In a world where every transaction, interaction and communication generates a data point, it’s fair to say many businesses are creating and managing more data than they know what to do with. Customer data is hoarded away on a database or other distant location, in the hopes that eventually it will come in useful, but all too often that single cohesive view of a customer is exactly that – a hope, rather than a reality.
At the same time, every brand is working to find ways to deliver personalized, meaningful interactions with each customer. Here there is somewhat of a mismatched perception – with 81% of brands saying they understand customers deeply, but just 46% of consumers agreeing, according to Twilio’s 2024 State of Customer Engagement report. Linking the two is at the core of an effective data strategy – and it’s where the combination of artificial intelligence into that strategy becomes additionally effective. AI can help automate data collection, integration and analysis processes, establishing the workflows that can pave the way to more meaningful customer experiences.
Senior Product Marketing Manager at Twilio.
Taking on the administrative legwork
The first use case for using AI to assist with data strategies is in collecting customer data more efficiently. In conjunction with a customer data platform (CDP), which offers a unified view of the customer with clean, consented and consistent data, leveraging every data source your company has, AI can serve as a professional organizer of customer data. It can categorize data points, identify correlations and store it in a way that’s easily retrievable and actionable. AI can also make suggestions on how this data could be put to work – which kinds of personalization might be most effective for a given customer base, for example.
Once that data is collected and organized, it’s time to put it to work – and again AI can help. Let loose to analyze vast datasets, data teams can leverage AI to tailor their strategies and carry out informed testing and comparison. Segmenting audiences, triggering tailored campaigns, and optimising messaging and delivery times – AI can help do all of this at scale, allowing teams to focus on the bigger-picture strategy instead of dedicating time to the process.
Unified profiles
A third use case for AI in this world of customer engagement is in creating golden profiles – an ideal state where a business has a comprehensive, accurate, and dynamic representation of a customer, which is continually updated as new data and insights they contain are captured. 64% of companies surveyed for Twilio’s 2024 State of Customer Engagement said they are already using AI to build a unified view of every customer, which is promising but also shows how much work there is still to be done. This status can be a real game changer for businesses looking to make their marketing communications work harder. AI can help integrate data from traditionally siloed locations into one cohesive profile, cleansing and correcting inconsistencies in the process.
As organizations become more comfortable using AI in their data strategies, it’s also likely to play in a role in maintaining data privacy and compliance. We’re already seeing many cybersecurity tools using AI to analyze and triage evolving threats to data security, for instance. AI could also make obtaining customer consent more straightforward, by analyzing user interactions and offering choices based on those preferences.
Fine-tuning customer journeys, as they happen
The rise to prominence of wholly digital customer experiences has led to the creation of journey orchestration as a discipline – with entire specialist teams in larger organizations dedicated to building and fine-tuning the customer journey so the brand remains as engaging and easy to interact with as possible.
AI again has an invaluable role to play here in offering predictive analytics, providing forecasts of behaviours and preferences to allow data teams to customise the journeys customers take in real-time. Thanks to the processing power of AI, marketing campaigns can be analyzed and adjusted on an ongoing basis, to ensure customer experiences are as relevant and engaging as possible.
Finally, those engaging experiences are no longer based on traditional demographics thanks to AI. Static audience lists and broad segment categories are a thing of the past in a world where AI allows companies to dynamically segment audiences according to their evolving behaviors. AI can help companies build more responsive, targeted, and effective campaigns as new interaction and purchase data come in.
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