The Tech Stack Behind Real-Time Social Triggers
Real-time sports data, transactions and friend activity all feed one profile. Here's how CRM systems turn that into smarter, better-timed engagement.
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In today’s world, even Fintech products such as Revolut or Monzo see enabling social connections as a core part of what they do.
Products such as social betting apps integrate these social connections and financial data alongside sports data and high-velocity transactions. Each goal, each transaction, and each message is an opportunity to engage a customer and build retention.
In this piece, I’m going to tell you about how you should build a CRM strategy to turn this data into user retention, the tech stack you should adopt (vs build), and the mistakes you want to avoid.
Turning Real-Time Data into Customer Engagement
When the triggers you want to use to send users push notifications come in at such a high velocity that they can be described as Big Data, it’s imperative that these notifications be sent on time, when they are still relevant, and also within a reasonable volume.
This is why you probably want to avoid using tools such as Firebase Cloud Messaging (FCM), Expo, Amazon SNS or even Apple’s APNs. The issue with these technologies is that;
- They can hit limits: if you have one event (say, a goal) that triggers notifications to a large user base, some users will be throttled and receive the notification too late.
- They do not offer any frequency capping, meaning that if a user qualifies for multiple notifications within 1 hour or less, they will receive all of them.
- There is no delivery visibility. Your marketing team can’t see whether the push notifications got delivered, how many were opened, or what the resulting activity was.
In these cases, it is better to use a dedicated CRM system, such as Braze or Customer.io. These platforms offer your marketing team cross-channel frequency capping, behavioural segmentation and user targeting, journey/campaign orchestration, as well as the deliverability and analytics that you need–working outside the box.
Most importantly, these platforms free your marketing team to send users the communications they need across channels without relying on engineering changes every time you want to start sending a notification or move one from one point in the user journey to another.
Before you integrate these platforms, though, you need to get the data piece right. A lot of companies have siloed data across their databases, Google Analytics, and other analytics platforms.
They do not have a canonical source, and they don’t have a tool that can reliably aggregate their data and then forward the relevant ones to the CRM. So before setting up any other tech, you need a Customer Data Platform (CDP).
Why Social Signals Drive Retention
In a social app, leveraging customer interactions not only as an engagement lever but also for segmenting and targeting customers is important. You should apply different levels of segmentation to your customers and send more or fewer comms based on their level of interaction.
In general, it’s useful to follow the Recency, Frequency, Monetary (RFM) model.
RFM segmentation allows you to use the recency of activity, a user’s frequency of interacting with your product, and their monetary value to place users into different segments that receive varying levels of communication.
For example, if a user is a formerly high-value player who spent a lot of money in your app, but has recently not done so, then you may need to send them one type of comms–perhaps reminding them what they are missing.
As an example, at Stakemate, the stack runs on Segment as the CDP and Braze as the CRM. Our two highest-velocity sources feed straight in: live sports data from our odds providers (such as Genius Sports) and transaction data from our own database.
When something a user cares about happens (a late goal in a match they’ve bet on, an early payout, or a friend copying their bet), the event lands in Segment, gets enriched with the context we already hold (open bets, recent activity), and is forwarded to Braze. Braze then checks it against the user’s segment, frequency cap, and quiet hours before sending anything.
The payoff is holding two very different data types on the same profile. The sportsbook side — stakes, deposits, open positions — is what RFM feeds on; the social side — who’s active in group chats, whose bets get copied — is often the stronger retention lever. Fusing them means a user isn’t just “high-value, lapsing” but also “the person three friends copied last week.”
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