> For the complete documentation index, see [llms.txt](https://partner-docs.covergenius.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://partner-docs.covergenius.com/optimizations/explorations.md). # 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:
FieldWhat it shows
Exploration nameThe name of the Exploration and the protection product being tested.
StatusWhether the Exploration is currently Running, Scheduled, or Closed.
TypeThe dimension being varied (e.g. Price).
Start dateWhen the Exploration began collecting data.
DurationHow long the Exploration has been running.
End dateThe date the Exploration was closed.
Related ExperimentsThe 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:
StatisticWhat it shows
Primary metricThe primary value being measured (e.g. GWP per order).
Secondary metricThe secondary value being measured (e.g. attach rate).
Total quotesThe cumulative number of quotes generated across all variants since the Exploration began.
DurationHow long the Exploration has been running.
VariantsThe 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.
FieldWhat it means
VariantThe 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 metricThe primary value being measured.
Secondary metricThe 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. {% hint style="info" %} **Important:** Dimension Analysis results are directional signals only. A segment-level pattern identified through Explorations is not a confirmed causal finding. Always validate with a dedicated Experiment before acting on a segment-level signal. {% endhint %} ## 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. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://partner-docs.covergenius.com/optimizations/explorations.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.