> 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/optimisations/explorations.md). # Explorations Explorations distribute traffic across a range of price variants to understand how pricing affects demand, revenue, and attach rate across your customer base. They are designed for pattern recognition, not decision-making. **Finding Explorations in the Partner Portal:** Log in → left-hand sidebar → Optimisations → Explorations. Select any Exploration name to open its detailed view. The sections below walk through each part of the Explorations interface in the Partner Portal. ## The Explorations list The Explorations list gives you a snapshot of all your Explorations in one place. Filter by status using the tabs at the top (All, Running, Scheduled, Closed), or use the search field to find a specific Exploration by name. | Field | What it shows | | ------------------- | -------------------------------------------------------------------- | | Exploration | 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. | ## The Exploration detailed view When you open an Exploration, the header gives you an at-a-glance summary of its current state. The title shows the protection product being explored (e.g. Travel Cancellation Protection) along with status and type badges such as Running and Price. Below the title, a subtitle line shows the scope of the Exploration: * **Region.** The geographic market in which the Exploration is running (e.g. North America). * **Range.** The spread of price variants being tested (e.g. -20% to +20%). * **Users per day.** The approximate daily traffic volume enrolled in the Exploration. The header also shows five summary statistics: | Statistic | What it shows | | ---------------- | ------------------------------------------------------------------------------------------ | | Primary metric | The primary value being measured (e.g. GWP per order). Configurable in the Partner Portal. | | Secondary metric | The secondary value being measured (e.g. attach rate). Configurable in the Partner Portal. | | 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 The Variant Allocation table shows how traffic is distributed across your variants and how each variant is performing on your key metrics. | Field | What it means | | ---------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Variant | The price variant label. The unchanged base price is labelled Base price (Control). Other variants show their adjustment relative to the base price (e.g. -20%, -10%, +10%, +20%). | | Traffic % | The share of enrolled users assigned to this variant. | | Primary metric | The primary value being measured. Configurable in the Partner Portal. | | Secondary metric | The secondary value being measured. Configurable in the Partner Portal. | Unlike Experiments, Explorations don't flag a winner. The Variant Allocation table is a tool for pattern recognition. Look across the rows for meaningful differences in the primary and secondary metrics to identify which price range is generating the best overall outcome. Traffic is typically allocated roughly equally across all variants. If you notice a significant imbalance, contact your Cover Genius Partner Growth Manager (PGM). ## Dimension Analysis The Dimension Analysis section lets you break down variant performance by user segment (e.g. country, device type, or booking value). Use this section to understand whether pricing impacts are consistent across your full user base or whether certain segments respond differently to price changes. 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. {% 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 The Traffic and Performance section contains two time-series charts that let you monitor the Exploration as it runs. * **Traffic chart.** This 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 chart.** 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 The Related Experiments section lists any Experiments derived from this Exploration. Each row shows the experiment name, status, and a link to the full experiment's detailed view. This section reflects the typical workflow: an Exploration surfaces a promising price direction, and one or more Experiments are run to validate that specific change. Use Related Experiments to track which hypotheses from the 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. 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