Introduction
This document provides an overview of how Dressipi cookies and tracking operate, outlining both policy rules and technical behavior.
1 Cookie Setting Mechanism
All cookies are set server-side using the Set-Cookie header.
Cookies are marked Secure and HttpOnly by default.
2 Cookie Overview
Cookie Name | When it’s set | Domain | Duration | Secure | HttpOnly | Description |
|---|---|---|---|---|---|---|
| All visitors | Full domain | 1 year | Yes | Yes (server-only variant) / No (client-readable variant) | Core identifier cookie used by Dressipi to maintain a consistent user identity across browsing sessions. The server-only variant (HttpOnly, SameSite=Lax) ensures secure, server-level identity management, while the client-readable variant (SameSite=None) enables integration with client-side tracking and personalization. |
| All visitors | Full domain | 2 years | Yes | No | Stores a client-side identifier for site visitors across multiple visits. This helps maintain personalization continuity when server-side mapping is not yet established. It is set with SameSite=Lax. |
| All visitors | Full domain | — | Yes | Yes | Records the pages visited and the activity of site visitors. This cookie securely links visitor activity to their browsing session and is used by Dressipi to generate personalized recommendations and outfits. It acts as both a tracking mechanism and a secure session token for Dressipi systems. |
| All visitors | Full domain | Session | Yes | Yes | Session management cookie that maintains a visitor’s active session while they browse the retailer’s site. It is automatically cleared when the visitor’s browsing session ends. |
| All visitors | Full domain | 2 years | Yes | Yes | Stores a persistent token to recognize returning visitors across multiple sessions, enabling smoother login experiences and continuity of personalization. |
| Only for retailers who have integrated the Personal Style Quiz | Full domain | — | Yes | Yes | Stores the visitor’s status within the Personal Style Quiz flow, allowing them to resume progress on subsequent visits. This cookie is only set when the quiz feature is enabled. |
| Only for retailers who have integrated the Personal Style Quiz | Full domain | — | Yes | Yes | This record keeps track of the last login time of visitors participating in the Personal Style Quiz. This allows quiz interactions to be personalized based on recent activity. |
| All visitors (when opt-out is enabled) | Full domain | — | Yes | Yes | Stores a visitor’s “do not track” preference. When set, this cookie ensures that Dressipi does not track or personalize that visitor's activity. |
| All visitors (attempted but not stored) | Tracking subdomain | — | No | No | Attempted by Snowplow to store a unique visitor identifier. This is rejected by browsers due to a domain mismatch, meaning the cookie is never actually set. |
| All visitors (attempted but not stored) | Tracking subdomain | — | No | No | Attempted by Snowplow to store a session identifier. This is rejected by browsers due to a domain mismatch, meaning the cookie is never actually set. |
3 Cookie & Identity Management
3.1. Third-Party Cookies
Mapp Fashion does not set or read any third-party cookies.
3.2. Cookie Lifetime
Mapp Fashion uses HTTPS exclusively, ensuring that all cookies are transmitted securely. The primary tracking cookie is configured with a lifespan of up to one year.
3.3. CNAME Cloaked Cookies
Mapp Fashion uses A-records, which are not affected by the CNAME-related changes introduced in iOS 14 and macOS Big Sur.
3.4. Identity Management
Mapp Fashion uses cookies set by tracking requests to maintain a persistent user identity across sessions. These identifiers are random values rather than personal data; however, they still allow users to be recognized when they return to the site. A user becomes personally identifiable only when they complete a purchase with order-confirmation tracking in place, or when they are explicitly identified via the identify call in Dressipi.js.
Please consult with your legal department to determine whether this behavior requires user consent in your market(s).
3.5. Relationship with Retailer User Identity
Initially, there is no direct connection between retailer user identities and Mapp Fashion user identities. This relationship is established once order confirmation tracking is in place. Because each order confirmation is tied both to the Mapp Fashion cookie and to the transaction data (via the order ID), it becomes possible to map Mapp Fashion identities to retailer identities.
In practice, a single retailer user may correspond to multiple Mapp Fashion users, for example, the same person browsing on both mobile and desktop. In such cases, activity data from all associated users is combined to deliver more accurate recommendations.
If transaction data also includes the purchaser’s email address (or a SHA256 hash of the email), Mapp Fashion can strengthen this mapping by linking user identities based on the email information.
3.6. Applicability to Mapp Fashion Components
Mapp Fashion components all use the same identity framework. Widgets identify users through the same cookies set by tracking, and client-side APIs rely on these same cookies to identify users. On the server side, the tracking JavaScript sets a cookie that contains an access token. This token corresponds to the current Mapp Fashion user and can be read by the retailer’s servers.
3.7. Impact on Recommendations
The type and quality of recommendations depend on the data available:
No Mapp Fashion identity: You will receive AI-optimized recommendations that are based on global trends.
Mapp Fashion identity with product views: Recommendations are tailored to the specific products viewed and their associated attributes.
Mapp Fashion identity with purchase data: Recommendations are refined further by taking into account purchased products and their attributes.
Completed personal profile: Profile preferences also influence recommendations, adding another layer of personalization.
Personalization begins within seconds of the customer’s first product view, ensuring that recommendations adapt quickly to user behavior.