Time Lag Report in Google Analytics

I’ve been working with Google Analytics for past 5 years and there are still a lot to learn. I would like to review one of my new insights in this post.

Google Analytics has a variety of reports you can use for making day-to-day decisions. It is hard to keep track of all the changes in Google Analytics even for experts. I’ve heard and looked at Time Lag reports a lot – but I’ve never actually dug in, to truly understand them. When I looked at the report for first time it seemed to me easy and pretty straight forward. In reality you need to really dig into the data to realize that there are more questions than answers in this report.

First, I would define time lag as “the difference between the first interaction date and conversion date within a look back window”. Let’s define these three concepts:

  • Interaction date –
    • In GA PREMIUM – a view of a display ad (as well as a click), or click on any other ad, or a visit from a source such as Direct, Referral or other non-paid source
    • In GA Standard – a click on an ad or visit from Direct, Referral, or other non-paid source
    • INTERACTION in this report is not equal to a SESSION. Interaction has a broader meaning since it includes impressions, clicks, rich media, etc. In other words an Interaction includes direct or indirect clicks/views on your marketing content (where views can be tracked).
  • Conversion date –
    • It is a date when user converted, i.e. placed a transaction or performed any other conversion action.
  • Look-back window –
    • A period of time in days before conversion date; Google Analytics is searching for all the interactions of this user within look-back window with your marketing content and selects the earliest date it is able to find within this period. If an interaction is registered outside of the look-back window it is not included into calculations. Let’s assume that look-back window is equal to 30 days. If user interacted with the content 31 days before conversion date and then returned in 31 days and purchased the time lag will be equal to 0, i.e. the interaction with purchase will be considered as the first one.

Next, we need to calculate the difference between A) a date of the first interaction and B) a conversion date, within that C) look back window.

(1st interaction date) – (conversion date) = time lag, where

  • There may be other interactions after the 1st interaction (here, we only care about this 1st interaction)
  • Look-back window is set to any period between 1 and 90 days

So, that calculation represents Time Lag in Days you see in the report. Note that the report provides several additional filters like Conversion Segment, Type and Interaction Type.

Now, let’s look at the below sample report:

Here, screenshot a Time Lag report.

Immediately, we see that 84% of conversions happen within a Time Lag of 0. Google doesn’t provide a description on the exact calculation of the metric and it causes misunderstanding. Generally speaking it tells us that visitors interacted with your content and purchased products at the same day This means that if a prospect clicks on a paid search ad or just visits this website directly at 12:01 am, he or she is going to purchase an item by 11:59 pm. Note that if users interact with your content first time at 3 pm time lag = 0 will be assigned in case they convert till 11.59 pm at the same day.

  • We see this ‘quick to purchase’ behavior a lot with brands with lower average item value, where the consideration cycle is short. Also, for brands that are very well known, with lots of TV or print marketing, most of customers tend to convert in the first 24 hrs after a visit – they know and trust the brand, regardless of the price point.
  • However, for brands that sell expensive items such as refrigerators or mattresses, as expected that graph is much ‘flatter’ – people don’t buy expensive items on a whim.

In most cases this bucket is the major one. Note that it includes users who had 1 or more interactions, i.e. users could interact with your site several times before making a purchase but within the same day – from 12.00 am till 11.59 pm. Number of interactions is called “Path Length”. You can use it to create conversion segments to analyze any particular sub-section of the selected conversions. In addition there is another report “Path Length” which can be used for further drill down.

All the above features are extremely helpful for understanding how quickly your customers convert after direct or non-direct interaction with your content. Using conversion segments you can identify groups of people who tend to convert immediately after a particular type of interaction like paid search or banner. Now you are ready to get started with the new awesome feature in Google Analytics.

Posted under Google Analytics, Web Analytics by Alexander Malyshko on 8th May, 2015

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