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How do I calculate Looksy ROI?

Compare the measured financial benefit during a test period with the Looksy cost for the same period:
Use your own store data. Looksy does not guarantee a conversion lift, return-rate reduction, or ROI percentage.

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What should count as measured benefit?

Include only changes you can support with store data:
  • contribution margin from incremental orders;
  • avoided return-processing and shipping costs;
  • any other documented savings attributable to the test.
Do not count all revenue as profit. Use contribution margin after product, fulfilment, payment, and other variable costs.

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What should count as cost?

Include the Looksy subscription and any additional-credit charges shown for the period. Current monthly prices are:
  • Starter: $14.99
  • Growth: $29
  • Scale: $79
Confirm current pricing in Looksy before calculating.

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A practical measurement process

  1. Choose a consistent product group and test period.
  2. Record sessions, orders, conversion rate, return rate, contribution margin, and Looksy cost.
  3. Compare like-for-like periods or run an A/B test where possible.
  4. Separate correlation from causation and note promotions, stock changes, seasonality, and traffic-mix changes.
  5. Calculate a range using conservative, expected, and optimistic assumptions.
A worked example is only a model. It is not evidence that another store will achieve the same result.

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How long should I measure?

Wait until the sample is large enough to make the comparison useful. Return-rate analysis also needs enough time for the applicable return window to close. Avoid drawing conclusions from a small number of shoppers or orders.

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What should I report?

Document:
  • the test dates and product group;
  • traffic and order counts;
  • conversion and return-rate calculations;
  • contribution-margin assumptions;
  • Looksy subscription and usage costs;
  • factors that may have affected the result;
  • confidence level and next action.

Conversion Tracking

Define events and attribution before evaluating impact.

A/B Testing

Compare a test group with a suitable control.