Your performance dashboard lets you view your overall account performance and individual journey metrics. It can help you analyse what happened within a period of time as well as uncover opportunities to optimise and further grow your metrics.

Index

Performance metrics

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Sales performance

This module shows transaction level metrics related to preezie usage.

Assisted conversion

Assisted conversion is the rate of users that started preezie and made a transaction within the attribution window (30 days by default). A start is recorded when they answer their first question.

We measure from preezie starts to track all users who engage with preezie. The start action can immediately encourage more positive shopping behaviour. A preezie user's product decisions improve with each question as they better understand their browsing needs. Most users who start go on to complete preezie journeys and become more likely to buy, visit again and spend more over time.

Note, if your customer sales funnel is less than 30 days, then you can change from this default to 7-day attribution within Settings > Tenant settings > General > Days attribution - this change is immediate and set at the account level

Assisted revenue

Assisted revenue is the value of all assisted transactions in the attribution window.

This figure aggregates the total order value that originally started with a preezie action. The total is used to report on the user’s shopping behaviour after using preezie as this can range from a single recommended item to a variety of products the user found.

Avg order value

Avg order value is the sum of Assisted revenue divided by the number of transactions during the attribution window. You can use this to gauge how much preezie users spend in line with your overall website averages.

How to use Sales performance data

preezie influences user purchase behaviour over time, often directly benefiting your typical purchase lifecycle. We recommend comparing conversion rate and AOV against your website average using the same attribution window.

On average we see between 6-8% conversion rate, but expect 2-4x your average CR% depending on the nature of your products. Check out our case study with Curvy and learn how they achieved a conversion rate of 6.98% here.

Note, all Sales performance figures represent transactions found both in the date range you’ve chosen AND with a start that occurred within your 30/7 day attribution look-back window.

For example, under a 7 day attribution setting if a transaction was made yesterday but they started preezie 8 days ago it would not be shown in this part of the dashboard. However the start would be tracked in the other modules (see below).

Shopper insights

This module shows journey activity metrics related to preezie usage.

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Journeys completed

This is a total count of all journeys completed on your website(s). It increments every time someone flows through to see the product results.

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Remember, every completed journey is stored in your reports for you to analyse as customer data whether they clicked on the product results or not.

You can access journey breakdown stats in Reports > Views Vs Starts and Completions: https://admin.preezie.com/app/reports/viewsstartscompletions

Answers collected

This is a total count of all answers from all completed journeys.

Every answer is stored in your reports, including from incomplete journeys. This equals a lot of customer insight! You can access all of the answers in your Reports > Answers: https://admin.preezie.com/app/reports/viewsstartscompletions

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Email profiles captured

With the Lead capture feature turned on this number will show you the total count of email addresses captured at the end of your journeys:

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This is first-party data that can be used in many ways to be one of the most engaging email campaigns.

We have seen brands grow their emails captured by 5x when asking for an email at the end of preezie journeys. These can then be directly integrated with your email platform such as Klaviyo. Plus, with open rates of 60% the preezie results email has proven to perform even better than Abandoned Cart emails! Read our case study and learn how My Linen uplifted their email capture by 357% using the preezie Klaviyo integration.

All of these emails are available to view and download in your Reports > Leads: https://admin.preezie.com/app/reports/leads or sent directly to your marketing platform (see Klaviyo, Zapier, Custom API).

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If you’re not currently capturing email addresses contact your Customer Success team to learn more.

How to use Shopper insights data

Depending on the types of journeys you have, this data can feed into your:

User experience: use your user’s preezie answers as explicit data to help prioritise content or tailor website features
Inventory management: cross reference what customers want with your inventory levels
Product development: understand what customers want earlier and use those insights for product decisions
Marketing decisions: What is hot right now, what is trending, use this information to create relevant social posts, email campaigns, blogs and marketing material. Don’t forget, all email addresses captured are packaged with their journey answers to enable customer profiling into detailed segments
Email platform/CDP: You can directly pass your journey data into other platforms to segment, trigger and learn more from your campaigns

Engagement and coverage

This module shows utilisation metrics related to preezie usage.

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This will show you levels of preezie utilisation across your website. They are defined as:

Engagement

journey starts - shopper clicks Next to answer the first question
completions - shopper views their product results at the end of their journey
result clicks - a total count of each click to recommended product results
Completion rate - the rate at which shoppers go through the journey from start to finish
Avg time spend (sec) - the time from when preezie is loaded on the page until the journey is completed. Note, this count is only available from May 25th 2022 onwards.

