Customer 360

Create meaningful customer engagement with a complete, real-time view of your customers

Real-Time Customer 360

Understanding how customers interact with your organization across every channel is essential to delivering the best customer experience. What makes this hard is the difficulty in accessing and analyzing the most up-to-date customer data. Using Rockset, you can analyze all relevant customer data quickly and simply in a real-time customer 360, so you can respond to customer events as they happen.

Customer 360 Use Cases

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    Retail

    Generate unified customer profiles in real time from in-store, web, app and social media data. Deliver a consistent, compelling customer experience across all channels to drive marketing effectiveness and revenue.
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    Manufacturing

    Combine data from multiple customer touchpoints with real-time product usage and quality data. Increase cross-sell opportunities while proactively reducing customer churn.
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    Support

    Equip customer support teams with comprehensive views of the customer based on their latest activity. Reduce time to resolution for customer issues and make your customers more successful.

Why Rockset

Why Customer 360s Are Hard

How Rockset Makes It Easy

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Customer data in different formats: Customer data includes sales transactions in OLTP databases, user activity in streaming systems or data lakes, and data from internal CRM and customer service tools—each with a different data model.
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Analyze data regardless of data format: Bring in data with different formats without requiring upfront transformation. Build accurate pictures of your customers using as many types of customer data as possible.
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Can't incorporate real-time data: Real-time purchase, product or user activity data has to go through latency-inducing data pipelines before being queried, so your customer profiles don't reflect the latest customer interactions.
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Optimized for low data latency: Rockset ingests data continuously from real-time sources and makes it queryable within seconds. This ensures the actions you take are based on the most up-to-date data.
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Requires complex analytics: Consolidating customer data is just the first step. Building a real-time customer 360 requires running complex analytics, spanning multiple data sources, to build customer profiles on the fly.
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Fast search, aggregations and joins: Run complex queries, including joins, at scale. Generate unified customer profiles in real time, combining internal and external, live and static customer data.

Why Customer 360s Are Hard

Other
Customer data in different formats: Customer data includes sales transactions in OLTP databases, user activity in streaming systems or data lakes, and data from internal CRM and customer service tools—each with a different data model.
Other
Can't incorporate real-time data: Real-time purchase, product or user activity data has to go through latency-inducing data pipelines before being queried, so your customer profiles don't reflect the latest customer interactions.
Other
Requires complex analytics: Consolidating customer data is just the first step. Building a real-time customer 360 requires running complex analytics, spanning multiple data sources, to build customer profiles on the fly.

How Rockset Makes It Easy

Check
Analyze data regardless of data format: Bring in data with different formats without requiring upfront transformation. Build accurate pictures of your customers using as many types of customer data as possible.
Check
Optimized for low data latency: Rockset ingests data continuously from real-time sources and makes it queryable within seconds. This ensures the actions you take are based on the most up-to-date data.
Check
Fast search, aggregations and joins: Run complex queries, including joins, at scale. Generate unified customer profiles in real time, combining internal and external, live and static customer data.
Core Features for Customer 360s
  • 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 Index™

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

Resources



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Real-time customer 360 on Kafka, MongoDB data

A step-by-step guide to building a real-time customer 360 using seconds-old purchase data from MongoDB and marketing data from Kafka.

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From batch to real-time user engagement

Companies need to embrace real-time analytics to compete and survive. Only those that have invested in a real-time data stack will thrive.

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Analyzing consumer behavior in real time

Fynd uses Rockset to perform fast queries on real-time Kafka event streams, so they can react to consumer behavior as it happens.

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Schemaless ingest and auto schematization

Rockset's schemaless SQL platform automatically infers schema at read time, allowing you to analyze messy data using SQL.

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Converged Index™ for blazing-fast queries

Rockset automatically builds search, columnar, and row-based indexes on every field of the data it ingests to accelerate different types of queries.

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Real-time analytics on Kafka data

Connect Kafka and Rockset to obtain real-time analytics with ad hoc SQL queries on event streams.

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Customers

Real-Time Analytics At Lightning Speed

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