Enterprise ecommerce growth is no longer driven by instinct. It is driven by intelligence.

As acquisition costs rise and operational complexity increases, brands need more than surface-level metrics. They need actionable insight that connects customer behaviour to commercial performance.

The Mirra Analytics Dashboard is designed to do exactly that.

By translating Try Before You Buy behaviour into structured data, Mirra enables brands to unlock sustainable growth and more predictable results.

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Compare AOV by Order Type
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Not all orders carry the same value.

One of the most powerful insights within the Mirra dashboard is the ability to compare Average Order Value (AOV) between TBYB and standard Buy Now orders.

For enterprise brands, this segmentation matters.

Understanding the value difference between trial-based and traditional transactions helps quantify incremental revenue uplift. It also supports more informed media investment decisions. When you can demonstrate higher AOV from Try at Home customers, marketing allocation becomes more strategic.

This is not anecdotal growth. It is measurable performance differentiation.

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Track Trial-to-Purchase Conversion
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Conversion does not end at checkout.

The trial-to-purchase conversion metric reveals which products are ultimately kept versus returned. This provides a more nuanced understanding of product performance beyond initial sell-through.

At enterprise scale, this insight supports:

• Range optimisation
• Size curve adjustments
• Merchandising strategy refinement
• Product development feedback loops

Instead of relying solely on return rate percentages, brands can see behavioural patterns across categories, price points and customer segments.

Faster learning cycles lead to stronger inventory decisions.

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Understand First-Time Buyer Behaviour
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First-time customers behave differently to repeat buyers.

Mirra data allows brands to isolate and analyse first-time buyer patterns, including AOV, keep rates and product selection behaviour.

For acquisition-focused teams, this insight is critical.

Pinpointing what drives first-time conversion enables more targeted messaging, smarter product positioning and improved onboarding experiences. It also highlights which categories lower the barrier to entry and which require more support.

At enterprise level, reducing first-purchase friction improves lifetime value and lowers customer acquisition payback periods.

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Uncover Key Return Reasons
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Returns data is often reactive. Mirra makes it proactive.

Through structured feedback within the trial flow, brands gain clear visibility into why items are returned. Whether driven by fit, quality perception or expectation mismatch, this qualitative data becomes operational intelligence.

This supports:

• Fit refinement
• PDP content improvements
• Sizing guide optimisation
• Supply chain quality control

Reducing friction upstream protects margin downstream.

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Reveal Upsell and Bundling Patterns
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Try at Home generates rich behavioural insight into what customers add together in a single trial.

The dashboard surfaces upsell and bundling patterns, showing which items are frequently selected alongside others. This enables smarter bundling strategies and cross-category promotion based on real behaviour rather than assumptions.

For merchandising and trading teams, this insight drives incremental revenue without relying on blanket discounting.

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Smarter Decisions. Stronger Results.
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Mirra is not only a customer experience solution. It is a commercial intelligence layer.

By connecting trial behaviour to revenue performance, the Mirra Analytics Dashboard gives enterprise brands greater control, faster feedback loops and more efficient inventory economics.

Data-driven decisions improve conversion.
Conversion improves margin.
Margin drives sustainable growth.

When brands leverage Mirra analytics effectively, they do not just convert smarter.

They operate smarter.

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