> ## Documentation Index
> Fetch the complete documentation index at: https://docs.vortexiq.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Average Transaction, Klarna

> Average Transaction for Klarna stores. Tracked live in Vortex IQ Nerve Centre. How to read it, why it matters, and how to act on it.

**Metrics type:** [Supporting Metrics](/nerve-centre/overview#metrics-types-explained)  •  **Category:** [Payment Gateway](/nerve-centre/connectors#connectors-by-type)

## At a glance

> Klarna's **mean order value** in the period. Klarna AOV is structurally 30 to 45% higher than card AOV because customers feel comfortable buying larger baskets when payments are spread. The single most important commercial metric for justifying Klarna's higher merchant fee.

|                                       |                                                                                                                            |
| ------------------------------------- | -------------------------------------------------------------------------------------------------------------------------- |
| **What it counts**                    | `SUM(order_amount.value) / COUNT(orders WHERE status=CAPTURED)`, in matching currency.                                     |
| **Pay in 30 vs Pay in 4 vs Slice it** | Slice it AOV is 4 to 10x other products (longer instalments justify higher value). The blended AOV depends on product mix. |
| **Currency**                          | Per-currency.                                                                                                              |
| **Refunds**                           | Excluded from count.                                                                                                       |
| **Vs card AOV**                       | Klarna AOV typically 30-45% above card AOV for same store. The "Klarna lift" justifies the higher merchant fee.            |
| **Time window**                       | `30D vsP`.                                                                                                                 |
| **Alert trigger**                     | `+/-15% movement vsP`.                                                                                                     |
| **Roles**                             | owner, finance, operations                                                                                                 |

## Calculation

Calculated automatically from your Klarna data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.

## Worked example

"Helle Mode", 30 days ending 02 May 26.

| Klarna product         | Count     | Volume EUR    | AOV         |
| ---------------------- | --------- | ------------- | ----------- |
| Pay in 30 days         | 4,820     | 612,400       | EUR 127     |
| Pay in 4               | 1,840     | 248,300       | EUR 135     |
| Slice it               | 320       | 184,200       | **EUR 575** |
| **Blended (EUR only)** | **6,980** | **1,044,900** | **EUR 150** |

Helle Mode's card AOV (Stripe) for the same period is EUR 102. **Klarna AOV is 47% higher.** That's the "Klarna lift" justifying the 3.5% merchant fee vs 2.0% card fee.

What the merchant should notice:

1. **Slice it AOV at EUR 575 dominates the blended figure.** Slice it is 4.6% of count but 17.6% of volume; including it lifts the blended AOV by 15-20%.
2. **Pay in 4 AOV (EUR 135) marginally higher than Pay in 30 (EUR 127).** Pay in 4 customers know they're spreading; basket sizes lift slightly.
3. **A 10% drop in blended AOV likely means Slice it adoption dropped.** Slice it requires a credit check; if the customer-facing UX deteriorates (a checkout-page redesign mistake), Slice it conversion drops sharply.
4. **The Klarna AOV lift is the commercial justification.** A 47% AOV lift on 35% of orders translates roughly to 16% revenue uplift attributable to Klarna integration; well above the 1.5pp incremental fee cost.

## Sibling cards merchants should reference together

| Card                                                                                        | Why pair it                                                 |
| ------------------------------------------------------------------------------------------- | ----------------------------------------------------------- |
| [`kla_total_volume`](/nerve-centre/kpi-cards/klarna-api/total-volume)                       | Numerator.                                                  |
| [`kla_total_transactions`](/nerve-centre/kpi-cards/klarna-api/total-transactions)           | Denominator.                                                |
| [`kla_top_payment_methods`](/nerve-centre/kpi-cards/klarna-api/top-payment-methods)         | Pay in 4 vs Pay in 30 vs Slice it (Slice it dominates AOV). |
| Stripe [`stripe_avg_transaction`](/nerve-centre/kpi-cards/stripe/average-transaction-value) | Card AOV; the comparison shows the Klarna lift.             |

## Reconciling against the vendor's own dashboard

**Where to look:**

[portal.klarna.com](https://portal.klarna.com) → **Reports → Sales** with average-order-value computed (volume divided by count) per period.

**Why our number may differ:**

| Reason                 | Direction | Why                                                         |
| ---------------------- | --------- | ----------------------------------------------------------- |
| **Time zone**          | Either    | CEST vs UTC.                                                |
| **Currency rendering** | Either    | Klarna Portal can render EUR-converted; we preserve native. |

**Cross-connector reconciliation:**

| Comparison                                                                                                          | Expected             | Why                                             |
| ------------------------------------------------------------------------------------------------------------------- | -------------------- | ----------------------------------------------- |
| `kla_avg_transaction` ↔ [`stripe.stripe_avg_transaction`](/nerve-centre/kpi-cards/stripe/average-transaction-value) | Klarna 30-45% higher | Klarna's BNPL psychology drives larger baskets. |

## Known limitations / merchant FAQs

**Why is Klarna AOV so much higher than card AOV?**
Two reasons: (1) BNPL psychology lets customers commit to bigger baskets when payments spread, (2) Slice it (long-instalment) deliberately targets higher-value purchases. The blended Klarna lift is typically 30-45% on the same store.

**A 10% AOV drop, what to investigate?**
First check the product mix. Slice it AOV is 4-10x other Klarna products; if Slice it conversion dropped (UX issue, credit-check friction increased), blended AOV drops sharply. Second check is Pay-in-30 vs Pay-in-4 mix; Pay-in-4 has slightly higher AOV but Pay-in-30 is the volume driver.

**Is the Klarna lift sustainable, or do customers eventually return to card AOV?**
Sustainable. Multi-year studies show the BNPL AOV lift persists; customers continue to use Klarna for larger purchases over years. The lift narrows slightly (40% in year 1, 35% in year 3) as customers become accustomed.

**Slice it median vs mean, do they differ?**
Yes substantially. Slice it has heavy right-tail (some customers finance EUR 2,500+ purchases). Median is typically half of mean for Slice it; this card is mean only.

**Klarna AOV calculation includes refunded orders?**
Yes the original capture is in numerator; refunds are tracked separately. A fully-refunded EUR 500 order still contributes EUR 500 to numerator and 1 to denominator.

**B2B Klarna orders, AOV different?**
Klarna B2B (Klarna for Business, available in some markets) targets SMBs ordering supplies; AOVs are EUR 800-3,000 typical. If the merchant has Klarna B2B enabled, those orders skew the blended figure.

***

### Tracked live in Vortex IQ Nerve Centre

*Average Transaction* is one of hundreds of KPI pulses Vortex IQ tracks across Klarna and 70+ other ecommerce connectors. Nerve Centre runs the detection layer; Vortex Mind investigates the cause when something moves; Ask Viq lets you interrogate any number in plain English.

[Start for free](https://app.vortexiq.ai/login) or [book a demo](https://www.vortexiq.ai/contact-us) to see this metric running on your own data.