Fueling Customer Intelligence for the Enterprise: Audience Analytics
by Kiki Burton
posted on 09-21-2017
In our conversations with customers, we’ve observed that marketers and publishers often leverage audience segmentation and customer analytics in silos — a data management platform houses rich segmentation comprised of first, second, and third-party data assets, while the analytics side of the operation stores valuable customer engagement metrics and insights. Today, we’re breaking down these barriers to empower data and analytics to work together to seamlessly power and inform customer experiences. Adobe Analytics Cloud introduces Audience Analytics — an enhanced integration between Audience Manager and Analytics, aimed at driving enterprise insights, intelligence, and action.
A richer customer profile.
As customer data grows increasingly varied and expansive, it is becoming that much more important for marketers to see a full view of a customer across digital touchpoints. Audience Analytics provides the ability to take segments from Audience Manager — such as media exposure, offline or CRM attributes, third-party data, email engagement, and survey data — and then send it back into Analytics. This can be woven together with site or app metrics and engagement information to create a more complete customer profile for the enterprise.
In the data economy, it is essential to understand and measure audience segmentation in the context of customer value, channel effectiveness, and consumer journey — and be able to react quickly. Adobe Analytics has a long-standing reputation for providing digital marketers with best-in-class analysis tools that immediately impact the customer journey. Through Audience Analytics, marketers can incorporate Audience Manager segments into existing Analytics workflows. For example, the segment data can be utilized along with Analysis Workspace features such as the Segment Comparison tool, flow visualizations, and Venn diagrams. This new integration turns insights into action faster than before, giving marketers additional insights that guide the optimization of current campaigns, inform personalization strategy, and enhance existing segmentation practices.
Example Use Cases:
- _See the results of data sources stored in Audience Manager in Analytics.
_Ingest purchased third-party segments from Audience Manager — such as demographic or psychographic attributes — into Analytics to view overlap with awareness, consideration, and purchase segments, and optimize accordingly. For example, if you’re an online retailer looking to target a particular demographic — such as urban moms — you can purchase data from Audience Marketplace that gets you close to the criteria of that demographic. Incorporate that data back into Analytics to analyze how this prospective segment of urban moms interacts with your brand, and tie this information to their purchase behavior for key products.
- Tie off-site advertising to user action. Send media exposure segments stored in Audience Manager to Analytics to see how particular placements, creatives, or campaigns contribute to funnel activity. For example, if you’re on the media team for a large financial institution, share the data associated with your media programs with your analytics team. Work with your analytics team to see how your media buying initiatives are contributing to campaigns — perhaps to convert new users to a low-interest mortgage offer. Optimize your media campaigns based on insights.
- Use onsite engagement to inform content. Use Analytics workflow, such as the flow feature to test which first-party segments contribute most to user engagement, and apply your findings in ad sales efforts or content personalization accordingly. For example, the personalization team at a publishing company could send data from Audience Manager to Analytics, including second and third-party segments. Then, they could analyze which first-party segments contribute the most to user engagement, and work with content teams to optimize page content accordingly.
- Consolidate reporting. Track data against key metrics like conversion and engagement in one place, rather than in separate silos. For example, an audience management team at an automotive brand might need to report key metrics to global stakeholders on all facets of audience engagement — including audience interaction with paid advertising, along with site and app engagements. They could work with the analytics team to bring Audience Manager segmentation into Analytics, and be able to report and benchmark across data sources.
DMP’s have traditionally been viewed as data and activation hubs — places to define and package an audience, activate to various channels, and optimize as necessary. Similarly, customer analytics platforms have customarily been valuable for tracking site and app engagement. Adobe is looking beyond tradition with Audience Analytics to more closely connect the strengths that exist within the Analytics Cloud. Audience Analytics empowers marketers and publishers to collaborate across teams, consistently track audience metrics, and drive valuable customer experiences quickly and at scale.