Site coverage

preezie loads - whenever the preezie widget code is loaded on the page
coverage rate - the rate that a start (user answers the first question) occurs after preezie is loaded on the page
active journeys - the number of workflow journeys you have created in your account (pop-ups and selectors refer to workflows so are not counted as active journeys)

How to use Engagement data

These stats will tell you how utilised preezie is across your website. We typically see:

a range between 10-20% of preezie starts to your average website sessions gives you a clear user engagement boost
a completion rate of at least 70% will result in significant user conversion and data insight benefits
Case study: Learn how Guitar Center have successfully achieved a completion rate of 76% with the preezie solution

Funnel performance

Your overall account activity is displayed in this chart covering the stats defined above in Engagement.

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The ideal scenario is the completions count is as close to the starts as possible, this means once shoppers start their journey, they’re engaged and flow through to the end.

The Engagement table beneath the graph represents preezie event metrics on your website. The table is split into 3 columns:

Actuals count the event metrics based on the date range of
1. Loads - when the page is loaded with a journey on it
2. Starts - when the user clicks Next on the first question
3. Completions - when the user answers all questions and views the results
4. Result clicks - each click made to the product results
5. Transactions - every purchase made in this date range based on your attribution window
Funnel shows the % that makes it through each stage of the funnel from the initial Loads figure
- This can be used to show how effective your journeys are from start to finish
- For example, Completions ÷ Loads (7905 ÷ 55848 = 14.15%)
Stage conversion shows what % make it through each stage
- This can be used to see where any drop-off is occurring. A 100% stage conversion means all those that clicked from one stage progress to the next!
- For example, Starts ÷ Loads (9195 ÷ 55848 = 16.46%) i.e. when preezie is loaded on the page 16% engage and click through at least question 1

Note, Result clicks track can exceed 100% stage conversion as there can be multiple clicks to the product results compared to the number of completions (i.e. viewing the results set).

How to use Funnel data

This table will tell you where users are dropping off in your journeys and how engaged they are with the product recommendations. Use these metrics as a guide and benchmark how your journeys are performing. We expect the stage conversion ranges of:

10-20% of loads to your page views. This ensures enough user sessions of those who need preezie assistance can access it
10-20% starts to loads. Although this can vary based on where it is shown, e.g. embedded on home pages are ~10% whereas product category pages are ~20%. Pop ups range from 2%-10%
Over 70% completion rate shows users are engaged by your questions and keen to see the results, why not aim for 90%!?
Over a 50% result click through rate is key to demonstrating the results (and journey) was relevant and useful. To improve this think about your question count, how many results shown, and adding result pagination, sort by and answer selection.

Don’t forget, users who start preezie immediately show more beneficial browsing habits, due to their better understanding of their own needs and your product catalogue (think, the good in-store sales assistant effect!).

If you’re interested in improving your current performance, reach out to our Customer Success team to book in an Optimisation Session. Connect with the Customer Success team at support@preezie.com.

Charts

Below your main activity chart, you can see two further sales breakdowns. These two represent:

Conversion rate - showing the daily rate of start to transaction within your attribution window
Revenue - showing the daily transaction value that began with a preezie start within your attribution window

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Breakdown tables

Workflow breakdown

These tables will show you the breakdown of all your Workflows, Selectors and Pop-ups.

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The metric calculations are the same as the above Sales performance module.

Product breakdown

This breakdown shows an overall view of your most popular products recommended through preezie. To appear here, the product would need to be recommended via preezie.

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Top products shown - Pos 1/2/3/4/5/6+ represents the total times that product appeared in that position, it does not consider if the shopper saw them or clicked on them
Top product purchases - these are the top products bought after preezie was started. Use this list to compare against your usual top products, e.g. are preezie user’s buying different products than usual?
Top product clicks - these are the top products clicked on by shoppers when recommended in the preezie results

This is a great way to understand what products from your feed are being consistently matched against your shopper's answers. You can view a breakdown by workflow of all your product positions in Reports > Results: https://admin.preezie.com/app/reports/results

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How to use Product data

This table reflects your most seen SKUs based on your user’s needs. It can be analysed to view patterns in certain product attributes, e.g. sizing, style, or brands that are trending.

Use this data together with your shopper insights listed above.

Other settings

In your tenant settings, you can toggle these additional dashboard items.

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Dashboard type - If your account is focused on lead generation only, then setting this to Lead Gen will hide the Sales performance module in the dashboard. This is default set to Standard, so all dashboard modules are shown.
Attribution setting - by default, the attribution window for all transactions is set to 30 days; if your typical purchase lifecycle is typically less, you can change this to 7 days.

After you make the changes, the dashboard will immediately reflect your new settings and remain as such as you change date ranges and view reports.

Analysing preezie in GA4

We encourage customers to push preezie data directly into their GA4.

You can set this up here: GA4 event set up
A quick guide to setting up reports is here:
- Example GA4 reports for preezie journeys
- Example GA Universal Analytics reports for preezie journeys