An overview of field types, and ideas on how to use them in Plecto.
You can choose to segment the data by these dimensions:
- Source Medium
- Product Name
- Country and Region
- Country, Region and City
If you choose e.g. Campaign, Plecto will create one registration per campaign per time dimension (e.g. hour, day, month, year)
It is very important to think about what time dimension you want to look at when you create the data source in Plecto. This is crucial for the total number that will end up on your dashboard when you show e.g. the number of users.
Example: In one day you have 100 users that visit your website. The next day the same 100 users come back. Even though it is 200 visits, it will still be the same 100 users in total. If you want to show this number on a daily time period, your time dimension should be 'Day' when you set up the data source. If you want to look at how many users that have visited your website each month, your time dimension should be 'Month'. This basically means that you should create 2 data sources; one with 'Day' as time dimension and the other with 'Month' as time dimension.
What you need to know when you create your data source
Not all dimensions and field types can be combined in Plecto. At the moment, only certain field types can be used together to create valid combinations in your Google Analytics data source. To achieve the best result, you create a data source for each report you have in Google Analytics.
The following will give you an overview of which metrics/reports that are possible to visualize in Plecto:
- Time dimension: Hour, Day, Month and Year
- Field Types: User - New Users, User - Users, Session - Hits, Session - Sessions, Page Tracking - Avg. time on Page, Page Tracking - Pageviews, User - New Sessions, Session - Avg. Session Duration, Session - Bounces, Session - Bounce Rate
- Time dimension: Hour, Day, Month and Year
- Field types: Quantity Added to Cart, Transactions, Transactions, Revenue per User, Unique Purchases, Revenue, Shipping, Total Value, Traffic Sources - Organic Searches, Quantity Checked Out, Transactions Per User
- Time dimension: Day, Month and Year
- Field types: Goal Conversion Rate, Goal Completions, Total Abandonment Rate
- Time dimension: Day
- Field types: Ecommerce - Ecommerce Conversion Rate
Field types explanation
- Session – Sessions: A session is a user’s interaction with your website that results in data being sent to the Google Analytics server.
- Session – Avg. Session Duration: Average time spent on your website. This metric is one of the most common used by companies to track the traffic being driven to their website.
- Session – Bounces: Bounces are visitors who leave your website after viewing only one page. This can be an indicator of low-quality traffic.
- Session – Bounce Rate: The bounce rate is a metric that measures the percentage of people who land on your website, and do nothing further on the page as they entered. It is calculated by dividing all single page sessions by all sessions. A user bounces, when there has been no interaction with other pages on your website, and ends with a single-page visit. You can use the bounce rate to indicate the quality of a page on your website or whether the audience fits the purpose of your site.
- Page Tracking – Pageviews: The number of pages on your website that people have viewed in total.
- Page Tracking – Avg. Time on Page: Average time spent on one page on your website.
- User – Users: The number of people visiting your website – both unique visitors and returning customers.
- User – New Users: A unique visitor.
User Behaviour scenario and visualization example
If a visitor goes to Plecto.com and looks at our home page, our about page and our pricing page, that would count as 1 user, 1 session and 3 page views.
If the visitor, on the other hand, visits Plecto, looks at the front page and closes the tap, this would count as a bounce as there is no trigger sent to the Google Analytics server.
Is a high bounce rate a bad thing?
This depends on the purpose of the page on your website; if the purpose is only to inform, and people visit a page to read an article or a blog post, a high bounce rate is not a bad thing per se as the visitors close the tap after they are done reading or after they have found what they were looking for.
If the purpose of the page is to engage with the website, i.e. to get the visitors to look further on your website and read your content on the pages, a high bounce rate is a bad thing.
You can visualize your bounce rate in a speedometer in Plecto and preferably use conditional colors. Instead of just having white numbers on your dashboard, it gives a cool visual effect to use conditional colors, which also makes the numbers easier to browse through:
Things to be aware of with Google Analytics data:
Google Analytics (and some other marketing integrations) don't support importing raw data. This means that we are not able to show all metrics accurately for all time periods since data is accumulated per hour, day, week or month.
The number of unique visitors. One visitor can be counted as unique for every day in the week, but also only counted once for the whole week. Simply summing unique daily visitors would not give you the weekly unique visitors (7 vs 1).
When adding the data source you can pick the time granularity you would like to have. You should match this to the time period on your widgets to get the most accurate results.
Goals can only be imported by the goal number, so you have to know which goal corresponds to which number. For each goal, there will be a field created for the following metrics: Starts, Completions, Value, ConversionRate, Abandons, AbandonRate.
It is possible to link an Adwords account to a Google Analytics account to import ads data into an analytics data source. You cannot, however, use ads data in combination with the "hour" time dimension because AdWords data is only calculated once per day.
If you would like to see the source of the data then you need to set the Secondary Dimension to "Source Medium" in the advanced settings when you are setting up your data source. Then you will have a field in your data source that you can add to see the different sources of your data.
This is the view you get when you set up your Google Analytics data source and click on "Advanced Settings"