Generative AI

The role of generative AI in personalised advertising and recommendations

Gone are the days when customers only had to choose from a hundred or so products available in their nearest shops. With millions of choices at their fingertips, customers often struggle to make a decision, with a 70.19% average cart abandonment rate. So, how can you help your customers make a choice? The answer lies in personalisation and personalised advertising.

What is AI-powered personalisation?

Today's customers expect a personalised experience, and businesses need to find new ways to tailor their experience. Machine learning and generative AI systems have brought on exciting developments in businesses’ approach towards personalisation in advertising. Leveraging customer data, from demographic information and purchase history to browsing history and social media interactions, AI-powered personalisation can help businesses understand the unique preferences and needs of every customer and tailor a unique experience to engage customers.

Implementing generative AI in marketing

Leveraging generative AI for marketing and personalisation requires careful consideration, planning, and execution of your strategic efforts. But how can you implement an AI-powered personalised advertising experience for your customers?

• Start by defining your marketing and personalisation objectives. Describe why you want AI-powered personalisation – to increase revenue, boost customer satisfaction, or increase customer retention – for effective strategy development and implementation.
• Your AI-powered personalisation models are as good as the quality of data they can use. So, focus on developing mechanisms to collect and store high-quality data to better understand your customers.
• Continuously test and refine your personalisation strategies.
• Be transparent about your data collection and usage policies to build trust with your customers.
• Integrate personalisation across all channels and customer touchpoints for consistent customer experience.

Applications and examples of personalisation in marketing

As personalisation and hyper-personalisation efforts reflect directly on increased customer satisfaction and revenue, close to 92% of global businesses are trying to leverage AI to facilitate their personalisation efforts. Generative AI systems have the potential to transform personalisation efforts across industries. But what does it look like to use AI and machine learning tools to hyper-personalise a unique experience for each customer?

Here are some examples and applications of using AI-powered personalisation in advertising and marketing:

• Personalised product recommendations and ad targeting to help customers navigate the sea of products.
• AI chatbots for a personal connection and quick customer service.
• Personalised communication and content from individualised email communication to dynamic websites.

Challenges in personalised advertising

With potentially endless possibilities, businesses around the globe are assigning more than half of their budgets to personalisation efforts, but only 35% are satisfied with their omnichannel personalisation success. This is because, despite the attention and investments in personalised advertising, businesses often fail to consider key AI-powered personalisation challenges, such as:

• Defining the target user segment effectively can be one of the biggest hurdles in personalisation efforts, as you can focus on numerous factors to segment a market. Creating a target user persona can be a much better strategic approach for effective segmentation.
• Establishing trust and transparency with customers regarding data privacy and use for personalisation. This disconnect in customer confidence can be a great obstacle to personalisation in advertising.
• Striking a hyper-personalisation balance is the difference between a personalised vs. creepy customer experience. You must consider customer feedback and determine what data to use for a useful personalised marketing experience.
• Costs and resources necessary for implementing generative AI in marketing are some of the biggest barriers to personalised advertising. Access to qualified personnel, availability of quality data, and investment in technological infrastructure are still inaccessible to many smaller businesses.

Advantages of generative AI in marketing

Despite its implementation challenges, generative AI in marketing has tremendous potential and can help you gain a competitive advantage in today’s digital economy. Reaching customers at the right time with the right message on the right platform brings many advantages:

• Data-driven insights that can help you understand your customers better, guide your strategic efforts, and stand out from the competition.
• Better customer experience that accounts for the preferences and needs of individual customers. This can result in customers feeling understood, boosting engagement, increasing satisfaction, and fostering loyalty.
• A satisfied and loyal customer base means a reduced churn rate, allowing you to focus your efforts on serving existing customers better instead of constantly worrying about reaching and acquiring new customers.
• Engaged customers who receive personalised recommendations are less likely to abandon their carts and may even purchase additional items. This boosts the average order value for each customer, boosting the overall revenue.

For organisations on the digital transformation journey, agility is key in responding to a rapidly changing technology and business landscape. Now more than ever, it is crucial to deliver and exceed organisational expectations with a robust digital mindset backed by innovation. Enabling businesses to sense, learn, respond, and evolve like living organisms will be imperative for business excellence. A comprehensive yet modular suite of services is doing precisely that. Equipping organisations with intuitive decision-making automatically at scale, actionable insights based on real-time solutions, anytime/anywhere experience, and in-depth data visibility across functions leading to hyper-productivity, Live Enterprise is building connected organisations that are innovating collaboratively for the future.

How can Infosys BPM help?

Infosys Generative AI Business Operations Platform (Infosys Topaz) is a set of AI-first, ready-to-use BPM-focused solutions that can help you lead the way in generative evolution and create value for your business and customers. From finance, accounting, and procurement to HR recruitment and customer service, the Infosys BPM generative AI system can help you re-imagine your business operations while reinforcing AI ethics to give your customers a personalised experience.