Conversion Lag Report Explained in Google Analytics Attribution

In the context of attribution reports, a conversion can be a goal completion and/or ecommerce transaction. 

A conversion lag (known as ‘time lag’ in GA multi-channel funnels reports) is the number of days to conversions.

The length of conversion lag depends upon the amount of buying consideration involved. 

For example, when it comes to buying a greeting card, people often do not spend days and weeks researching which card to buy. So when they see an ad on greeting cards and they like the card they see, they would just go ahead and buy it (provided they have a reason to buy a card). 

Since a very small amount of consideration is involved in buying a greeting card, the conversion lag tends to be very short (usually a couple of hours or days).

However, when it comes to buying a house, people often spend weeks and months researching which house to buy. So when they see a property ad, they don’t just go ahead and purchase the property straight away even when they like it. They are going to spend weeks/months doing research on that property. 

Since a lot of consideration is involved in buying a house, the conversion lag tends to be very long (usually a couple of weeks/months),

In the offline world, the conversion lag is known as the ‘sales cycle’. 

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Introduction to Conversion Lag report

Through the Conversion Lag report, you can determine the number of days it takes on an average for customers to complete one or more conversions on your website under a particular conversion credit model (aka attribution model).

The Conversion Lag report is similar to the Time Lag report you see in GA multi-channel funnels and is used to understand the length of your conversion/sales cycle under a particular attribution model.

In order to access the Conversion Lag report follow the steps below:

Step-1: Navigate to https://analytics.google.com/analytics/attribution/ 

Step-2: Click on the ‘Conversions lag’ link on the left-hand side:

The top row of the Conversion Lag report provides an overview of how long it takes for selected conversion type(s) to occur under a particular attribution model. 

The top row shows not only the average number of days to selected conversion type(s) but also the total number of conversions, total revenue, and two blue bar charts.

The two blue bar charts represent the percentage of total conversions and the percentage of total revenue. 

All rows others than the top row, show total conversions, total revenue, and the two blue bar charts for each day to selected conversion type(s).

The Conversion Lag report is sorted by ‘Days to conversion’ and you can not change the sort order.

Note: By default, the Conversion Lag report shows data for all conversion types. In order to see the Conversion Lag report for a particular conversion type, select the conversion type from the drop-down menu:

Conversion Lag report settings

You can change the settings of your Conversion Lag report by clicking on the ‘Edit report’ button on the top right-hand side:

Once you clicked on the ‘Edit report’ button, you would see the ‘Report Settings’ panel:

Through the report settings panel you can:

  • You can change the conversion credit model (aka the attribution model) used by the Conversion Lag report.
  • You can change the way data is displayed (cumulative or non-cumulative) in the Conversion Lag report.

Cumulative: Use this setting, if you want the Conversion Lag report to show the conversion and revenue data from prior days for each day to selected conversion type(s). By default, the Conversion Lag report displays cumulative data.

Non-Cumulative:  Use this setting, if you do not want the conversion lag report to show the conversion and revenue data from prior days for each day to selected conversion type(s). 

You can also change the conversion credit model from withing the reporting interface of the conversion lag report by clicking on the ‘Conversion Credit Model =’ button:

Similarly, you can also change the way data is displayed in the conversion lag report by clicking on the ‘Display data = “ button:

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  17. Introduction to Nonline Analytics – True Multi Channel Analytics
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  21. Introduction to TV Attribution in Google Analytics Attribution 360
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  36. How to Use ZMOT to Increase Conversions and Sales Exponentially
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  40. Conversion Time & Interaction Time Explained in Google Analytics Attribution
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Himanshu Sharma

Digital Marketing Consultant and Founder of Optimizesmart.com

Himanshu helps business owners and marketing professionals in generating more sales and ROI by fixing their website tracking issues, helping them understand their true customers' purchase journey and helping them determine the most effective marketing channels for investment.

He has over 12 years of experience in digital analytics and digital marketing.

He was nominated for the Digital Analytics Association's Awards for Excellence. The Digital Analytics Association is a world-renowned not-for-profit association that helps organisations overcome the challenges of data acquisition and application.

He is the author of four best-selling books on analytics and conversion optimization:

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