5 Ways to Increase Customer Engagement using Artificial Intelligence (AI)

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The AI market is growing at a rapid rate, with experts claiming that it will snowball to reach a market value of $190.61 billion by 2025. Research also indicates that the forecasted AI annual growth rate will reach 33.2% between 2020 and 2027.

And if you think that AI is primarily being used to drive innovation in the technological space, think again. As per data, the most prominent use case for AI in the retail industry is for customer engagement, which makes use of AI-powered chatbots, predictive behavior analysis, hyper-personalization, etc., to deliver a superior experience to customers. Furthermore, a staggering 80% of marketers in 2020 were already seen deploying chatbots as part of their customer experience strategy.

Clearly, not using AI to supercharge your customer engagement efforts is a big mistake. In this blog, we will deep-dive to understand how you can use AI to improve your customer engagement efforts strategically and organically. Let’s jump right in.

Top-5 Strategies to Boost Customer Engagement using AI

1. Use AI as powerful customer service (CX) assistants

Artificial intelligence is paving the way for ‘smart’ virtual CX agents. The brand has integrated an AI-powered chatbot into its advertisements to encourage users to ask questions about their trip or simply share their experiences. To effectively address the user’s pain points, the chatbot browses through the Emirates Vacations’ inventory as well as combs through content on relevant sites to ultimately recommend personalized vacations packages and destinations. As you can imagine, this improves customer engagement ten-fold. That’s the power of AI, in short.

2. Use sentiment analysis to analyze customer feedback

If you think AI’s capabilities are restricted to answering straightforward questions that users pose, think again. Today, you already have a plethora of sentiment analysis tools that are capable of understanding a user’s intent, emotions, attitudes, opinions, and well, sentiments.

Alternatively, you can also conduct sentiment analysis on any kind of customer feedback you receive via open-ended surveys, emails, etc.

In cases where you have the customer elaborating on their experience, you can analyze their sentiments and feedback and tie it to specific features of your product. In other words, you can directly tie the user feedback to your product/service, and understand what’s working for your target audience and what’s not.

As an added advantage, you can eventually do a sentiment analysis of previous NPS surveys and compare the results to see how your user’s sentiments towards your product have changed over time.

3. AI chatbots have come of age, empowering self-service like never before

As mentioned earlier, AI-driven chatbots are becoming more and more advanced in terms of the features they’re offering. Plus, these bots offer immediate and 24×7 assistance to customers, without the latter having to wait to get help. The chatbots can offer answers to common FAQ-type questions, provide important information relating to an order, assist in providing a productive shopping experience, among other things.

The bot guides users on the Checkout page and provides users with critical information such as booking confirmation, check-in notification, boarding pass details, flight status updates, etc. The result?

  • By integrating the chatbot, the brand has witnessed a 40% increase in the volume of Facebook messages.
  • The chatbot can effectively handle over 16,000 customer interactions weekly.
  • According to estimates, over 1.7 million messages have been sent on Messenger by over 500,000 people

All in all, the travel bot is able to boost customer engagement by providing a host of business use cases–from resolving user queries to initiating transactions. Plus, it allows your customer service team to handle more complex problems and tasks that demand creative problem-solving and a literal sense of ‘human touch.’ Finally, the bot can also collect critical user information such as purchase history, likes, dislikes, friction-points, etc. to personalize the customer experience from start to finish.

4. AI-powered chatbots can drive personalization

Tying back to the previous point, AI-powered chatbots have become somewhat of an authority on driving a hyper-personalized user experience. Since the chatbots are constantly gathering user data in real-time, they can analyze the information and extract actionable insights and help create an in-depth user persona.

Retail giant H&M understands the importance of using chatbots to drive the Gen Z and millennials, and literally speak to its target audience in the latter’s preferred language and medium of communication–text.

The chatbot is perfectly capable of driving two-way communication, asking the user relevant questions so that it can provide relevant and custom-made suggestions. Naturally, this can improve the quality of the interaction and boost user engagement through the roof.

5. Leverage improved data analysis to understand customers

At the heart of powerful AI lies real-time data analysis. While AI can drive a seamless user experience, it can also act as a treasure trove of important user information. This data can further be used to improve the customer experience and provide users with tailor-made suggestions.

As customers keep feeding data into the app, the chatbot keeps collecting user data, which can further be used to personalize other forms of marketing communication (think: emails, text, etc.).

Long story short, AI allows brands to better understand the customer, preempt their needs, and wants, and ultimately, provide a personalized user experience–all of which can boost the customer engagement rates and lead to a happy, more loyal user base.

The Takeaway

Did you know that for around 40% of businesses, customer experience is the top motivator for using artificial intelligence?

The writing is on the wall: Artificial intelligence is no longer restricted to resolving customer support requests. If used correctly, it can lessen your team’s workload and provide a consistent, seamless, and customized user experience. It can not only drive reactive customer support but a proactive one. It can not only address user needs but preempt them. It can not only drive brand awareness but also build long-term user loyalty. Moreover, these AI platforms offer instant service, without making customers wait, making it a win-win for all. Agree?

1 COMMENT

  1. Hi Revanth: Thank you for your article and I agree with you that “Artificial intelligence is no longer restricted to resolving customer support requests. If used correctly, it can lessen your team’s workload and provide a consistent, seamless, and customized user experience.”

    However, the security of data storage is so fragile. For example, 3 billion Yahoo accounts leaked in 2013, 700 million LinkedIn users leaked in 2021, and 533 million Facebook users leaked in 2019. All the victims received were only apologies from these digital giants.

    Even if the data stored in the world’s most secure technology giant may be stolen, how can customers ensure that their data is safe?

    In 2006, Clive Humby the famous UK mathematician coined the phrase “Data is the new oil.” Business people now generally use the phrase “data is the new currency.”

    There is no doubt that data has its value, especially customer data. When a customer allows the company to use his/her data, the ownership of the data is still the customer, not the company.

    When a company leaks customer data, should the company directly compensate the customer instead of paying a fine to any other organization or entity? Considering that the customer data of so many large companies and digital giants has been leaked, should a mechanism/pricing structure be established to directly compensate for the loss of customer data?

    If there is no compensation to the customer, how can the customer comfortably let any company do any personalized things for them? This is unfair and unjust. Remember: customers own their data and the data has value, not to mention the tremendous value generated by improved AI data analysis.

    I would love to hear your thoughts.

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