Artificial intelligence (AI) helps turn governed marketing data into predictions and recommendations. In an insights and intelligence layer, AI and machine learning work alongside advanced analytics to identify patterns in customer behavior and inform marketing decisions. section 2.3.3
Finding customers likely to leave
A marketer might define a churn-risk audience using a handful of rules and intuition. An AI model can instead weigh hundreds of customer features, their transformations, and their interactions to predict churn for each customer. Marketers can then combine those predictions with other customer attributes when defining an audience. section 4.4.5
Other marketing uses include:
- Recommending products from browsing and purchase patterns. section 2.3.3
- Identifying campaign timing from real-time engagement data. section 2.3.3
When choosing a first-party data solution, assess both how easily existing predictive models enter marketers’ workflows and whether its generative AI capabilities fit the team’s plans. Generative AI for marketing is more effective when it can use a unified dataset, available channels, and organizational objectives. Organizational policies may also govern its use; AI features alone are not a substitute for a suitable architecture. section 4.4.5
Table 4.6 Artificial intelligence considerations
| Solution |
Considerations |
| Composable CDPs |
(+) Composable CDPs can connect directly to your team’s predictions, and the cloud-native architecture makes it easier to incorporate new AI capabilities provided by your cloud platform. |
| Marketing clouds/engagement platforms |
(-) MCs often provide limited prebuilt AI capabilities that focus on ease of use but lack integrations with major cloud platforms that offer more-advanced AI capabilities. |
| Monolithic CDPs |
(-) Monolithic CDPs often provide limited prebuilt AI capabilities that focus on ease of use but lack integrations with major cloud platforms that offer more-advanced AI capabilities. |
| In-house builds |
(+/-) The applications of AI and the availability of best-in-class AI capabilities are subject to the design of the in-house build, and they vary widely from one build to the next. |
Compare solution types by their access to existing predictions and newer AI capabilities: composable CDPs can connect to team models and cloud-platform capabilities, while prebuilt options may be easier to use but more limited. section 4.4.5
