🔒 This feature is available to Kit customers and users with an existing Referral Program.
Detecting referral fraud and making sure your subscribers don't win rewards by cheating is one of our most important responsibilities—and something we take very seriously!
Our anti-fraud measures ensure only high-quality referrals and is the reason most big newsletters go with us—we're by far the most advanced in terms of anti-fraud for email referral programs.
SparkLoop comes with a sophisticated range of anti-fraud mechanisms to help you detect and prevent cheating in an automated, or mostly automated, way.
Anti-fraud levels
You can set your preferred level of anti-fraud detection by going to Settings > Anti-fraud.
There are 3 levels of anti-fraud security in SparkLoop: Flexible, Strong and Very Strong.
The majority of referral programs will be best served by the Flexible setting. Larger newsletters offering high-value or expensive rewards may find the Strong setting necessary. The Very Strong setting is our highest level of anti-fraud.
⚠️ We only recommend using the Very Strong setting if you have an audience that is extremely prone to cheating, or are using a reward or giveaway prize of extremely high value.
How anti-fraud works
When a new referral is tracked, our algorithm will assess the fraud level in real-time.
Noticeably fraudulent referrals will immediately be rejected and marked as rejected referral, regardless of your anti-fraud level.
When a referral is marked as "rejected," it will not count towards the advocate's reward points. SparkLoop will update the RH_ISREF custom field to "REJECTED", allowing you to segment and remove these subscribers in your ESP.
Unverified referrals
Sometimes, it's not immediately obvious if a referral is fraudulent. If that happens, our anti-fraud algorithms predict the likelihood of a referral being fraudulent based on multiple factors such as the referral's IP address, device, domain and other factors.
Based on your selected anti-fraud level, SparkLoop may mark a referral as Unverified. You can see all unverified referrals under the Subscribers page and quickly reject the ones you think are fraudulent.
Manual and semi-manual reward approval
To help you avoid giving rewards to cheating subscribers, you can set a custom reward approval level on a reward-by-reward basis:
Automated: The reward will be approved automatically when a subscriber wins it. Ideal for digital/low-monetary rewards.
Semi-manual: Requires manual approval only when a subscriber has unverified referrals. Otherwise approved automatically.
Manual: The reward always requires manual confirmation. Ideal for expensive/high-monetary-value rewards.
Blocking and whitelisting
To block an advocate who is referring fraudulent email addresses, go to their profile > Click on Actions > Select Block.
Whitelisting is the opposite — when you whitelist an advocate, SparkLoop will automatically confirm any reward they win even if they have unverified referrals.
⚠️ You will still need to manually approve any rewards that require manual confirmation.
Rejecting individual referrals
To manually reject referrals:
1. Go to the referrer's profile page and scroll down to the Referrals section.
2. Select all the referrals you want to reject by ticking the checkbox next to their email address.
3. Click on the Reject Referrals button in the top right corner.
4. In the modal window, click on Reject Referrals again to confirm.
⚠️ Please note that rejecting these referrals will NOT remove rewards that have already been won.