How to use Google Analytics for data

driven designan introduction into Google Analytics

In this presentationThis presentation is an introduction into data driven design. It provides you with some basic knowledge about Google Analytics. And shows how to use Google Analytics to evaluate your implemented designs.

After this presentation you are familiar with the glossary of (Google) Analytics. You will be able to gain relevant data from Google Analytics. And we provide you with some basic takeaways to implement data driven design in your projects.

Table of content• Part 1: Data driven design? A short introduction.

• Part 2: Google Analytics: The who, what & where.

• Part 3: How to use in a project: setting up your data for succes.

• Part 4: Analytics myths: busting some misconceptions.

Part 1 Data driven design?

A short introduction

understand the data and applying it for the betterment of product

and consumer understanding.

We, as webdesigners, have a desire to move forward in the right way.

To make sure that the right decision is made we try to

What is data driven design?• Quantitative vs Qualitative data

• Track, track and track some more.

• Numbers leave patterns, patterns tell stories

• Understanding opportunities vs issues

1.Quantitative data shows the who, what, when and where. Qualitative is non-numerical data that demonstrates the why or how.

Quantitative vs Qualitative

2.When it comes to data-driven design, the more data you have at your disposal the better; but only when that data is organised and manageable. Make sure you’re tracking your most important webpage elements (e.g. buy now button) first.

Tracking data

3.

Start by looking at the data you have. Whether this is web page visits, goal completions or customer feedback. Look for common occurrences and try to correlate these numbers (e.g. a high exit rate in a sales funnel and a lot of users that enter the information page may indicate an issue).

Numbers leave patterns, patterns tell stories

4.By assessing and ranking issues and opportunities together, you can begin to identify where to add more research effort and which to work on first.

Opportunities vs issues

The who, what and where

Part 2 Google analytics

Due to the vast amount of features it has become the most used

Why Google Analytics?

It’s a free and powerful tool that provides a lot of quantitative data.

web analytics tool.

Glossary

The user’s activity on your site (including just the loading of a single page).

Bounce

The number of times a visitor enters a domain on a page but leaves before viewing any other page in the domain, divided by the total number of views of that page. Also generally expressed as a percentage.

Bounce rate

An activity carried out by the user which fulfils the intended web page purpose (product purchase, download, newsletter subscription etc.)

Conversion

Google Analytics uses a lot of terms that need some explanation to fully understand what the data is telling you. So here is a short but

comprehensive glossary of the metric terms used in Google Analytics

Glossary

The total number of pages viewed. Repeated views of a single page are counted. However, for an accurate number, it’s important to look at unique pageviews because a single visitor can trigger multiple pageviews in one session.

Page views

The average number of pages viewed during a visit to your site.Pages/Session

A page is loaded or reloaded by a user.Page impression

A group of interactions a single user has within a given time frame on your website.Sessions

The number of times a visitor leaves your domain from a page, divided by that page’s total views. Generally expressed as a percentage.

Exit rate

The number of times visitors entered your site through a specified page or set of pages. Entrances

The total number of distinct devices that have accessed your site. Users

The percentage of visits that were first time visits (from people who had never visited your site before).

New sessions

The total number of visits to your site, from unique or repeat visitors. Visits

The number of unduplicated visitors to your website over the course of a specified time period.

Unique visitors

Navigation

The Google analytics interface can be quite a daunting thing to understand. In the following

slides we will explain where what kind of information can be found.

Navigation

Dashboard Create your own custom dashboard with widgets.

Intelligence Events Custom alerts for specific events (change in number of sessions, conversions, etc..).

Real-Time Pretty self-explanatory…

Audience Who (demographics, location, devices, etc..) has viewed your website.

Acquisition How did the visitors navigate to your website? Which channels did they use?

Behavior What did the visitors do on your website? E.g. navigation flows and search queries.

Conversions Did they convert? Which route did they take and how much time did they spend on reaching their goal?

Crunching numbers

It’s possible to add another layer of information to most of the graphs & tables by

adding a segment. This will make it possible to compare multiple types of information.

E.g, in the following slides we show how to add a segment to compare all sessions (all traffic) with the mobile- and tablet traffic.

Adding segments

Step 1 Audience (You can add segments to each of the information categories).

Step 2 Select: ‘Add Segment’

Step 3 Select the type(s) of information you wish to view in the graph / table.

Step 4 Analyse the data.

Import segments

Lots of custom made segments are available from the Google Analytics community. These segments can be imported and can give new insights in your data, such as additional info

about social media traffic or the level of engagement.

