DIGITAL INTERACTIVE SERVICES
How AI is personalising digital interactive experiences?
In the ever-evolving digital landscape, businesses are turning to Artificial Intelligence (AI) to revolutionise user engagement, and AI-based personalisation is at the forefront of this transformation. It is reshaping the way users interact with digital platforms and services.
As per the Forbes Advisor survey, 73% of businesses plan or use AI-powered chatbots for messages, 61% of companies optimise emails with AI, and 55% utilise AI for personalisation, including recommending products.
Therefore, understanding the dynamic world of AI-powered personalisation and its profound impact on creating personalised website experiences is of utmost importance.
How AI personalisation improves digital engagement?
AI-based personalisation involves machine learning algorithms that analyse user data and behaviour and deliver customised content recommendations and interactions based on individual user profiles. Here are a few examples of AI personalising digital interactive experiences:
Tailoring content and recommendations
AI tools can analyse user preferences, browsing history, and interactions to deliver content and suggestions that align with individual interests. For example, Netflix’s AI and ML algorithms pick up on nuances and threads in the content a user consumes to curate film and show recommendations for each user.
Dynamic user interfaces
AI platforms powered by machine learning (ML) algorithms can adapt user interfaces based on user behaviour, preferences, and context. The arrangement of elements, choice of colours, and how content is positioned can be flexibly modified to craft a smooth and user-friendly experience. With dynamic website personalisation, it offers personalised website experiences.
AI-based personalisation for e-commerce
E-commerce is one of the most popular and competitive domains for AI-based personalisation because it involves several customers, products, and transactions that generate a lot of data. AI-based personalisation can help e-commerce businesses understand their customer’s preferences and behaviours and provide them with relevant and tailored products. A survey by Statista found that 70% of e-commerce decision-makers in North America and Europe believed AI would help their business with personalisation in 2021.
Natural Language Processing (NLP) for conversational interactions
NLP, a building block of AI, enables casual interactions between users and digital platforms. Chatbots and virtual assistants powered by NLP can understand user queries and provide relevant responses. For example, Siri uses NLP to answer user questions and perform tasks. Domino’s Pizza uses NLP to allow users to order pizza via voice or text.
Use cases of personalisation with AI
AI personalisation revolutionises business outcomes with custom content and design. It enables businesses to boost engagement and conversions. Let’s see a few cases about how AI personalisation impacts deliveries.
- Product recommendation
- Dynamic pricing
- Dynamic websites
AI tools can analyse user data, such as browsing history, purchase history, preferences, and feedback, to recommend products that match the needs of customers and interests. For example, Amazon uses AI to provide personalised product recommendations based on each user’s shopping behaviour.
AI tools also can help businesses adjust the prices of their products or services based on various factors, such as demand, supply, seasonality, customer behaviour, and competition. One example is Uber, which uses AI to dynamically change the fares of its rides based on the demand and supply of drivers and riders .
AI tools help businesses customise their websites for each user based on their data and preferences. Intellimize uses AI to optimise the layout, design, and content of websites for each visitor and provides a personalised website experience.
AI-based personalisation: Benefits and challenges
In the dynamic landscape of AI-driven personalisation, the benefits of AI-powered personalisation make it a compelling avenue for businesses to explore and flourish. Nevertheless, significant challenges warrant attention from both users and businesses.
Benefits
- AI-based personalisation provides customised and relevant digital interactions that enhance the user experience and improve business performance.
- AI-based personalisation also increases conversion rates, revenue, and customer lifetime value by delivering personalised offers and incentives.
- AI-based personalisation generates data-driven insights into customer behaviour and preferences. This helps businesses to optimise their strategies and build stronger relationships with customers.
Challenges
- AI-based personalisation requires collecting and analysing large amounts of customer data, which raises concerns about data privacy and security.
- AI-based personalisation may affect user trust and control over their digital interactions, as users may not understand how or why AI makes certain decisions or recommendations.
- AI-based personalisation may introduce bias or unfairness in digital interactions, as AI algorithms may reflect the biases or errors of the data or developers that train them.
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How can Infosys BPM help?
Digital content as a service at Infosys BPM focus on providing a tool-agnostic and process-centric approach across various domains, such as content management and creative design, to transform digital business outcomes.
