Sift + Salesforce
Connect Sift and Salesforce to Turn Fraud Signals into Smarter Sales Decisions
Automatically sync Sift fraud scores, risk assessments, and user decisions into Salesforce so your teams have real-time trust data when they need it.
Why integrate Sift and Salesforce?
Sift is a fraud and risk platform that uses machine learning to score user trust in real time. Salesforce is the CRM most teams already use to manage customers, opportunities, and revenue pipelines. When the two run separately, sales, support, and risk teams end up working with incomplete information — chasing revenue without knowing which accounts carry fraud risk, or flagging legitimate customers who shouldn't be flagged. Integrating Sift with Salesforce gives every team a unified, risk-aware view of each account.
Automate & integrate Sift & Salesforce
Use case
Enrich Salesforce Lead Records with Sift Trust Scores
When a new lead is created in Salesforce — from a web form, marketing campaign, or manual entry — tray.ai can instantly query Sift for a trust score and risk signals based on email, IP, or device fingerprint. The score and risk level are written back to custom fields on the Salesforce Lead record, giving sales development reps immediate context before they make first contact. High-risk leads can be automatically routed to a review queue rather than an outbound sequence.
Use case
Sync Sift Fraud Decisions Back to Salesforce Accounts
When Sift issues a fraud decision — blocking, watching, or clearing a user — tray.ai can push that decision in real time to the corresponding Salesforce Account or Contact record. Custom fields, tags, or account statuses update automatically to reflect the latest Sift ruling. Sales, support, and finance teams always have the current fraud disposition without logging into Sift separately.
Use case
Create Salesforce Cases Automatically for High-Risk Sift Events
When Sift detects a high-risk event — an account takeover attempt, suspicious login, or payment abuse signal — tray.ai can automatically create a Salesforce Case and assign it to the appropriate fraud analyst or support team. The Case is pre-populated with Sift event details, risk scores, and relevant user context so teams can triage immediately, no manual data entry required. Fraud incidents can be tracked, escalated, and resolved entirely within existing Salesforce workflows.
Use case
Automate Salesforce Opportunity Risk Flagging Based on Sift Scores
For B2B or marketplace businesses where Opportunities are tied to accounts under fraud evaluation, tray.ai can monitor Sift risk scores and automatically flag or tag Salesforce Opportunities when an associated account crosses a risk threshold. Sales managers get alerts, and the Opportunity stage can be held or modified pending a fraud review. This stops revenue from being booked on deals that carry real chargeback or abuse risk.
Use case
Update Sift User Labels Based on Salesforce Customer Lifecycle Events
When a Salesforce contact hits a defined lifecycle milestone — becoming a paying customer, being flagged for non-payment, or having their account closed for a policy violation — tray.ai can send the corresponding label update to Sift. This two-way sync keeps Sift's machine learning models trained on accurate, current ground truth signals from your CRM, which improves the precision of future fraud predictions.
Use case
Generate Salesforce Reports and Dashboards for Fraud-Impacted Revenue
By continuously syncing Sift risk scores, fraud decision counts, and chargeback-related signals into Salesforce custom objects or fields, tray.ai lets finance and revenue operations teams build native Salesforce reports that quantify fraud exposure across segments, regions, or product lines. Leaders can see what percentage of pipeline or closed revenue carries elevated risk and make informed decisions about market strategies and risk appetite.
Use case
Trigger Salesforce Workflows When Sift Scores Change Significantly
Risk profiles change. A customer who scored as low-risk at signup may look very different weeks later based on behavioral changes Sift picks up in real time. With tray.ai, significant Sift score changes can trigger Salesforce workflow actions: updating account health scores, sending internal alerts to account owners, or placing pending renewals on hold. Salesforce stays current with each customer's actual risk profile.
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Sift & Salesforce Challenges
What challenges are there when working with Sift & Salesforce and how will using Tray.ai help?
Challenge
Matching Sift Users to Salesforce Records Reliably
Sift tracks users by a user_id or device fingerprint that may not correspond directly to the email addresses, Account IDs, or Contact IDs used in Salesforce. Without a reliable cross-reference, automated lookups can fail to match records or create duplicates, leaving data enrichment incomplete.
How Tray.ai Can Help:
tray.ai's data transformation tools let teams build flexible matching logic with multiple fallback identifiers — email, external ID, phone, or a custom Sift User ID field stored on the Salesforce record. Conditional branching handles cases where no match is found, routing unmatched records to a review list rather than failing silently.
Challenge
Handling Real-Time Sift Webhook Volume at Scale
Sift can fire a high volume of real-time decision and score-change webhooks, especially for businesses with large user bases. Processing each webhook synchronously with a Salesforce API call for every event can exhaust Salesforce API rate limits and create processing backlogs fast.
How Tray.ai Can Help:
tray.ai handles webhook ingestion asynchronously and supports configurable rate limiting and batching logic. Incoming Sift events can be queued, deduplicated, and batched into efficient Salesforce bulk API calls so high-volume fraud signals are processed reliably without hitting Salesforce's API governor limits.
Challenge
Keeping Sift Decision Labels Consistent with Salesforce Terminology
Sift has its own decision taxonomy — labels like 'block', 'watch', 'accept', 'good_user', 'bad_user' — that don't map natively to Salesforce field values, picklist options, or account statuses. Manual mapping is error-prone and hard to maintain as either platform changes.
How Tray.ai Can Help:
tray.ai's data mapping and transformation tools let teams define and maintain a centralized lookup table that translates Sift decision values into the exact Salesforce picklist values, custom field entries, or tag names their organization uses. Updates to the mapping require no code changes and can be managed through tray.ai's visual workflow editor.
