Explorations
Explorations are deliberately designed to observe without optimising, so that by the time you run an Experiment, you are testing a direction you already have reason to believe in.
For example, an Exploration can distribute traffic across a range of price variants (e.g. -20% to +20% of your base price) and help you explore how pricing affects demand, revenue, and attach rate.
The sections below walk through each part of the Explorations and the data you can expect to see in your Portal.
Finding Explorations in your Portal: Log in → left-hand sidebar → Optimisations → Explorations. Select any Exploration name to open its detailed view.
The Explorations list
All active and historical Explorations are available in your Portal. The Explorations list gives you a snapshot in one place. Each entry contains:
Exploration name
The name of the Exploration and the protection product being tested.
Status
Whether the Exploration is currently Running, Scheduled, or Closed.
Type
The dimension being varied (e.g. Price).
Start date
When the Exploration began collecting data.
Duration
How long the Exploration has been running.
End date
The date the Exploration was closed.
Related Experiments
The number of Experiments linked to this Exploration.
Deep-dive an Exploration
With any Exploration in your Portal, you’ll get the detailed scope of the Exploration:
Product. The Cover Genius protection product being tested, (e.g. Comprehensive Travel Protection)
Users per day. The approximate daily traffic volume enrolled in the Exploration.
Key metrics:
Primary metric
The primary value being measured (e.g. GWP per order).
Secondary metric
The secondary value being measured (e.g. attach rate).
Total quotes
The cumulative number of quotes generated across all variants since the Exploration began.
Duration
How long the Exploration has been running.
Variants
The number of price variants included in the Exploration.
Variant Allocation
We aim to split traffic equally across all variants. This is intentional — equal distribution keeps results unbiased, even if it takes a little longer to see where the opportunities are.
The Variant Allocation table in your Portal shows how traffic is distributed across your variants and how each variant is performing against your key metrics.
Variant
The variant label. The unchanged version is labelled Control. Other variants describe how they differ from it — a numeric adjustment (e.g. a price change of −20%, −10%, +10%, +20%), a different product configuration, or an alternative feature or design being tested.
Traffic %
The share of enrolled users assigned to this variant.
Primary metric
The primary value being measured.
Secondary metric
The secondary value being measured.
Unlike Experiments, Explorations don't flag a winner. Results are directional signals only. Look across the rows for meaningful patterns in the primary and secondary metrics to identify which variant is generating the best overall outcome.
Traffic is typically allocated equally across all variants. If you notice a significant imbalance, contact your Cover Genius PGM.
Dimension Analysis
Dimension Analysis breaks down Exploration results by segment — country, device type, booking value, or customer cohort.
Use Dimension Analysis to understand whether impacts are consistent across your full user base or whether certain segments respond differently to changes (e.g. pricing). A variant that performs well overall may be driven by a single high-value segment. Equally, a variant that looks neutral in aggregate may be showing strong signals in a segment that's worth targeting.
Segments can be customized. Speak to your Cover Genius PGM about the segments required for your Exploration.
Traffic and Performance
Traffic and Performance gives views of how your Exploration is progressing over time.
User sessions. Shows the volume of users assigned to each variant over time. Use this to confirm that traffic allocation has been consistent since launch and to spot anomalies. For example, a sudden drop that might indicate a configuration issue.
Performance. This shows how each variant's primary metric (e.g. GWP per order) has changed over time. A pattern that holds consistently over a longer duration is more meaningful than a short-lived spike.
Related Experiments
Any Experiments derived from an Exploration are captured. Each entry includes the experiment name, status, and a link to the full experiment detail.
This is the feedback loop in action. An Exploration surfaces a promising direction. An Experiment validates it. The confirmed result becomes the new baseline, and the next Exploration builds on that. Over time, each cycle moves you further from intuition and closer to a continuously improving product.
Use Related Experiments in your Portal to track which hypotheses from this Exploration are currently being tested.
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