Marketing departments have been some of the primary benefactors of the development of artificial intelligence (AI) and machine learning (ML) technologies.
Marketers use AI and ML tools, platforms, and services to segment audiences and target their most valuable customers more efficiently and effectively. Customer data platforms (CDPs) that are equipped with AI and ML capabilities help marketers understand and predict customers behavior in order to personalize customer experiences.
For marketers to set themselves apart from competitors and gain a competitive edge, they should be looking to more advanced AI/ML-powered applications and use cases that can truly set them apart. Here are several ways marketers can use AI-powered insights from their CDP to elevate their marketing efforts.
Create Accurate Customer Data Profiles
One of the top AI/ML use cases for marketing is providing more visibility into customer data. With AI-powered identity resolution, duplicative data can be cleansed and consolidated into a single customer profile. This eliminates redundancies or inaccuracies, and gives marketers greater visibility into the customer journey.
Identity resolution also helps marketers link unknown customer data to known profiles, and identify audiences with similar affinities or attributes. This allows for greater personalization, segmentation, and improved customer experience for both known and unknown audiences.
Data-Driven Campaign Optimization
AI helps marketers recognize and categorize customer segments by their behavioral patterns. These insights can then be used to optimize ad performance and spend by monitoring how well different types of content performs against individual customer segments.
Marketers can use AI-powered predictive analytics to identify additional target audiences for micro-segmentation within their CDP. Predictive analytics enrich segmentation by enabling marketers to:
- Identify and group customers by likelihood to convert, and group them into a separate audience segment for tailored lead nurturing.
- Analyze customer purchase history to find upsell or cross-sell opportunities for high-value customers.
- Inform loyalty programs to improve retention, and improve customer lifetime value.
- Avoid targeting loyal high-value customers with irrelevant messaging or experiences.
AI also allows marketers to predict what creative will work on their ads before their campaign begins. By using AI to predict ad creative performance, marketers can drive conversions at lower costs.
Orchestrate the Customer Journey
With an AI-powered CDP, brands can go beyond tailoring ads for campaign optimization, and personalize the full customer experience across all channels and touch points.
One of the most powerful applications of AI-powered functionality, along with predictive analytics, is next-best action content and product recommendations. An AI-powered next-best action model will leverage customer behavioral data and single customer view profiles to identify personalized content and messaging for specific audiences that deliver value through the right channel, at the right time.
Developing and delivering data-driven content goes hand-in-hand with customer journey orchestration. A CDP can provide the visibility needed to understand how customers behave at different journey stages. These insights can help marketers plan and execute campaigns that move customers through the customer journey effectively.
By providing users with quality recommendations based on previous search and purchase history, buyers will receive content that is highly relevant and personalized to their unique customer journey. This can improve conversions and ad campaign performance.
Increase Efficiency Through Automation
According to a recent Hubspot survey, the average marketer spends around 16 hours a week on routine tasks – that’s about one-third of their work day. The types of routine tasks include tagging content and images, segmenting clients, and running manual campaigns.
The same survey found that the process of creating and sending emails takes an average of 3.48 hours per week, while the process of collecting, organizing, and analyzing marketing data from disparate sources for about 3.55 hours per week.
With a CDP equipped with AI tools, marketers can automate routine tasks and free up time to focus on more thoughtful, creative, and productive tasks.
Using AI for Data-Driven Marketing
With advances in AI and ML, marketers can use their CDP to tailor customer experiences and guide data-driven content development. It’s time to use these capabilities to free up your team and focus on what matters– your customers.