> ## Documentation Index > Fetch the complete documentation index at: https://docs.fanfare.io/llms.txt > Use this file to discover all available pages before exploring further. # Consumers > Understanding consumer identity, verification, and tracking in Fanfare Fanfare tracks your **consumers** as they participate in experiences. Consumers can range from guest shoppers to fully verified account holders. ## Consumer Identity Levels As consumers engage with your experiences, they can progress through different identity levels: Consumer identity levels diagram showing guest, registered, and verified progression. ### Guest Consumers Consumers who participate without creating an account: * Quick, frictionless entry * Limited to browser session * Cannot receive notifications * May have restrictions on high-value items **Best for:** Maximizing participation, low-risk distributions ### Registered Consumers Consumers who have provided contact information (email or phone): * Can receive notifications and updates * Can be reached for marketing * Session can be recovered * Enables better fraud detection **Best for:** Most distributions, building consumer relationships ### Verified Consumers Consumers who have confirmed their identity (via email code, SMS code, or login): * Highest trust level * Full account features * Purchase history available * Required for some distributions **Best for:** High-value items, auctions, appointment booking ## Consumer Information ### Contact Details | Field | Purpose | | --------- | --------------------------------------------- | | **Email** | Notifications, order confirmations, marketing | | **Phone** | SMS notifications, verification | | **Name** | Personalization, order fulfillment | ### Consumer Scores Fanfare calculates helpful scores about your consumers: **Loyalty Score** A measure of consumer value based on purchase history and engagement: | Score Range | Meaning | | ----------- | -------------------------- | | 0-25 | New or occasional consumer | | 25-50 | Returning consumer | | 50-100 | Regular consumer | | 100-150 | Loyal consumer | | 150+ | VIP consumer | Use loyalty scores to create VIP audiences for early access or exclusive experiences. **Activity Level** Recent engagement with your experiences: * Decays over time (recent activity counts more) * Helps identify currently active consumers * Useful for re-engagement campaigns ### Purchase History Track consumer value over time: * **Total orders** — Number of purchases * **Lifetime value** — Total amount spent * **Average order** — Typical purchase amount * **Last order** — Most recent purchase date ### Location (Inferred) Approximate location based on their visits: * Country * Region/State * City * Timezone Useful for timezone-appropriate communications and regional targeting. ## Guest vs. Verified Access Different distributions may require different identity levels: | Distribution | Guest Access | Typical Requirement | | ------------- | --------------- | ------------------------------ | | Queue | Usually allowed | Low friction preferred | | Draw | Usually allowed | Maximize entries | | Auction | Rarely allowed | Need payment capability | | Appointment | Rarely allowed | Need contact for booking | | Timed Release | Usually allowed | Quick access | | Waitlist | Usually allowed | Need contact for notifications | ### When to Require Verification * High-value or limited items (prevent abuse) * Auctions (need payment method on file) * Appointments (need to contact for changes) * VIP experiences (confirm membership) ### When to Allow Guests * High-volume launches (maximize participation) * Lower-value items (fraud risk is lower) * Flash sales (speed matters) * Lead generation (convert later) ## Progressive Collection You can collect consumer information gradually: Progressive collection diagram showing guest entry, email collection, phone collection, and checkout profile collection. This approach: * Reduces friction at the start * Collects information when consumers are motivated * Builds profiles over time ## Using Consumer Data ### For Audiences Create targeted groups based on consumer attributes: * VIP consumers (loyalty score > 100) * Recent buyers (ordered in last 30 days) * High spenders (lifetime value > \$500) * Local consumers (specific regions) [Learn more about Audiences →](/concepts/audiences) ### For Personalization Use consumer data to personalize experiences: * Show relevant products based on history * Adjust messaging based on loyalty level * Target communications by timezone ### For Fraud Prevention Consumer data helps identify suspicious activity: * Bot detection based on behavior patterns * Order limits for new vs. established consumers * Velocity checks for unusual activity ## Consumer Privacy Fanfare helps you manage consumer data responsibly: * **Consent tracking** — Record marketing opt-ins * **SMS opt-out** — Respect unsubscribe requests * **Data export** — Provide consumer data on request * **Archiving** — Remove inactive consumers ## Best Practices ### Match Friction to Value * Low-value, high-volume → Allow guests * High-value, limited → Require verification ### Collect Progressively Don't ask for everything upfront. Collect information as consumers progress through the experience. ### Use Scores Wisely * Loyalty scores help identify your best consumers * Don't over-gate experiences—frustrates consumers * Test different thresholds ### Respect Preferences * Honor opt-out requests promptly * Don't over-message * Make preferences easy to manage ## Next Steps * [Audiences](/concepts/audiences) — Group consumers for targeting * [Experiences](/concepts/experiences) — How consumers participate * [Distribution Types](/concepts/distributions/overview) — Access methods and requirements