers). Export all your historic data without restrictions Better Management API (for developers). Set up filters, Adwords links and user access programmatically across many accounts. Useful for large companies or agencies with hundreds of web properties.
Pulling Google Analytics into Google Docs - automated template driven reporting
The Google Docs library for the analytics API provides a great tool for managing complex or repetitive reporting requirements, but it can be tricky to use. It would be great if it was a simple as dropping a spreadsheet formula on a page, but Google’s library stops a few steps short of that - it needs some script around it. This sheet closes that gap, providing a framework for template driven analytics reports in Google Docs. With it you can set up a report template, and click a menu to populate it with your analytics results and run your calculations - without needing to write a line of script - the code is there if you want to build on it, but you can get useful reports without writing a line of script. Prerequisites While you don't have to write code to use this, there are some technical requirements. To get the most out of it you'll need to have: your Google analytics tagging and views set up familiarity with Google’s reporting API familiarity with Google Docs spreadsheets - some knowledge of Google apps scripting is an advantage If you are looking for something more user-friendly or tailored to your needs, contact us and book a consultation to discuss - we can help with your analytics setup and bespoke reporting solutions. Getting started Setting this up takes a few steps, but you only need to do this once: Open the shared Google spreadsheet Make a copy Enter a view ID in the settings sheet - get this from the Google Analytics admin page. Authorise the script Authorise the API - in the API console - this is the only time you need to go into the script view using Tools|Script Editor Once in script editor select Resources|Advanced Google services On the bottom of the Advanced Google services dialogue is a link to the Google Developers Console, follow this and ensure that Google analytcs API is set to On You're done. You can go back to the spreadsheet and run the report (on the Analytics menu). From now on all you need to do is tweak any settings on the template and run the report. Setting up your own report template You can explore how the template works using the example. Anywhere you want to retrieve value(s) from Google Analytics, place this spreadsheet function on the template: = templateShowMetric(profile, metric, startdate, enddate, dimensions, segment, filters, sort, maxresults) This works as a custom spreadsheet function, for example =templateShowMetric(Settings!$B$2,$B7,Settings!$B$3,Settings!$B$4,$C7,$D7,$E7,$F7,$G7) Note that in the example, several of the references are to the settings sheet, but they don't have to be, you can use any cell or literal value in the formula - it's just a spreadsheet function. To get the values for the API query, I'd suggest using Google’s query explorer. To set this up for a weekly report, say, you would have all the queries reference a single pair of cells with start and end dates. Each week you would change the date cells run the report again - all queries will be run exactly as before, but for the new dates. Using spreadsheet references for query parameters is key. This opens up use of relative and absolute references - for example if you need to run the same query against 50 segments, you list your segments down a column, set up segment as a relative reference, and copy the formula down spreadsheet style. You can use this to do calculations on the sheet and use results in the analytics API, for example you might calculate start and end dates relative to current date. Future posts will cover setting up templates in more detail. Under the hood The templateShowMetric function generates a JSON string. When you trigger the script, the report generator copies everything on the template to the report sheet and: runs any analytics queries specified by a templateShowMetric function removes any formulas that reference the settings sheet (so you can use the settings sheet to pass values to the template, but your reports are not dependant on the settings staying the same)
Analytics showing wrong numbers for yesterday's visits
We've noticed a few issues with clients using Universal Analytics this last month, when visits for the last day have been double the normal trend. It then corrects itself a few hours later - so seems to be just a blip with the data processing at Google. Others have noticed the same problem. The temporary fix is to only generate reports with time series ending the day before yesterday. i.e. ignore yesterday's data. Now Google have officially acknowledged the problem Looking forward to seeing that one fixed!
Measuring screen resolution versus viewport size
There’s a difference between the ‘screen size’ measured as standard in Google Analytics and the ‘browser size’ or ‘browser viewport’. Especially on mobile devices, there are pitfalls comparing the two. Browser viewport is the actual visible area of the HTML, after the width of scroll bars and height of button, address, plugin and status bars has been allowed for. Desktop computer screens have got much bigger over the last decade, but browser viewports (the visible area within the browser window) are not. The CSS tricks site found only 1% of users have their browser viewing in the full screen. While only 9% of visitors to his site had a monitor less than 1200px wide in 2011, around 21% of users have a browser viewport of less than that width. Simply put, on a huge monitor you don’t browse the web using your full screen. Therefore, 'screen resolution' may be much larger than 'viewport size'. The best solution is to post browser viewport size to GA as a custom dimension. P.S. Google Analytics does have a feature within In Page Analytics (under Behaviour section) to overlay Browser Size, but it doesn’t work for any of the sites I look at.
How many websites use Google Analytics?
Google Analytics is clearly the number one web analytics tool globally. From a meta-analysis of different surveys, we estimate it is currently installed on over 50% of all websites or 80% of operational websites using any kind of analytics tracking. We looked at the following sources for this chart: Datanyze survey of Alexa top 1m sites (04/2014) BuiltWith survey of all websites (04/2014) MetricMail survey of Alexa top 1m sites Pingdom survey of Alexa top 10k sites (07/2012) W3Techs survey of their own sites (04/2014) LeadLedger survey of Fortune 500 sites (04/2014)
What's included in Analytics traffic sources?
The Channel report in Google Analytics (under 'Acquisition' section) splits out into 6 or more types of visit channel: Direct Where a visitor has: typed the URL into the address bar clicked on a link which is NOT in another web page (e.g. in a mobile app) visited a bookmarked link Organic Search All visits from search engines (i.e. Google, Bing, Yahoo) which were not an advertisement. You used to be able to filter out people searching for your brand (which are more like Direct visits), but now the search terms are not provided. Paid Search Visits from search engines where the visitor clicked on an advert. Referral Where a visitor has clicked on a link in another website (not your own domain), but not including search engines or social networks. Social Networks Specifically links from known social network websites (including Facebook, Twitter, LinkedIn etc) Email From links tagged as medium = 'email'. Your email software needs to be configured correctly to add this tag. Display Links tagged as 'display' or 'cpm'. FAQs Can I change the channel groupings? Yes, you can change this under Admin .. (Selected View).. Channel Grouping. But we recommend you don't do this for your default view, as you won't be able to compare the historical data.
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