Managing Customer Data with Exacaster Customer 360 Primer

Learn how to use Exacaster Customer 360 by selecting and managing workspaces, creating production, staging, or unit-specific environments to unify customer data and invite team members.

Create and name new workspaces, switch between prepaid and sandbox environments, and organize customer data in an empty workspace setup within Exacaster Customer 360 Primer.

Manage your workspace settings and team roles by updating the workspace name, deleting the workspace, and inviting members with access levels from viewer to owner.

Explore the main menu of the Exacaster customer 360 platform, including sources, customers, metrics, data exposure, data sync, and the marketplace, with S3 and apps output as examples.

Review the publicly exposed roadmap, vote on features, and track wallet-based prioritization. Access documentation and raise questions via the report feature for quick team support.

Navigate notifications and personal settings to monitor data events, edit your profile and security options, manage notification preferences, and generate API tokens for programmatic access.

Discover how sources serve as the primary means to integrate data into customer 360 platform, with options like Amazon S3, data from workspaces, and databases such as Redshift and Snowflake.

Create an Amazon S3 source by selecting Amazon S3, naming the source, and connecting to your bucket, then manage access keys, secret keys, and automated key rotation every six days.

Prepare event or snapshot data files for Amazon S3 ingestion into the Customer 360 platform, following strict naming, versioning, and partitioning; include user ID and timestamp columns with proper escaping.

Learn to connect to an Amazon S3 bucket with a file transfer tool, upload the snapshot users and events payments files, and start processing for Customer 360.

Review Amazon S3 source processing by inspecting uploaded files, moved to processed or Sandfire Files, with duplicates and incorrect structures routed to failure; Customer 360 shows snapshot and payments events.

Create a Python demo source and send data to Customer 360 via API, using a Jupyter notebook to generate events and batch data for scalable delivery.

Sync data across workspaces using a customer 360 workspace source, generating a security token for cross-workspace transfers, then export active sandbox users to the prepaid customers workspace for aggregation.

Connect to Amazon Redshift as a source, configure the connection, and identify usable tables for Exacaster Customer 360, ensuring each has a data column and a unique user identifier.

Review the technologies for bringing customer data into the Cancer Customer 360 platform, including Amazon S3 transfers, real-time API delivery, and data exchange across workspaces and databases.

Select a primary snapshot from Amazon S3 sources that holds full information for the active customer list. Use this list for all metric calculations, ensuring every active customer is included.

Explore types of metrics, including base metrics like sums and max, snapshot metrics, derived metrics, and Spark SQL based metrics, transforming raw data into actionable insights for customer value management.

Create event based metrics from payments events, counting and summing daily, weekly, monthly, and 90 days; analyze max amounts, most frequent channels, and days since last event for each user.

Validate and assign proper data types in the user snapshot schema, then convert attributes into metrics. Build flag and lifetime metrics, including days between calculations, with daily automatic updates.

Create a metric based metric to compute the average payment amount over the last 90 days, selecting a daily/weekly/monthly period and defining its data type.

create spark sql based metrics to compute daily averages from a payments source, using a secure environment, and name metrics like average payments in the e-shop channel.

Learn to edit and wrap up metrics, fix zero-payment errors with revised formulas, and review four metric types and Spark aggregation functions for exposing metrics to destinations.

Learn how to set up destinations to expose customer data to systems like Amazon S3, define event and metric exports, and run data sync to generate and verify export files.

Expose metrics through an API destination named career by creating a metrics export, configuring API resources, and testing with a token-authenticated API call to access all daily customer metrics.

Learn how identity mapping extends the Exacaster Customer 360 Primer API by using extra identifiers like email or mobile number to query the same customer data after syncing identities.

Configure a customer 360 workspace destination by adding a customer 360 source, generating and using a token, and exporting metrics and payments to the sandbox destination.

Learn to configure a customer facts destination to export metrics from a customer journey platform into Exacaster, including setting the integration, API URL, and token for marketing campaigns.

Connect a relational database using a PostgreSQL destination, create an export of selected metrics, define the destination name, and verify the metrics appear in the Democrats table.

Explore five methods to expose customer information, including Amazon S3, API access, and queries via customer identifiers, with exports to PostgreSQL, workspaces, and marketing automation platforms such as Customer Journey.

Learn to trigger and schedule data syncs in Customer 360, including manual runs for all data, specific destinations, or exports, and daily scheduling with latency and backfill settings.

Configure notifications across workspaces with delivery options (bell, platform, email) and per-workspace rules to alert on data sync failures, missing information, and data latency.

Explore the Caster customer 360 apps market, including prepaid churn prediction and next best offer tools, and learn how gap radar, offer management, and recommendations library optimize outcomes.

Learn key Customer 360 platform capabilities and become a certified Customer 360 user, while sharing candid feedback to improve future courses and preview the CDP next best offer applications course.