So, following on from Part 1 of implementing the new Google analytics, which can be found on my Google + page
Step 5 New Google Analytics: Understanding Reporting And Visualisations — continued
# 1 : Webmaster Cognition
What this means is that now, the webmaster has a more intuitive form of reporting that helps him predict the future of a design or content piece, much more effectively than before.
The best part is that a huge chunk of features from Google Webmaster Tools are now integrated into the new Google Analytics (GA).
Let’s understand with the help of examples.
1. Keywords
Imagine you buy 2 keywords that have lots of clicks. But one of them is attaining goals and getting you buyers at the end of the funnel, whereas the other is scaring traffic away. Ideally, you should take out all your budget from the campaign and start a new one focusing on that exact keyword which really brings in a huge amount of buyers.
That’ll save money and increase revenue.
How do we see what this keyword is?
That’s where Webmaster cognition comes in.
Open up the dashboard relevant to the campaign and select the “traffic sources” option. Under this, select “Keywords”.
Now you’ll see a list of all paid and non-paid keywords that users type in to discover your site. On the right side, you’ll notice a small button that says “Compare to Site”.
This button will bring up a keyword cloud that shows you all the keywords in their mighty sized form. The bigger the keyword the more relevant traffic it brings in, which means the more CPC you should assign to it.
2. Property Monitoring
The next part of webmaster cognition is presentation of Google property reports. This is also a side benefit coming from the inclusion of webmaster tools.
These are tabulated forms of traffic data that tell you the impressions, clicks, average position and click through ratio (CTR) of a particular web-property.
In the reporting section, look for the custom reports option and select the properties you wish to monitor. For some users this may not be visible as their site operates on a single medium and hence the code is hit by only a single type of visitor. In that case, default settings are applied.
The report will be in the form of a table giving properties like
–Mobile (Smartphone)
–Web
–Image
as the rows and…
–Impressions
–Clicks
–Average Position
–CTR
as the column attributes.
3. Social Engagement Monitoring
Again, in the reports section, you can find the “social source and actions” tabulated. Or better yet, if you’re switching from the old GA to the new GA, under the “visitor” option in the analytics navigation, social media interaction was shown. You can recall that to understand this.
The same has been re-tabulated and better categorized in the new GA. The new social engagement table, called the “Social Source and Action” table shows,
Social Media signals like:
- Google: +1
- Facebook: Like
- Facebook: Send
- Twitter: Tweets
as the table rows and…
–Visits
–Pages/Visit
–Average Time on Site
-% New Visits
–Bounce Rate
as the column attributes.
# 2 : Presenting Stats And Visualisations
Visualisations are now more perceptive and allow for quick analysis. So instead of waiting for stats to appear and then reading through tables upon tables upon tables of cumbersome percentages, things just became so much better.
You now have the ability to see real time information from the website and a set of easy to interpret cross-linked mind maps to monitor visitor flow and goal flow.
There’s 3 ways this has been implemented:
- Real-Time Stats
The old GA would serve you data after a 24 hour delay in most cases. Well now, activity is monitored as it happens. Reports for
–Active Pages
–Top Referrals
–Page views
–Keywords
are created real-time and you can see what your top active sources for traffic and engagement are, as well as the best referring URLs. A key benefit of this is that you can monitor a test campaign as it takes place by doing it on a small scale first.
If the results are favourable, go a for a bigger launch!
Here’s a sample of what Real-Time stats look like:

- Graphical Measures of Tendency
Sounds complicated, right? It’s easy though.
A measure of central tendency is basically an average, or more commonly used — a median value. And any other measure or percentage of total is a trend indicator. These are currently deployed for three analytics functions:
–Site Speed (Average page loading time in seconds)
–Page views
–Page Load Sample
The report being a graph easily gives you the median value or the trend line based on the function selected on the top of the trend indicator. Here’s a sample of what it looks like: 
- Visualisations
GA offers special criss-crossing mind map visualisations to map goal flow and visitor flow in a campaign. These can be accessed in the sections of your dashboard where you get the goals summary and funnel analytics.
What they reflect essentially varies between what goals you set and what pages they include. Hence, visualisations and what you can do with the data would vary from site to site.
A “visitor flow report” can be generated at the click of a button that gives you an idea of how visitors move along your site, so that you know where best to set your target pages.
A “goals flow report” essentially shows you where in your sales funnel do people drop off or repeat actions. This will help you find those tweaks your funnel needs in order to get more people to a goal and raise conversions.
