Where are users dropping off? Is mobile checkout pulling its weight? What would it take to lift conversion by half a point? Ask the question. Get the answer.
James Wright manages the Bloom & Measure online store. He knows the conversion rate is around 3%, but he doesn't know where the other 97% go. Is it a product discovery problem? A checkout problem? A mobile problem? He used to spend half a day building funnel reports in Looker Studio. Now he just asks.
Every answer below came from Askalytics using verified Q1 2026 data from the Bloom & Measure demo property.
"Where in the purchase funnel are we losing the most users?"
Sessions: 28,707
Add to Cart: 3,445 (12% of sessions)
Purchases: 857 (24.9% of carts)
The biggest leak is at the top. Only 12% of sessions result in an add-to-cart event. From there, roughly half of carts proceed to checkout, and 46.2% of checkouts complete a purchase.
With 3,445 carts and 857 orders, approximately 2,588 carts were abandoned in Q1. At an AOV of $65, that's a significant pool of recoverable revenue.
Confidence: Medium | Data: Google Analytics 4
That Confidence badge is our Confidence Check: every insight is verified by a second AI on a different provider. "Medium" signals the two providers broadly agreed but the staged funnel rates carry assumptions worth a second look before you invest in a fix.
"What is the checkout completion rate and how does it vary by month?"
Overall checkout completion: 46.2% (1,169 purchases from 2,530 checkout sessions).
January: 46.4% | February: 46.0% | March: 46.1%
Remarkably consistent across all three months. Valentine's Day drove a clear spike in checkout volume but didn't shift the completion rate, which suggests the checkout experience performs reliably even under seasonal pressure.
Confidence: High | Data: Google Analytics 4
"Compare mobile vs desktop conversion rates"
Desktop: 2.85% (14,267 sessions, 407 conversions)
Mobile: 2.83% (11,536 sessions, 327 conversions)
Tablet: 2.85% (1,650 sessions, 47 conversions)
The gap is just 0.02 percentage points. All three devices convert at nearly identical rates, which is a strong signal that the mobile checkout experience is well optimized.
Where devices do differ: session duration. Desktop users averaged 3 minutes 30 seconds compared to 1 minute 45 seconds on mobile. Bounce rate was 32% on desktop versus 45% on mobile. Mobile visitors move fast but leave more often without engaging.
Confidence: High | Data: Google Analytics 4
"What is the average order value on mobile vs desktop?"
Desktop: $65.41 (658 orders)
Mobile: $65.47 (531 orders)
Tablet: $65.34 (76 orders)
Virtually identical across all devices. A spread of just $0.13. This means customers are equally comfortable spending regardless of how they shop. The mobile experience isn't discounting or limiting basket sizes.
Confidence: High | Data: Google Analytics 4
88% of visitors leave without adding anything to their cart. Product discovery and page engagement are the primary constraints, not checkout friction.
2,588 abandoned carts in a single quarter. At $65 AOV, even recovering 10% of those through abandonment emails would add meaningful revenue.
Conversion rates and AOV are nearly identical across devices. The mobile checkout holds up. The opportunity is in reducing mobile bounce rate (45% vs 32% on desktop).
46.2% completion rate held steady through Valentine's Day peak. The checkout flow works reliably regardless of traffic volume.
This is how Askalytics works for product teams. Every insight is verified by a second AI through the Confidence Check.
Session to add-to-cart, cart to checkout, and checkout to purchase, each measured and comparable across devices and time periods. Ask where you are losing users and the drop-off shows up in under a minute.
Yes. Ask and you get conversion rate, AOV, bounce rate, and session duration by device. Often the gap is in bounce rate rather than conversion, which points you to the real fix.
From your live Google Analytics 4 e-commerce events, synced nightly into a private warehouse. The AI reasons over that warehouse and runs the queries it needs. Every number traces back to the exact query that produced it (the Advanced Breakdown), and any figure that does not trace is flagged.
Every insight is verified by a second AI on a different provider through the Confidence Check. A Medium badge means the two broadly agreed but staged funnel rates carry assumptions worth a second look before you invest in a fix.
Plans run from Scout $19 to Scale $149 per month. Start with a 14-day free trial, no card needed. Every free trial account includes the Bloom & Measure demo property. See full pricing.
Connect your analytics and ask where users drop off. The answer comes from your live data, not a benchmark report, and every figure is checked against your data before you ship a fix.
Get Started