Personalization

Deliver the most relevant user experiences based on real-time user activity

Real-Time Personalization

Customizing user experiences is a surefire way to grow customer engagement and revenue. Many online businesses employ some level of personalization today, but using minutes- and seconds-old data for real-time personalization has always been elusive.

With Rockset, you have the ability to analyze real-time user activity to derive user intent. So you can offer your users what is most likely to interest them—right now.

Personalization Use Cases

  • Use Case Card Icon

    Retail

    Bring real-time behavioral data together with other data on purchase history, demographics and inventory. Increase conversion, cross-sell and upsell with personalized product recommendations and offers.
  • Use Case Card Icon

    Media

    Track what content your audience is watching, clicking on, fast-forwarding through or skipping. Grow user engagement with personalized content recommendations based on real-time user activity.
  • Use Case Card Icon

    Adtech

    Combine real-time intent signals and precise location information with customer profile data. Improve conversion by serving highly personalized ad experiences.

Why Personalization Is Hard

How Rockset Makes It Easy

Other
Don't know what users did in the last 5 minutes: Behavioral data is messy and complex, and often needs to be transformed before it is queryable. If your data is going through a data pipeline, your personalization engine won't be operating on the latest data.
Check
Analyze user activity as it happens: Rockset ingests data continuously and makes it immediately queryable without any data prep. Personalize your users' experiences based on user activity and intent from seconds ago.
Other
Need to join data from multiple sources: Personalization requires behavioral, transactional, customer profile, location and other data. But you can't combine these disparate data sets without extensive application logic.
Check
Join data across multiple sources: Join data from different collections and data sources effortlessly. Improve your personalization by including new data as needed, without requiring denormalization or application-side joins.
Other
Can't scale to handle user growth: You have a small window in which to capture your users' interest. But your queries bog down and you can't deliver customized experiences in time as the number of users grows.
Check
Fast queries at scale: Rockset is optimized to serve low-latency queries at high concurrency. Reach your users in time, with customized experiences, even as their number grows.

Why Personalization Is Hard

Other
Don't know what users did in the last 5 minutes: Behavioral data is messy and complex, and often needs to be transformed before it is queryable. If your data is going through a data pipeline, your personalization engine won't be operating on the latest data.
Other
Need to join data from multiple sources: Personalization requires behavioral, transactional, customer profile, location and other data. But you can't combine these disparate data sets without extensive application logic.
Other
Can't scale to handle user growth: You have a small window in which to capture your users' interest. But your queries bog down and you can't deliver customized experiences in time as the number of users grows.

How Rockset Makes It Easy

Check
Analyze user activity as it happens: Rockset ingests data continuously and makes it immediately queryable without any data prep. Personalize your users' experiences based on user activity and intent from seconds ago.
Check
Join data across multiple sources: Join data from different collections and data sources effortlessly. Improve your personalization by including new data as needed, without requiring denormalization or application-side joins.
Check
Fast queries at scale: Rockset is optimized to serve low-latency queries at high concurrency. Reach your users in time, with customized experiences, even as their number grows.
Core Features for Personalization
  • Schemaless Ingestion

    Ingest semi-structured, nested data without requiring a fixed schema. Rockset automatically infers the schema, so you can run queries without performing any transformation.
  • Built-In Data Connectors

    Set up continuous ingestion from common data sources, like MongoDB, DynamoDB, Kafka and S3, in a plug-and play manner. New data is reflected in Rockset in seconds.
  • SQL with JOINs

    Join multiple data sets for analysis. Rockset supports full-featured SQL, enabling complex search, aggregation and join queries.
  • Converged Indexing™

    Rockset automatically builds search, columnar and row indexes on your data to deliver fast queries at scale.

Resources



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