The navigation dataset operates with two main tables: pageviews and sessions. A pageview refers to each new page that a user accesses while browsing a store, while a session is the set of all pageviews made by a user in a single visit. Each session remains active until no new pageviews occur for a period of 30 minutes.

The navigation dataset does not capture all types of events that occur during browsing. For example, specific clicks, special events, and interactions with the mini cart are not recorded.

This section includes the following information:

• Characteristics of navigation data
• Table: sessions
• Table: pageviews
• Analyses with navigation data
• Correlations with other data

Data Pipeline only provides data from sessions originating from VTEX storefront solutions: Legacy CMS, Store Framework, and FastStore. VTEX does not have access to sessions originating from third-party marketplaces or proprietary storefronts. Furthermore, storefront customizations may interfere with or even disable the script, resulting in some sessions not being recorded, or in discrepancies in the conversion rate observed in the dashboard. To minimize the impact on store performance, the script is configured to be the last element to load on the page. This means that very brief sessions may not be captured.

This table only contains closed sessions, whether due to inactivity or because a purchase was completed. It's sorted by session_id, session_end_time, and store_name. Avoid filtering large data ranges by columns that are not part of this sorting strategy. The table fields are described below:

Each item in this table corresponds to a page viewed by the buyer, such as homepage, product page, and checkout stage.
A page view is counted after the buyer's browser loads the page. Each page has specific attributes, however, because this table brings everything together in a single schema, many null values will appear. For example, product page attributes are expected to be null when the page view corresponds to a shopping cart stage. The table fields are described below:

Navigation data can be used for the following analyses:

• Overall conversion rate: Calculate the proportion of sessions that resulted in a purchase in relation to the total number of sessions to assess the overall effectiveness of the website in converting visitors into buyers.
• Conversion funnel analysis: Group pageviews by funnel stages (home, search, product, cart, checkout) and count how many sessions have passed through each stage, identifying where users give up.
• Most visited pages: Count the number of pageviews for each type of page (home, category, product) to identify the pages that attract the most attention and optimize them for conversion.
• User path tracking: Follow the sequence of the pageviews for each session to understand the path taken by the user and discover common navigation patterns.
• Traffic source: Analyze the reference URL of each session to determine the traffic source and get insight about which marketing channels are most effective.
• Bounce rate by page type: Identify sessions that end after a single page view and calculate the bounce rate by page type to improve the content or design of these pages.

VTEX navigation data has significant interactions with other datasets that enrich user behavior analysis, for example:

• Interaction with order data: Comparative analysis between navigation and order conversions reveals the impact of user journeys on purchase decisions.
• Relationship with SKUs: User interaction with product and category pages offers insights into the popularity and effectiveness of product presentation.
• Marketing data and campaigns: The correlation between navigation and marketing campaigns helps evaluate how efficient campaigns are in attracting traffic and generating conversions.

• Inventory
• Payments
• Orders
• Prices
• Promotions
• Gift cards
• Bridge logs