Import segments

Step 1 Select: ‘Add Segment’

Step 2 Select ‘import from gallery’

Step 3 Select ‘import’ for the desired plugin

Filter metrics

Filters allow you to isolate certain results in the data charts. E.g. these filters can be added to find pages with a high bounce rate, low exit

rate or a high page value.

In the following slides we show how to add a filter to find all pages with a bounce rate less than 60%.

Filter metrics

Step 1 Select: ‘Advanced’

Step 2 Select include or exclude and the value type (e.g. exit rate, bounce rate, unique pageviews).

Step 3 Select: ‘Advanced’

Step 4 Select value and apply

Step 5 (optional) Add a segment to further focus your data.

Goals

Goals measure how well the site or app fulfils a target objective (convert). Google Analytics

defines micro goals (e.g. step 1 in a sales funnel) and end goals (e.g. checking out).

Goals

With a destination goal (e.g. buying a product) you can specify the path you expect the

traffic to take. You can view information about this funnel in the Goal Flow and Funnel

reports.

In the following slides we will show you a couple of ways to view the goal data in Google Analytics.

Destination goals

Conversions page This example shows all the completion data in one graph and one table. A bit messy in my opinion. Luckily there is another way to view this data..

Funnel visualisation Shows all the stats about the sales funnel in one easy to understand page!

Micro goal #1 Amount of completions of the first micro goal (e.g. first step of the funnel)..

Micro goal Open the dropdown to view another micro goal timeline.

Funnel visualisation This shows the conversion rate and the amount of people that enter and leave each step of the sales funnel.

Setting up your data for succes

Part 3 How to use in a project

Thing to take in consideration• Key to succes: be specific

• Focus your efforts

• Develop a common language

• Quantitative & qualitative

• The definition of succes is not always the same

• Keep your data clean

The best kind of data is the kind that answers a specific question that can lead directly to a

change in design.

E.g. questions such as “how is the website performing?” won’t help you to improve your

designs. Questions such as “in which step of the sales funnel do mobile visitors drop out?”

are much more specific.

Key to succes: be specific

You can’t isolate variables when looking across big aggregated metrics (e.g. overall page views or downloads). This makes it difficult to

draw conclusions from your data.

Key to succes: be specific

“All data in aggregate is crap” – Avinash Kaushik

Analysing data can be resource-intensive. Don’t just track pages and elements.

Always use specific, empirical data — don’t offer “high-level” metrics. Find data points that

answer specific design questions and, thus, illustrate whether design or content changes

worked.

Focus your efforts

Develop a common language with the analytics tool and your project team.

Educate your team so that they understand the importance of metrics.

Develop a common language

Use quantitative and qualitative data together while redesigning a page. Qualitative data will

help you to answer the ‘why’ of the ‘what’ (quantitative data).

Quantitative & Qualitative

Take the goals of individual pages and different users into consideration. A returning visitor might have different needs from a new visitor, a redirected visitor might have different

needs from a visitor from an organic search.

The definition of succes is not always the same

Polluted data will affect your design choices. Exclude your own traffic from reports and

install spam blocking plugins to prevent (SEO) spam traffic filling up your data reports.

Keep your data clean

Busting some misconceptions

Part 4 Analytics myths

Often people assume the bounce rate represents people who land on your site and

leave straightaway. However, the number indicates the percentage of visitors that leave

your website without visiting another page. So for single page websites a high bounce rate is

inevitable.

A high bounce rate is an awful thing

The unique visitors count the number of cookies dropped in a browser. Often people

assume this shows the amount of people (and therefore size of audience) that are engaging on their website however this metric cannot indicate unique browser or even computers.

Unique visitors are people

The average visit duration report underestimates the actual time sped on a site. The calculation used does not account for the

time sped on the last page they view before leaving the site. So this report shows the

average time sped navigating the site.

Average Visit Duration reports shows

how long people spend on a site.

Direct traffic shows the traffic from sources that are not indexed by search engines like:

emails, instant message services, links in offline documents, redirect pages, bookmarks

or a javascript link.

Direct traffic comes from typing the address

into an address bar

In conclusion

Conclusion• Analytics are a great way to get information about the

performance of a web service.

• Be specific, gather your data empirically.

• Always use the quantitative data in combination with the qualitative data for the best results.

Statistics may be dull, but it has its moments.

Questions? E-mail me at mark@sodastudio.nl

Good luck!