Analytics Overview

The Analytics Dashboard in Account Editor gives you performance insights across every upsell surface and offer.

It’s your central hub for tracking revenue, conversion rates, and customer engagement — helping you understand which upsell strategies are actually working.

📊 Where to Find It

1. Go to Upsell Engine → Analytics.
2. You’ll see the Analytics Dashboard — a performance summary for all your upsells, A/B tests, and surfaces.
3. Use the Last 30 days filter (top-left) to adjust your reporting window.

🧩 Dashboard Overview

Each metric card highlights your store’s performance growth over the selected period.

Let’s break down each section of the dashboard.

💰 Total Revenue

Shows the total revenue generated from your upsell offers.

This includes all accepted upsells from Checkout, After Checkout, Thank You, and Order Status pages.

• Example: $4,066.91 ↑ 100%
• This means your upsells added $4,066.91 to store revenue in the last 30 days.

⚡ Conversion Rate

Represents the percentage of customers who accepted an upsell out of all those who viewed it.

Formula:

Conversion Rate = (Upsell Conversions ÷ Offer Views) × 100

• Example: 48.15% ↑ 100%
• Nearly half of all shoppers who saw your upsell accepted it.

👀 Total Views

Indicates how many customers saw at least one upsell offer.

• Example: 54 views ↑ 100%
• A higher view count means your upsell widgets are correctly placed and visible on key pages.

💵 AOV Lift (Average Order Value Lift)

Shows how much your upsells increased your store’s average order value compared to the baseline.

• Example: 22.27% ↑ 100%
• Meaning, your AOV grew by 22.27% thanks to accepted upsells.

👤 Customers

Displays the total number of unique customers who interacted with or accepted upsell offers within the selected date range.

• Example: 3 customers ↑ 100%

📈 Revenue Trends

Visualizes your upsell revenue growth over time.

• The blue line shows upsell-generated revenue (by day or week).
• Hovering over the line shows exact revenue values for each date.
• You can compare this to past performance (shown as the dotted line).

💡 Tip: If you see a sharp rise, it’s often linked to new offer activations or A/B test winners applied.

🌍 Surface Performance

Breaks down upsell results by surface — so you can see which stage of the customer journey performs best.

💡 Tip: If one surface consistently underperforms, review its offer visibility or layout.

🔄 Conversion Funnel

Shows how customers move through the upsell flow — from viewing to purchasing.

Each step narrows naturally, but major drop-offs help identify where improvements are needed.

🥇 Top Performing Offers

Highlights which upsell offers contributed most to total revenue.

Displayed as a color-coded donut chart showing:

• Each offer’s total revenue
• Its share of overall upsell sales

Example Breakdown:

💡 Use Case: Quickly spot your top earners and replicate their format or conditions.

👥 Customer Segmentation Performance

Shows how different customer groups performed based on interactions or user counts.

💡 Tip: Pair this with A/B tests to understand which audience segments respond best to certain offers.

🌎 Geographic Performance

Displays total upsell revenue by region or country.

• Useful for identifying high-performing markets.
• You can adjust targeting in future offers based on location-based success.

💻 Device Performance

Shows which devices generated upsell conversions.

• Example:

• Desktop: $4,066.91 (100%)
• Mobile: (if applicable)

💡 Insight: If desktop outperforms mobile, review how your upsell widget renders on smaller screens.

🧭 Customer Journey Flow

Visualizes upsell activity along the shopping journey — how many interactions occurred at each touchpoint.

💡 Use Case: Understand where customers are most receptive to upsells and plan accordingly.

📚 Pro Tips

• Review Analytics weekly to identify new opportunities for A/B testing.
• Use your top-performing surfaces as templates for new offers.
• Track AOV Lift alongside Conversion Rate for a complete success picture.
• Combine data from A/B Testing + Analytics to make data-driven decisions.

Updated on: 27/11/2025