How Intempt works

Core mechanics of our platform

Intempt allows you to gather data from multiple data sources and apply an advanced profile merging logic to unify customer profiles.

With unified customer data, you can use multiple GrowhOS tools under a single data model:

  1. Discover 🎯
    ‍Identify, build, and analyze audiences. Unify customer data across all digital and offline touchpoints and use it to identify your target leads & accounts.
  2. Personalize ✨
    Personalize every interaction to deliver an optimal customer experience at scale across web, mobile and email.
  3. Engage 💬
    Set timely, automated triggering events based on real-time behavior to send timely emails and SMS when customers are most likely to engage, like in the event of lifecycle stage change, a lack of activity shown in the past week, and more.
  4. Predict 🔮
    Predict user intent in real time with machine learning. Understand your customers better than ever before with a neural network algorithm that identifies future-purchase intent.
  5. Optimize 🛠️
    Experiment anywhere on your digital properties with great agility, more confidence, and less risk

Infrastructure

Intempt is powered by the Clickhouse database, which is built for ingesting, storing, and querying trillions of events in real-time.

Event-centric

Intempt is built for ingesting, storing, and triggering events. Each event has a name, a timestamp, a unique identifier, a masterID that identifies the entity that performed the event, and a JSON of properties. Events map cleanly to real-world actions. When something happens at a point in time to a user, you can track it with all the context you know about that event.

Real-time

Analytics. Events are available for analysis in Intempt within seconds of hitting our ingestion servers. Clickhouse leverages an architecture to collect recent events in a row-oriented format while storing historical events in a time-partitioned columnar format. This enables fast, real-time analysis and efficient historical analysis.

Engagement. We use Flink pipelines to trigger real-time engagement sequences for our Journeys product - so each message gets to the customer at the precise time it was planned.

Personalization. We use advanced CDN techniques to apply real-time segmentation and serve personalized experiences in any part of the world under 500ms.

Data ingestion layer

You can collect data by implementing Intempt’s tracking libraries as your sources:

SDKs

  • Our Javascript SDK is the most powerful way to track customer data from a website. We recommend it as the default installation for any website.
  • iOS SDK is the best way to simplify tracking in your iOS apps. We recommend them over server-side sources as the default installation for any mobile app.
  • Node.js SDK lets you send analytics data directly from your servers when client-side tracking doesn’t work or when you’re sending mission-critical data like revenues.
  • Use the REST API if we don’t offer a library for your specific environment yet.

Cloud App Sources

We also offer cloud app sources to integrate data from your third-party tools:

  • Our cloud sources can import third-party tool data directly into your Intempt project based on the data recorded in the app like Shopify and HubSpot

How you can track data

Intempt supports several ways to implement tracking. The two most common are to use client-based or server-based libraries. You can use Intempt’s client-based libraries, such as Javascript SDK and iOS SDK, to make calls on users’ browsers or mobile devices. You can also track data with Intempt’s server-based libraries, such as Node.js SDK or REST API, where the calls are triggered on your own servers and then sent to the Intempt servers.

Although there are some tradeoffs between the two approaches, neither is better than the other, and we recommend that you implement a mix of both. In general, more direct interaction data is available using a client-based library, but the server-based collection is more secure, reliable, and can’t be blocked by ad blockers.