Reward Sciences
Loyalty & ReferralTrack customer activity for loyalty and rewards with the Reward Sciences API, recording the actions that earn credit. Agents log qualifying events from the systems where they actually happen.
What This Integration Enables
Reward Sciences is not a campaign builder and has no storefront your customers log into. It is a headless activity sink with an identity graph behind it, and that is the whole point. You define the rules for what earns credit inside Reward Sciences. This connector is how the events that satisfy those rules actually arrive, from the systems that observed them.
Four actions cover the entire surface, which tells you something honest about the product. An agent records an activity for a customer with a free-form activity type you define, such as bought-coffee or attended-event, and the customer is created automatically if the programme has not seen them. It resolves your own system's identifier into the internal user ID, enrols someone before any activity exists for them, and attaches an additional identity so the same human being is recognised across email, your CRM and a social login. Small surface, one hard problem: making sure the person earning the credit is the right person.
Without FlowRunner
With FlowRunner
Use Case Scenarios
Purchases posted from billing, not from a file
A payment succeeds in Stripe. The agent takes the payer email, calls Get User By Identity to resolve it into a Reward Sciences user, and calls Track Activity with a bought-product activity type and the order value. If the person is not yet in the programme, Track Activity enrols them as part of the same call, so a first-time buyer starts earning on their first purchase instead of after someone notices them. The customer's balance reflects the purchase within seconds of the card clearing.
Enrolment ahead of the first activity
Someone completes a signup form in Typeform that is not itself a rewardable action. The agent calls Create User By Identity to enrol them under their email, which returns the new user ID. That ID goes back into the CRM record, so every downstream flow can reference the rewards profile directly without a lookup. The person exists in the programme before they do anything, which makes the first real activity clean.
Non-transactional activity from wherever it happens
Reward Sciences accepts any activity type you define, which means the earning surface is not limited to purchases. An agent watching an events platform records attended-event when a badge is scanned. An agent watching a community forum records answered-question. An agent watching a support queue records completed-onboarding-call. Each one is a Track Activity call from the system that saw it happen, and the rules engine decides what each is worth. No nightly export, no reconciliation job.
Human-in-Loop Highlight
The consequential call in this connector is not recording an activity. It is Add User Identity. Attaching an identity to an existing user tells Reward Sciences that two identifiers belong to the same human being, and from that moment their activity histories and earned balances are one profile. There is no unmerge action in this connector. If the agent is wrong, one customer has inherited another customer's rewards and the only fix is manual work inside Reward Sciences. So the agent treats a fuzzy match as a stopping condition. When a CRM contact and a social login share a surname and a company domain but not an email address, it does not guess. It calls Get User By Identity on both, assembles what each profile has done, and asks the programme owner directly: "CRM contact 88213 and the Google login for [email protected] look like the same person. Profile A has 14 recorded activities since March, profile B has 2. Merging is not reversible here. Same person, or leave them separate?" The person answers, the agent acts. This is what a human-in-the-loop step is for: a small number of irreversible decisions, handed to someone who can actually make them, while the thousands of clean activity records flow through untouched. FlowRunner's connectors are built and verified against each vendor's official API, so the agent knows exactly which calls carry that weight and which do not.
Agent Capabilities
4 actionsActivity
1- Track Activity Records an activity for a customer so the loyalty rules can award points or rewards for it. The customer is identified by an identity provider name and their identity within it, and the activity type is a free-form slug you define, such as `bought-coffee` or `attended-event`. Creates the customer automatically if they are not yet known, which makes it safe to fire on a first-time buyer.
Identity
3- Get User By Identity Looks up the Reward Sciences user ID for a customer from an identity provider and their identity within it, such as their email address. Used to resolve your own system's identifier into the internal user ID before recording anything further.
- Create User By Identity Creates a Reward Sciences user for a given identity provider and identity, returning the new user ID. Used to enrol someone into the programme before any activity has been recorded for them, so the profile exists when the first real event arrives.
- Add User Identity Attaches an additional identity to an existing user so the same person is recognised across several systems, such as email, your CRM and a social login. Used to merge identities onto one rewards profile, and the one call in this connector that belongs behind a human decision when the match is not certain.
Frequently Asked Questions
What can FlowRunner do with Reward Sciences?
FlowRunner agents can run Track Activity, Get User By Identity, and Create User By Identity in Reward Sciences, plus 1 more action.
Does connecting Reward Sciences to FlowRunner require OAuth?
No. Reward Sciences connects to FlowRunner with an API key, no OAuth flow required.
Can Reward Sciences trigger a FlowRunner workflow automatically?
Reward Sciences doesn't currently expose triggers in FlowRunner. It connects as an action step inside workflows started by another trigger.
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