Rekindle the spark by delivering true personalization for customers with AI
Time to read: 4 minutes
As technology aimed at supporting customer engagement has evolved, each new development has promised greater intimacy and warmth—like a corner store where the proprietor knows your name. However, these tools often create greater distance and coldness instead.
In fact, “customer centricity,” as promised by many software vendors, is a fallacy. Although companies are well-intentioned, technology has only allowed them to look at customers in generic ways. It is difficult to offer true personalization if your approach is based on “personas” and “audiences,” which aggregate large numbers of individuals into amorphous clumps.
This approach leaves businesses vulnerable. Customers feel unseen and are more likely to defect to other brands that deliver a more personal touch—or maybe just lower prices to compensate for the transactional nature of the relationship.
Companies are aware of the need to put the customer at the heart of their business, and they look to personalization as the key to delivering on that promise. According to Twilio’s recent State of Customer Engagement Report, 91% of companies say that they always or often personalize engagements with consumers.
But consumers don’t agree. Just 56% of consumers report that their interactions with brands are always or often personalized.
Siloed data is often the culprit. As customers move through their journey with a company, each department that interacts with them collects the data that’s most relevant to achieving its objectives. Then, sales data is often stored in a customer relationship management (CRM) platform, marketing data is stored in a variety of marketing platforms, customer support data in a contact center application, etc.
Not only is this data siloed, but it’s also often in completely different formats, with different fields and incompatible customer IDs. A company in this situation will struggle to connect the dots for its customers, leading to frustrating experiences.
The problems are not just theoretical. Overall customer satisfaction has been dropping since 2018—despite increased business spending on customer experiences—due to data silos and poorly implemented customer experience solutions, as well as rising consumer expectations. It’s no wonder that 47% of marketers say that data silos are their biggest problem.
You might think that AI is just another turn of that wheel, promising personalization but delivering only frustration.
But this new era of AI is different. With its conversational capabilities, generative AI is capable of human-like dialogue. Predictive AI can anticipate customers’ needs and next actions, allowing brands to tailor their engagement better. Taken together, AI enables companies to respond to each customer as a true individual, not just a member of a cohort.
In the analog world, it would be impossible to hire a customer success agent for every individual customer. But in the digital AI world, individualized engagement at scale is possible for the first time.
AI can help with customer interactions in several ways:
- Tailored customer journeys: AI can help create the most relevant customer journey for each individual, tailoring the next offer and outreach based on a nuanced understanding of that person’s past interactions, their preferences, and their likelihood of connecting with each offer.
- Customer predictions: AI can predict what a customer is likely to do next and what they are most likely to respond to. Predictive AI can estimate, with great accuracy, someone’s likelihood to make a purchase or to churn, their likelihood to add a product to a cart or to use a promo code, or even their predicted lifetime value (LTV). This is immensely valuable data for marketers.
- Content creation and optimization: Generative AI can help marketers who need to create content from scratch. For example, marketers can enter simple text prompts that turn ideas into fully formed emails in seconds, including recommended subject lines and message copy that’s optimized to convert.
- Purchase or expand their use of Box
- Attend in-person field events
- Experience BoxWorks, the company’s annual customer and developer conference
From here, Box tailors marketing content and campaigns to better meet customer needs. This forward-thinking brand is very much at the forefront of using AI to enhance the customer experience and, in turn, drive business results.
It may seem like the capabilities we’ve talked about should already exist. The reality is, they should. But only the biggest brands can deliver personalization with this kind of back-end efficiency right now.
AI can now make all brands more human. But making this work requires investment in integrating data across silos. The most ambitious AI strategy may stumble if it’s not built on a strong foundation of consistent, well-managed data. Getting the data integrated is an important first step for companies that want to reap the rewards of the AI renaissance.
Brands also need to make an investment in training and continuous improvement. Humans need to learn how to use AI effectively, whether they are developers writing code with an AI assist or support staff solving problems with natural language understanding. Additionally, your AI needs to be trained on relevant, proprietary, first-party data to deliver results that are truly personalized to your customers and your business.
Amid the evolving landscape of customer experience, AI has emerged as a powerful catalyst for transformation. By addressing data silos and harnessing AI’s capabilities, brands can finally deliver, digitally, the kind of experience offered by a local store.
Through strategic deployment of AI, companies can rekindle the spark and help their customers fall in love with them all over again. Learn how your marketing team can leverage Twilio’s CustomerAI technology to drive unique customer experiences.
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