How Summary Data Enhances Adobe Customer Journey Analytics Datasets

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Introduction

Adobe Customer Journey Analytics (CJA) has introduced a new dataset type: Summary data. This feature significantly enhances CJA's data model and expands its potential use cases, offering users improved capabilities for data analysis and insight generation. Summary data consists of time-series information from a summary dataset, based on a schema using the XDM Summary Metrics class. Currently, only hourly or daily time-series data are supported. By incorporating Summary data, CJA builds upon its existing foundation of Event, Lookup, and Profile datasets, creating a more comprehensive and versatile toolkit for practitioners.

The introduction of Summary data unlocks exciting new possibilities for exploring and interpreting data within CJA. This powerful dataset type complements existing options by enabling users to work with pre-aggregated information, providing a high-level perspective that's particularly valuable for certain analyses. By integrating Summary data alongside established dataset types, CJA users can now adopt a more holistic approach to data management and interpretation—uncovering new insights and facilitating more nuanced decision-making processes.

Understanding Summary Data

Summary data in CJA offers a powerful way to incorporate pre-aggregated data into your analysis. This feature allows you to import high-level, summarized data directly into CJA, providing a comprehensive overview of your data landscape without the need for granular, person-level event details. By leveraging Summary data, analysts can efficiently work with large volumes of historical information, integrate third-party aggregated data, and quickly generate top-level insights.

The value of Summary data lies in its versatility and efficiency. For historical data, this feature enables efficient ingestion of pre-aggregated information, bypassing the need to process individual events at the person level. When dealing with third-party data that doesn't provide person-level event granularity, Summary data offers a straightforward solution for data integration. Moreover, for inherently aggregated data, such as campaign cost data or aggregate survey results, this feature fits naturally within the CJA dataset ecosystem.

By incorporating Summary data alongside traditional Event, Lookup, and Profile datasets, CJA practitioners can create a more holistic view of their data. This approach allows for the blending of high-level trends with detailed customer behaviors, enabling more nuanced and comprehensive analyses. Whether you're looking to establish benchmarks, integrate external data sources, or streamline your reporting process, Summary data in CJA provides a valuable tool for enhancing your analytical capabilities and driving more informed decision-making across your organization.

Use Cases for Summary Data

• Historical data migration: Ingest pre-aggregated data without the need for individual Person activity events.

• Third-party data integration: Incorporate aggregated data from external sources that don't provide Person event-level details.

• High-level reporting: Create top-level dashboards and reports using summarized data for quick insights.

• Performance optimization: Reduce data processing time for large datasets by working with pre-aggregated information.

Comparing Dataset Types in CJA

CJA Dataset Type	Timestamp Granularity	Key Characteristics	Application in CJA
Event	Seconds for reporting, with event ordering preserved down to milliseconds	Detailed, timestamped Person activities	Customer journey analysis, behavioral tracking. This data spans a range from up to ten years in the past to one month into the future.
Lookup	Not Applicable: Non-Timestamp Based	Static data for enriching other datasets	Adding context to Event or Profile datasets
Profile	Not Applicable: Non-Timestamp Based	Person-specific attributes	Customer attributes
Summary	Hourly OR Daily per Summary data schema	Pre-aggregated, high-level data	Historical trends, third-party integrations, and goals or targets are displayed in hourly or daily aggregates. This data spans a range from up to ten years in the past to one year into the future.

Best Practices for Using Summary Data

1. Identify datasets that are inherently aggregated and don't require person-level event granularity for effective analysis in CJA. This step is critical for determining which data is most suitable for summary data ingestion.

2. Strategically use summary data for high-level reports and quick insights into overall trends, targets, and goals at hourly or daily intervals. Reserve activity event data for more granular analyses requiring person-level information. This approach maximizes the strengths of both dataset types, ensuring efficient use of your data resources.

3. Enhance your analytical dashboards by combining summary data with other dataset types available in CJA. This integration provides a more comprehensive and nuanced view of your data landscape, enabling richer insights and more informed decision-making.

4. Leverage summary data to efficiently import and analyze large volumes of historical information without straining your license limits. This practice is particularly valuable for extensive datasets, allowing quick access to aggregate historical trends and patterns.

5. You can now configure a CJA Connection and Data View to report exclusively on Summary data. Additional Event, Profile, or Lookup data is not required as part of your configuration.

6. The timezone of your Summary data is defined at the summary schema level in Experience Platform. This timezone setting applies only to hourly granular data. Per the Experience League Summary data documentation:

   For daily granularity, Experience Platform assumes UTC, unless a timezone offset is included in the timestamp. When adding the summary dataset containing the daily summary data, Customer Journey Analytics ignores the timezone definition set on the schema and respects the day associated with the timestamp from the data in the dataset.

   For hourly granularity, Customer Journey Analytics respects the timezone configured on the summary data schema in Experience Platform when interpreting the timestamp. The table below provides some examples of this interpretation.

7. To set the correct timezone for your hourly granular summary data, you must configure the summary data schema appropriately. At present, setting the granularity and timezone for your summary data schema requires an API call. You can find a code example for this in the Experience League documentation. There's no user interface equivalent for this configuration at this time.

8. Ensure consistency in component settings for Summary data groups. These groups establish associations among all dimensions within the grouping, allowing you to combine dimensions from summary datasets with other dimensions for reporting purposes.

Conclusion

The introduction of Summary data marks a significant leap forward in supported CJA data analysis capabilities. By complementing existing dataset types with pre-aggregated information, CJA now offers a more comprehensive toolkit for analysts and decision-makers. This feature not only streamlines the process of working with historical and third-party data but also enables more efficient high-level reporting and trend analysis.

As organizations wrestle with ever-increasing volumes and varieties of data, the ability to ingest summary-level information alongside granular Person event data becomes invaluable. CJA's Summary data provides this flexibility, allowing users to strike a balance between detailed insights and broader trends. This holistic approach to data analysis empowers businesses to make more informed decisions, backed by a complete view of their data landscape.

Moving forward, the strategic use of Summary data in conjunction with Event, Lookup, and Profile datasets will be key to unlocking the full potential of Customer Journey Analytics. By adopting best practices and harnessing the strengths of each dataset type, organizations can enhance their analytical capabilities, streamline their reporting processes, and ultimately extract more value from their data investments.

For more information on implementing Summary data in your CJA workflow, refer to the Adobe Experience League documentation. This includes the official documentation, prerequisites, summary data group component settings, and a comprehensive use case walk-through.