Here’s a video explaining goal flow and it’s significance in depth:
# 3 : Funnel Dissection And Event Tracking
In the old GA, figures reported about conversions could lose their accuracy from time to time due to a major problem:
“Rigid Goal Interaction”
This meant that you had to have a new destination URL for all your goals to get accurate stats. If there wasn’t a destination URL, a virtual page view had to be generated to see the action taken by the user.
So you had to install a special code snippet on the page near the end of a goal definition, which would corrupt some of the analytics data you got. And you could not monitor user engagement and activity on your site very well.
Actions like viewing videos and documents or acrobat files wouldn’t get tracked without inflating the other metrics.
But now, the new GA allows you to modify your goal settings within each goal set. In your goal settings, just point to the event conditions list.
Then, just fill in the
–Category
–Action
–Label
–Value
for an event that occurs during the conversion process and it will be monitored separately.
The above mentioned attributes of category and label are entirely user defined and you can have all the flexibility in classifying and labelling a user action the way you like.
Another shortcoming of the old Google Analytics was a Webmaster’s inability to track conversions from a process lower in the conversion hierarchy.
What does that mean?
Let’s understand the consumer for a minute. Very few prospective customers will ever make a buying decision based on a single exposure of a brand, service or product. This means repeated exposures are more likely than ever, a “required” marketing effort.
When you can’t track conversions from processes lower in the hierarchy, it means that the effectiveness of the message delivered before the final message when the buying decision was made, get heavily undermined.
Example:
A consumer may have wanted to buy an app when you explained it in a launch video, but the credit for the conversion went to the sales letter or the email newsletter.
The new GA helps you track back your effective conversion activities behind the final channel of user engagement in a sales or lead funnel. It breaks down your funnel into multiple channels, with each channel focussing on a particular marketing activity such as a
- paid search ad
- launch
- sales page
- product portfolio
- organic search result
- referrals
- social media activity
…and many other activities that can have the analytics code embedded on a page. In your report for the dissected funnel, you will receive a visual representation of the funnels with a path telling you how the conversion took place.
It will show you the impact of your marketing from the past 1 month of time, including all the channel paths or channel-groups in a path (forming a channel grouping path) that made the conversion effective.
For more info creating and using channel grouping, refer to that link
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Step 6
A Crash Course On Working With Reports
Okay, so now that you know the “purpose” of the most useful GA features, it’s time to recognize the GA interface and get a grip on it’s on-ground operations. You now need to know about the basic report views and analytics usage.
So let’s delve right in.
But wait, before we really jump in, I want you to know that if at any point you feel overwhelmed or can’t find what you’re looking for, Google’s main activity — “Search” — is here to help you.
That’s right.
Google’s got a search box specific to analytics right there in your account! So if you feel lost, just type in what you’re looking for and your dashboard will fetch it for you. Navigation doesn’t get any simpler.
Onward…
- Time Control
The GA calendar gives you the active date range settings option. This is the slot of time for which you want to fetch and analyse data. Select the active date range by selecting days and months in the calendar. You can also type it into the input boxes to the right of the calendar.
Multiple data ranges can be set to compare the performance of a site from day to day, month to month or year to year. These comparisons will be reflected in all graphs and reports.
The Analytics timeline will show the traffic trends of your site.
- Graphs and Annotations
Most reports will have graphs towards the top. The time units for these graphs can be altered by day, week or month.
Graphs will also allow you to select special dates on the time-axis and attach annotations to them. To do this, just click on the date on the graph and in the pop-up click on “create new annotation”. You can also modify its visibility and make it private if needed.
These annotations are useful during special campaigns and launches. They stand out from the rest of the data and let you figure out if a certain event of marketing activity had an impact on your analytics data.
- Metrics
Metrics are “measurements” such as:
- Number of visits
- Pages viewed per visit
- Average time on site
These metrics will appear as scorecards and as column values in tables.
They can also be graphed. When viewing a set of scorecards or even a single scorecard, you can request a graphical view by just clicking on it.
The scorecard number, ratio or percentage will maximize into a small trend line graph.
- Metric Correlation
Correlation between two different metrics can be determined by viewing their graphs together. To do so, click on “compare metric”, which is right above the graph trendline.
A drop down menu appears. From this menu, select the metric you wish to compare.
- Explorer Tabs
Under the Explorer section of the dashboard, groups of metrics will be found organised into tabs. Clicking on each tab will show a different set of scorecards for that group of metrics.
