Page Comparison

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This will allow you to calculate some engagement metrics for all or individual journeys:

• Start rate what % of my users start preezie when seeing it? 20% is a good benchmark to aim for

  • preezie users / preezie loads users

• Completion rate what % complete preezie after starting it? Over 85% is a good benchmark to aim for

  • preezie completed users / preezie users

• Improved engagement is preezie helping grow more engaged users?

  • preezie completed engagement rate vs non-preezie users

  • preezie completed views per user vs non-preezie users

  • preezie completed session duration/bounce rate vs non-preezie users etc.

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preezie users Include users when Events > preezie_click
preezie completed Include users when Events > preezie_completed
preezie loads Include users when Events > preezie_load
non-preezie users We’ll create a segment that includes where it was loaded but not clicked Include users when Events > preezie_loadExclude users when Add sequence to exclude Step 1: Exclude from segment permanently Step 2: Events > preezie_load is indirectly followed by Step 3: Events > preezie_click	Image Removed Image Added

Import these metrics

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• Total users

• Engagement rate - as defined by Google: Engaged sessions divided by Sessions

• Engaged sessions per user - as defined by Google: The number of sessions that lasted longer than 10 seconds, or had a conversion event, or had 2 or more screen or page views.

• Views per user - as defined by Google: The average number of mobile app screens or web pages viewed per user.

• Average session duration

• Bounce rate - as defined by Google the % of sessions that: lasted longer than 10 seconds, or had a conversion event, or had 2 or more screen or page views.

Create

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a segment report

Add the segments and metrics to your report, it should look something like this:

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If you establish how much preezie can help new users then you can use it as a dedicated landing experience for marketing/advertising campaigns, e.g. www.preezie.com/christmas-gift-finder

Create a journey name report

• Duplicate the preezie user engagement report rename it journey engagement

• Delete the 4 segments

• Import Dimension preezie_journey - this is the name of each journey

• Add this Dimension to your report, you’ll now see each stat by journey name

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🛒 Conversions and revenue

There are 2 reports you can now create.

1. preezie user conversion

Now using your segments you can create an additional report tab to analyse preezie ecommerce metrics.

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First, add another Free form tab and call it ‘preezie conversion'

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Add 2 segments

Add your preezie users and non-preezie users segments created in step 1 above, this will breakdown allow us to compare performance:

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Import these metrics

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• User conversion rate - we use this as preezie users drive more sessions

• Add to carts

• Ecommerce purchases

• Purchase revenue

• Average revenue per user

• First-time purchaser conversion - as defined by Google: Percentage of active users that completed their first purchase event for the time period selected.

• First-time purchasers per new user - as defined by Google: Ratio of active users that completed their first purchase event divided by new users for the time period selected. These two populations are exclusive.

Create the segment report

• Make sure the 2 segments are added to the report

• Change the PIVOT to first row

• Add the imported Metrics from above, plus Total users (already imported)

It should look something like this:

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2.

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Journey user conversion

We can also breakdown ecommerce metrics by journey by following these steps. Example metrics:

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• Duplicate your preezie conversion report and call it 'journey conversion'

• Import Dimension journeypreezie_user

Create the

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journey name breakdown report

• Add journeypreezie_user to a row

• All of the other settings inheried inherited from your preezie conversion report will appear here:

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❔ Answer trends

This will allow you to calculate some answer metrics, for example:

• What answers are most/least popular?

• Is there a correlation with certain answers to add to cart events?

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Set up

First, add another Free form tab and call it ‘answer trends'.

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Add a dimension of preezie_answer, this will expose the quiz answers:

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Create the report

• Add preezie_answer dimension to your rows - note, this also includes the question number as a prefix

• Add preezie_journey to your columns

• Add Total users and Add to carts to your Metrics

• Add Filters of preezie_answer <> (not set) and preezie_journey <> (not set)

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• What product result position is most commonly clicked?

• How often are users purchasing the exact recommended product?

• Which product gets the highest clicks?

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Import these metrics

• Event count

Create the report

• Add preezie_product_name, preezie_product_position and Product name dimensions to your rows

• Add preezie_journey to your columns

• Add Event count and Ecommerce purchases to your Metrics

• Add the segment preezie users - this will show us only those who have used preezie, clicked and then bought these products

You should now be able to match your products clicked (event count) with your purchased store’s product names (Ecommerce purchases):

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