Challenge
Ensuring Bidirectional Data Integrity Without Infinite Loops
A two-way integration between Sift and Salesforce — where Salesforce updates trigger Sift label changes, and Sift decisions trigger Salesforce field updates — can create circular automation loops where each system's changes keep triggering responses in the other.
How Tray.ai Can Help:
tray.ai supports conditional logic and state tracking that prevents circular triggers. Workflows can check whether a field update came from an automated sync versus a human-initiated change, and skip downstream triggers accordingly. Source-of-truth flags or timestamped audit fields can differentiate automated writes from manual edits.
Challenge
Maintaining Compliance and Audit Trails for Fraud-Related Data
Fraud decisions, risk scores, and user labels are sensitive data points subject to regulatory scrutiny in many industries. Logging all Sift-to-Salesforce data flows in a way that's auditable and compliant with GDPR, CCPA, and internal governance policies is a real operational challenge.
How Tray.ai Can Help:
tray.ai provides detailed workflow execution logs that record every data transformation, API call, and decision made during each workflow run. Teams can configure data masking for sensitive fields in transit, set data retention policies on logs, and use tray.ai's audit trail to demonstrate compliance with both internal governance policies and external regulatory requirements.
Start using our pre-built Sift & Salesforce templates today
Start from scratch or use one of our pre-built Sift & Salesforce templates to quickly solve your most common use cases.
Sift & Salesforce Templates
Find pre-built Sift & Salesforce solutions for common use cases
Template
New Salesforce Lead → Sift Score Lookup → Enrich Lead Record
When a new Lead is created in Salesforce, this template queries Sift for the user's trust score using the lead's email address. The returned score, risk level, and relevant signals are written back to custom fields on the Salesforce Lead record. Leads exceeding a configurable risk threshold are automatically moved to a review queue or tagged for manual inspection.
Steps:
- Trigger on new Lead creation event in Salesforce via webhook or polling
- Extract lead email address and pass it to Sift's Users API to retrieve trust score and risk signals
- Map Sift score, risk level, and decision label to custom Salesforce Lead fields via PATCH request
- Evaluate score against risk threshold and conditionally update Lead Status or owner assignment
Connectors Used: Salesforce, Sift
Template
Sift Fraud Decision Webhook → Update Salesforce Account Status
This template listens for real-time fraud decision webhooks from Sift and maps each decision — block, watch, or accept — to the corresponding Salesforce Account or Contact record. A custom field is updated with the latest Sift decision, and an internal Chatter notification is posted to alert the account owner of any elevated-risk determinations.
Steps:
- Receive incoming Sift decision webhook and validate payload authenticity
- Parse user ID, decision type, and timestamp from the Sift webhook payload
- Query Salesforce to identify the matching Account or Contact record by email or external ID
- Update the Sift Decision Status custom field and post a Chatter notification to the account owner
Connectors Used: Sift, Salesforce
Template
Sift High-Risk Event → Create Salesforce Case for Fraud Review
When Sift generates a high-risk event alert — a suspicious login, account takeover indicator, or payment abuse signal — this template automatically creates a new Salesforce Case pre-populated with Sift event details, risk scores, and user context. The Case is assigned to the designated fraud review queue for immediate triage.
Steps:
- Receive Sift high-risk event via webhook and parse event type, user ID, and risk score
- Perform a Salesforce lookup to retrieve the associated Account and Contact records
- Create a new Salesforce Case with Subject, Description, and custom Sift fields pre-populated
- Assign Case to the fraud review queue and set Priority based on Sift risk score severity
Connectors Used: Sift, Salesforce
Template
Salesforce Account Lifecycle Event → Send Label Update to Sift
When a Salesforce Account reaches a defined lifecycle milestone — Closed Won, Closed Lost, or Suspended — this template sends a corresponding user label to Sift. Labels like 'good_user' or 'bad_user' are applied via Sift's Labels API, giving Sift's machine learning models ground truth data from the CRM.
Steps:
- Trigger on Salesforce Account status field change using a workflow outbound message or polling
- Map the Salesforce lifecycle status to the appropriate Sift label value using a lookup table
- Retrieve the Sift user ID associated with the Salesforce Account via a custom field or email match
- Call Sift's Labels API to apply the mapped label to the corresponding user profile
Connectors Used: Salesforce, Sift
Template
Daily Sift Score Sync → Refresh Salesforce Account Risk Fields
On a scheduled daily basis, this template queries Sift for updated trust scores across a defined segment of Salesforce Accounts and refreshes the corresponding custom risk fields in bulk. Accounts whose scores have changed materially trigger a Salesforce task to alert account owners for proactive review.
Steps:
- Run on a scheduled trigger (daily) and query Salesforce for all active Accounts with a Sift User ID
- Batch-query Sift's Users API for current trust scores for each Account in the result set
- Compare returned scores to previously stored values in Salesforce custom fields
- Update fields where scores have changed and create Salesforce Tasks for material risk score shifts
Connectors Used: Sift, Salesforce
Template
Sift Score Threshold Alert → Salesforce Opportunity Risk Flag
This template monitors Sift for risk score changes and automatically flags open Salesforce Opportunities associated with the affected Account when scores breach a defined threshold. The Opportunity record is updated with a risk indicator and the assigned sales rep receives an automated task to conduct a risk review before advancing the deal.
Steps:
- Receive Sift score update event and evaluate whether the score crosses the configured risk threshold
- Query Salesforce for open Opportunities linked to the Account matching the Sift user ID
- Update the Risk Flag custom field on each matching Opportunity record to 'Elevated'
- Create a Salesforce Task assigned to the Opportunity owner with a due date and risk context summary
Connectors Used: Sift, Salesforce