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5 Innovative Ways to Boost Customer Engagement with AI

5 Innovative Ways to Boost Customer Engagement with AI
Customer Engagement Solutions: 5 Ways to Use AI


Business leaders are always influenced by AI, which promises personalised and efficient interactions at every step of the customer journey. According to the Zendesk customer experience trends report, 57% of leaders plan to increase their AI investment by at least 25% over the next few years.

One research study also indicates that the growth rate of artificial intelligence will be around 33.2% between 2020 and 2027. Nowadays, companies are constantly seeking different ways to engage with their customers and increase sales. One innovative way to boost customer engagement solutions is generative AI, which uses machine learning and AI algorithms to help users generate unique experiences for each customer.

360 Degree Change in the Customer Experience with AI

Integrating AI into customer experience has led to a 360-degree transformation of various aspects of the customer journey. AI algorithms have the power to analyze how companies anticipate customer needs and trends, enabling proactive measures by optimizing inventory management.

We are already witnessing the successful journey of AI in multiple industries and fields. Let's talk about Tesla's autonomous cars, Google's digital assistant Siri, and Amazon's Alexa, which are the growing examples of AI.

However, if companies want AI-driven customer support, they need to find innovative ways to boost customer engagement.

5 Innovative Ways To Boost Customer Engagement With AI

Top 5 ways to boot customer Engagement with AI

1. Personalise your Customer Experiences

Personalising customer experience is the road to customer success and loyalty. Conversational AI can help companies to deliver personalised experiences at scale.

For example, Netflix’s personalised recommendations suggest movies and TV shows based on your viewing history, preferences, and ratings. This level of personalization keeps users engaged and helps them to discover content they might enjoy. Netflix estimates its recommendation system saves the company $ 1 billion per year in customer retention costs.

By analysing this data, companies can follow the following strategies to personalise customer engagement.

  • “Choose Wisely”: choose dynamic content on websites, marketing campaigns, and emails based on customer preferences and behaviour.

  • Address customers by their names and send relevant offers and updates based on their interests to give them a personalised feeling.

  • Predict customers’ needs to provide proactive support through AI-driven analytics and insights.

  • Design a feedback form and address the customer's concerns or suggestions promptly to show that their feedback is valued.

2. Provide quick resolutions

Pay close attention to the customer’s issues or concerns without any interruption. A HubSpot report shows that 90% of customers rate an immediate response as important when they have a customer service issue.

AI chatbots can automatically pull up the question and provide relevant information. They can also easily filter spam messages, ensuring agents don’t waste time on false tickets.

By demonstrating how businesses strategically implement quick resolutions to enhance customer satisfaction, follow the following strategies to provide quick resolutions.

  • Acknowledge the problem and express empathy towards the customer’s situation.

  • Give a sincere apology to the customer if there is a mistake or inconvenience.

  • Give one or more problem solutions to address the customer’s issue.

  • Take a follow-up with the customer to ensure their satisfaction and willingness to continue doing business.

3. Use sentiment analysis to analyse customer feedback

Sentiment analysis involves analysing text data to determine the sentiment expressed within it, such as whether it is positive, negative, or neutral. AI has the power of sentiment to analyse the tools that are capable of understanding emotions, attitudes, feelings, and opinions.

For example, in a social media sentiment analysis scenario, a retail company conducts a sentiment analysis of customer sentiment regarding its new product launch on social media comments. Salesforce found that 72% of consumers expect companies to understand their unique needs and expectations.  

Companies can follow the following strategies to provide customer feedback.

  • Gather customer feedback from various sources, like surveys, reviews, social media comments, and customer feedback.

  • Utilise natural language processing or machine learning techniques to classify the sentiment of each piece of feedback.

  • Compare the analysis over time or against competitors to benchmark performance and track improvements.

  • Quickly and easily identify the negative sentiment to get over the potential damage and resolve customer issues.

4. Enhance data analysis to understand customers

AI is the heart of real-time analysis. AI can quickly drive the user experience and can also act as important user information. Improved data analysis techniques offer businesses a powerful tool to get insights into customer behaviour, preferences, and needs.

For example, a subscription-based streaming service uses predictive analytics to forecast the rates among its subscriber base. According to McKinsey, companies that leverage predictive analytics outperform competitors by 20% in terms of revenue growth.

Businesses can gain actionable insights by leveraging data analysis to understand customers' techniques. Let's discuss some strategies and follow them.

  • Employ predictive analytics models to forecast future customer behaviour trends based on historical data and patterns.

  • Use behavioural analytic tools to track and analyse customer interactions with websites, digital platforms, and online stores.

  • Implement the power of machine learning and artificial intelligence algorithms.

5. Streamline Checkout Process

Streamlining the checkout process is challenging for improving customer engagement. A smooth checkout process helps to reduce the process and enhance the customer experience.

There are various kinds of checkout processes. Let us take a straightforward example: Spotify provides a streamlined single-page checkout process that allows customers to enter their billing, shaping, and payment information all on one page. The report of Baymard Institute shows that single-page checkout has been reduced to 50%.

Here are some strategies that can be discussed & follow

  • Allow customers to check as a guest rather than giving them the option to create an account.

  • Utilise the autofill feature to populate wherever possible.

  • Provide the CTA and make it easy for customers to edit or return to the previous page.

  • Regularly test and optimise the checkout process by doing A/B testing.


Integrating conversational AI offers an innovative avenue for elevating customer engagement strategies. By harnessing AI-powered recommendation engines, businesses can deliver hyper-personalised experiences, fostering deeper connections with customers through tailored product and content recommendations.

Through advanced recommendation algorithms, Splore offers specific pro suggestions, enhances relevance, and drives customer satisfaction. Additionally, AI-powered voice and visual search simplify the process by leveraging convenience and fostering deeper engagement.  

Do you want to boost customer engagement with AI, then what are you waiting for? Let us Connect Now!


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