Persona Analytics is included on the Pro plan and above and is switched on automatically. You don't need to request it. Persona tagging needs to be active before any data shows up.
Not on Pro yet? Persona Analytics is listed on the Pro plan card under Settings → Billing → Plans. If you're billed through Shopify, you'll manage your plan in Shopify's billing instead.
💡 Not sure how a number is calculated? Hover over any metric to see a tooltip explaining how it's computed.
How to open Persona Analytics
Go to Personas in the left sidebar.
Under the page title, switch the Overview | Analytics toggle to Analytics.
The Personas page always opens on Overview, so you'll switch to Analytics each time you visit.
The controls row
At the top of the Analytics view is a controls row that stays pinned to the top of the page as you scroll. It reads N of M personas · timeline · ranking:
Personas (N compared): how many personas you're looking at. Use it to pick personas to compare. See Compare personas below.
Timeline: the date window for the page: Last 30 days, Last 90 days, Last 6 months, Last 12 months or All time (the default).
Ranking: the order of the persona cards: Revenue share, Customer share, AOV or LTV.
How the date window changes the numbers
With All time selected, figures are lifetime figures. LTV and repeat rate are calculated across each customer's full order history with your brand and labeled as lifetime, both in the app and in export column headers.
With a shorter window selected, the cards switch to period figures. For example, ranking by LTV shows Spend per customer (period), which is spend within the window, not lifetime value. Period figures are always labeled so you can't mix them up with lifetime numbers.
Use a shorter window to see how a persona is performing right now, like during a promotion or over the last quarter.
The persona cards
Each persona has a compact card in the Analytics view showing:
Its rank and name
Its number of customers
Customers %: its share of your customers
A second figure that follows your ranking choice: Revenue %, AOV, or LTV (Spend per customer (period) when a date window is set)
The second figure is tinted green when the persona's revenue share is higher than its customer share, and red when it's lower. That's a quick read on which personas punch above their weight.
The Analytics view, section by section
1. Revenue over time, by persona
A stacked area chart of each persona's share of revenue (from persona-tagged customers) over the selected window. Switch between Monthly and Weekly, and hover to see exact values. Shorter windows switch to Weekly automatically. Use it to spot trends: is a persona growing or shrinking as a share of your revenue?
2. Revenue vs customer share, and product affinity
These sit side by side.
Revenue vs customer share. For each persona, this shows revenue share minus customer share, in points.
Right of the line, green (outperformers): the persona brings in more revenue than its size would suggest. These are your highest-value segments.
Left of the line, red (underperformers): the persona makes up a bigger share of customers than of revenue. That can be an opportunity: a large audience with untapped revenue potential.
Product affinity, by persona. One row per persona, showing that persona's standout product: the persona and product images side by side, the product name, how much more likely this persona is to buy it than your average customer (for example 3.1×), and the persona's revenue on that product. Click a row to open the product in Product Intelligence.
3. Discount vs full price
This section shows which personas tend to buy on discount and which pay full price in the selected window, with the number of buyers behind each figure.
Use it to:
Find personas you can reach without a discount, and protect your margin with them
Find personas that respond to promotions, and aim your sales and codes at them
Check whether a promotion reached the personas you meant it for
Seeing a dash (–) instead of a rate? When a persona has fewer than 10 buyers in the selected window, the rate is replaced with a dash, because a rate based on a handful of buyers isn't reliable enough to act on. Pick a longer window to include more buyers.
4. Compare personas
Compare up to six personas side by side.
In the pinned controls row, click the N compared button.
Tick the personas you want on their cards (at least two, up to six).
Click Compare N to save your selection. Click Reset to go back to all personas.
Once the controls row is pinned at the top while you scroll, the same button opens a dropdown with checkboxes.
The comparison shows a table with personas as columns and these metrics as rows: Customer %, Revenue %, Avg LTV, AOV, Repeat Rate, Lifetime Orders and Revenue Index. In each row the highest value is green and the lowest is red. Next to it, a radar chart shows each persona's overall shape.
Set up your Klaviyo playbook
If Klaviyo is connected but you don't have a playbook syncing personas to all customers yet, a prompt at the top of the Analytics view reads Set up the all-customers Klaviyo playbook: Sync personas to every customer profile in Klaviyo. Click Set up to open the playbook builder with the all-customers stream template ready to go. Persona Analytics works without it, but this is what puts persona data on your Klaviyo profiles so you can build persona-based segments and flows.
Persona profile
To see everything about one persona, open its full profile from the Overview view (click Expand on its card). The profile has a banner and four tabs. Click the × in the top-right corner of the banner to go back to all personas.
Overview
Who they are: Key motivations and Why our brand appeals side by side, then a Demographics summary covering profession, socioeconomic status, family status and geography
At a glance: eight figures: Revenue index, Share of your business, Avg LTV, Repeat rate, AOV, Lifetime orders per customer, Days between orders and First to repeat
Shortcuts to See Demographics and Compare personas
Demographics
Who this persona is, in two groups:
People: Age (average, median and an age-range chart); Where they live (a US map with the top states); and gender, Education (share with college or above) and Property value (median and average)
Work: Top occupations, Industries and Notable employers
Products
What they're buying:
Favorite: this persona's #1 product, with units, revenue, share of the persona's product revenue, and how it compares to your brand average (for example 1.6× vs brand)
Next best sellers: the persona's next top products, each marked with how much more this persona buys it than your average customer (for example 1.5× vs brand) or about brand average
Buying patterns: Products per order, Distinct products (bought in the selected window), Top 5 share (of persona product revenue) and Category mix of the top 5.
Customers
Core persona customers: the top five customers by persona affinity (with a photo on file). Each card shows their name and title, a one-line description, their last order, total spend and number of orders.
Persona pulse: the share of this persona carrying a VIP signal, the number of customers in the persona, the average lifetime value of the top five, and how much the top five spend compared to the persona average.
Use it to find standout customers in a persona for personal outreach or VIP treatment.
Exporting
From a persona's profile: three buttons at the top left of the banner:
Export CSV: this persona's customer list, for Meta, direct mail platforms or any other tool
Send to Meta Audience: send directly as a Meta Custom Audience source for building Lookalike Audiences
View in signal feed: open this persona's customers in your signal feed for more filtering, segmentation or playbooks
From the Personas page toolbar (under the title, on the right):
Download PDF: your persona report as a PDF
Export Analytics: choose CSV or PDF, pick which sections to include (revenue, demographics, geography, products) and which personas
Export Report: have the persona report emailed to you
Export column headers match the in-app labels. For example, LTV and repeat rate columns are labeled as lifetime figures.
Ready to put this data to work?