For example:
The ‘Site Usage’ tab shows the visits, pages per visit, average time on site, bounce rate, revenue etc.
The ‘Goal Set’ tabs show specific conversion rates for each of the goals you set in the beginning.
The ‘Ecommerce’ tab shows revenue, transactions, per visit value and other metrics pertaining to the ecommerce store’s group of metrics.
- Adwords Report
These reports will feature additional tabs in the explorer sections. The tabs are:
- Clicks (shows CTR, CTC, RPC, Clicks, ROI and Margins)
- Adsense (shows Adsense Revenue, Page Impressions, CTR etc.)
- Tables and Dimensions
A lot of your reports will contain tables. Such tables will break-down your data by a single dimension, for ease of interpretation and classification.
“Dimensions” are mainly the criteria on which tables are based.
Examples:
Dimensions can be — Country/Territory, City, Continent, Sub Continent Region etc.
The rows in the table will provide information of different records stored in that table, based on the dimension selected. Say, if “City” is the selected dimension, then each row in the table will be a record for a different city.
To select a dimension, point to the horizontal list of blue hypertext links placed next to “Viewing” option on top of a table. These blue hypertext words are the dimensions allowed for the table.
- Secondary Dimension
Below the horizontal list of dimensions is a grey bar that allows you to select a secondary dimension. This means you can select another allowed dimension and combine the data of the two dimensions to see all possible combinations of metrics for the 2 dimensions held together in a single table.
Example:
You can select Operation System as a dimension and the browser used by the visitor as a secondary dimension. Thus, you can pinpoint the exact source of most of your traffic, by checking the given combinations of the combined table and analysing correlation.
- Data Filtering
In the same grey bar as the secondary dimension, you can click the “Search” option above the table. It allows you to filter out, i.e. “Exclude” certain values of a particular dimension.
Example:
If you use “Search” and exclude City Dimension Value ‘London’ from the ‘City’ dimension, then any records pertaining to London will not be displayed in the table.
- Report Views
Next to the ‘Search’ option above a table, there’s the View Option. Click on it and a drop down containing the following choices will appear:
- Data
- Percentage
- Performance
- Comparison
- Term Cloud
- Pivot
The Data view organises information into a table. It is the default view in most reports.
The Percentage view creates a metric specific pie chart, while the Performance view gives a metric specific bar graph.
The Comparison view gives a visual measure of metric values, telling you if an entry in the table is performing above or below average. You can go ahead and modify the entries that are lossy and see what can improve them.
The Term Cloud, as stated before, will help you visualise your keywords. Their importance is indicated by their size in the cloud.
The Pivot view creates a ‘pivot table’ in which both rows and columns are allowed to beak out dimension values.
As an example of Pivot, you can have a table with different row entries for different keywords and different column attributes indicating different traffic sources such as Google and Yahoo Search.
- Data Sorting
Columns in tables can have their information sorted in both ascending and descending order. To change the current order, simply click on a column heading.
The arrow next to a heading title will give you the order in which the entries are listed. The down arrow means descending order and the up arrow means ascending order.
To expand the number of results displayed in table from the default 10, click on the “show rows” option to the bottom right of the table and change the number of rows. the maximum number of rows that can be displayed is 500 per page.
- Advanced Segments
Advanced Segments are subsets of your data. They limit analysis to a certain segment of a dimension, based on a metric.
Example:
If you select the advanced segment: ‘Visits with conversions’, then all your analysis will get narrowed down to user activity that resulted in a goal being attained with a desired conversion. The need for manual filtering gets lowered greatly.
You can apply more than one advanced segment, to filter data in multiple ways. You can select up to 4 segments at a time. This lets you compare data for each segment side by side as you go through your reports.
The ‘All traffic’ segment allows you to remove the filter and view all your data again.
Apart from the default segments, there’s another category of segments called ‘custom segments’. While default segments are pre-defined and available to anyone using GA, custom segments are user-defined and contain your personalized analysis criteria.
For certain types of reporting, custom segments can act as really powerful filters and markers of cause and effect. But you should avoid getting caught up in creating too many of these, as it can make analysis cumbersome.
In other words, fly as your campaign would need you to.
And finally … [TL:DR]
With that, I hope to have laid down a basic primer to the world of GA and encourage you to go ahead in setting up new Google Analytics for your web business. With practice, experimentation and usage, I’m sure you’ll realise that it really is a powerful tool for your growth.
Let me know how you get on and remember Part 1 on implementing the new Google Analytics is on My Google+ page
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