AI-powered personalization: The next frontier in customer engagement

Personalisation in digital marketing has emerged as a pivotal strategy for businesses aiming to enhance customer engagement and satisfaction. This approach involves tailoring experiences for individuals based on their preferences, behaviours, and interests, thereby creating unique and relevant interactions. As the digital landscape evolves, brands are increasingly recognising the significance of personalisation in standing out amidst competition and fostering lasting relationships with customers.

Current Landscape of Personalisation in Digital Marketing

Personalisation has become a crucial aspect of digital marketing in today's landscape, with businesses recognising its ability to enhance customer engagement, boost loyalty, and drive revenue growth.

According to Adobe's recent study, 67% of consumers expect personalised content, underscoring the growing demand for tailored experiences.

The importance of it is further highlighted by the fact that 75% of business leaders consider it table stakes for digital experiences. A Twilio report suggests that 85% of businesses believe they are offering personalised experiences, but only 60% of consumers agree, indicating a gap between perception and reality.

The personalisation market is healthy and growing, with the global personalisation software market reaching $943.25 million in 2021 and expected to grow at a CAGR of 23.58% to reach $2.72 billion by 2027. 

The real advances are happening due to the influx of artificial intelligence (AI) and machine learning (ML), with the global AI-based personalisation market projected to grow at a CAGR of close to 13%.

The Future of Personalisation: Trends and Predictions

1. Hyper-Personalisation: It involves using AI, data, and analytics to create highly customised experiences for individual customers. Platforms like Spotify and Netflix exemplify it by curating playlists and recommending content based on user behaviour and preferences.
2. One-to-One Engagement: It signifies a shift towards establishing personal relationships between customers and brands.
3. AI-Driven Personalisation: AI plays a pivotal role in driving personalisation strategies through various tools like chatbots, analytics, and recommendation engines.
4. First-Party Data Importance: The significance of first-party data collection has heightened in the absence of third-party cookies. First-party data, obtained directly from customers, provides valuable insights into individual preferences, behaviours, and interactions

Examples and Case Studies of Personalisation Strategies

1. Sephora: Beauty Insider Program

Insight: Sephora's Beauty Insider program utilises personalised product recommendations to enhance customer loyalty and retention.

Example: By offering tailored product suggestions based on individual preferences, Sephora creates a personalised shopping experience that drives customer engagement and satisfaction.

2. Hype Co.: Leveraging Personalization for Customer Engagement

Insight: Hype Co., a forward-thinking e-commerce brand, utilised personalisation to skyrocket customer engagement rates.

Example: By implementing personalised marketing strategies, Hype Co. was able to create tailored experiences for customers, leading to increased engagement and loyalty.

3. Starbucks: Personalising the Coffee Experience

Insight: Starbucks uses its mobile app to offer personalised offers and rewards based on purchase history and location data.

Example: Starbucks app remembers customers' favourite drinks and provides personalised discounts, simplifying the ordering process and enhancing customer loyalty.

Unique Insights and Strategies for developing customer engagement and communication

Here are some unique insights and strategies for developing customer engagement and communication, along with special tools and approaches that go beyond conventional methods:

1. Customer Communication Strategy with Unique Tools:

• Utilise an all-in-one customer service platform that integrates marketing, sales, and support functions to deliver high-quality experiences efficiently.

• Implement AI to automate tasks, triage customer requests, and identify trends in customer behaviour, enhancing organisational efficiency and customer service.

2. Proactive Customer Service and Engagement:

• Be proactive in communicating with customers, anticipating their needs, and addressing issues before they arise to demonstrate a customer-centric approach and build trust.

• Offer more than automated responses by engaging with customers on social media platforms, providing personalised responses, and humanising interactions to enhance customer relationships.

3. Internal Communication and Collaboration:

• Use tools like popular communication software and automated ticketing systems to improve collaboration, transparency, and responsiveness when addressing customer inquiries.

• Establish systems that facilitate internal communication and support collaboration among employees from different departments to deliver a cohesive customer experience.

Conclusion

As businesses navigate the digital realm, the ability to provide personalised experiences has become a fundamental requirement rather than a mere option. The future of personalisation in digital marketing lies in harnessing advanced technologies like artificial intelligence and machine learning to deliver tailored messages, offers, and experiences that cater to the unique needs of each customer. By embracing it, brands can not only enhance customer satisfaction and loyalty but also drive revenue growth and competitive advantage in an increasingly dynamic marketplace.

Shiva Bhavani, CEO of Wing Communications