Having a great product or service is no longer enough for the customer. The global pandemic has led to a seismic change in people’s expectations of brands and purchase behavior. The proof is in the pudding:

One McKinsey global survey found that the COVID-19 pandemic pushed the digitization of customer and supply chain interactions by three to four years – in just a few months. It essentially translates to a focus on building better, digital-first interactions for customers.

Top trends in customer engagement revolve around:

  • Insights-led customer engagement strategies are key
  • Interactions with AI are evolving
  • Brands who can humanize their customer interactions will thrive
  • Personalized experiences are the way forward
  • An omnichannel experience is critical for customer engagement
  • Digital transformation is key to survival in 2022 and beyond

But what makes for good customer engagement? Again, market evidence says its speed, agility, convenience, consistency and a human touch. But, most importantly, its personalization. Customers want to feel like they matter. Every brand worldwide strives for the best customer experience, yet customers seem disappointed. Looks like it’s time to raise the bar.

Challenges in current customer engagement practices

Let’s face it, engaging today’s customers is not easy. They want absolute control of their purchase journey, of how, when, and where they make the purchasing decision. And the decision to choose one brand over another rests on engagement. A poor engagement can take growth metrics such as conversions, profit, brand retention, and loyalty down in minutes.

Customer engagement goes beyond identifying a customer’s needs and preferred touchpoints. It starts with understanding them and then offering solutions when they need them. It helps create connected and consistent customer journeys. Not an easy feat by any means, but if achieved, it can earn long term customers. Several challenges keep businesses from reaching this level, such as resources deficiency, lack of data & its management, inability to support global markets, fleeting customer attention, poor personalization and more. A frequent and repeatedly emerging trend is third-party data & cookies losing their reliability. This can be addressed by adopting conversational AI to gain first-hand data and analytics so that businesses can keep the focus on the personalization of their customer’s journey. In short, challenges of all shapes and sizes prevent businesses from gaining engaged customers.

How Conversational AI is Changing Customer Engagement

Conversational AI has directed customer engagement in a direction from where there’s no turning back. Customers are the bedrock of any business. And conversation is a primary tool to ensure their satisfaction. Research indicates that about 40% of internet users worldwide prefer interacting with chatbots to virtual agents. This means higher usage of conversational AI triggering not just major innovation and investment but the beginning of the end for those who ignore the inevitable. Says renowned futurist Gihan Perera, “in business, if you’re not engaging with AI, you’re going to get beaten; it’s that simple.”

For most CEOs, regardless of the size of their business, adopting transformative technology is always a top consideration. However, at times, it is slowed down by concerns about investment. Until COVID-19, that is. Conversational AI currently represents the top use of AI in enterprises. And why not? The majority of the global consumer market falls under the age group of 18-34 and are called AI Natives, people who have been interacting with Brands through conversational AI for most of their adult lives. The phenomenal rise and adoption of conversational AI is coming from a proportionate demand for a hyper-personalized, 24×7, smooth online experience by customers. This rise, according to Deloitte, is expected to almost double over the next two to five years. It says that interactive AI will soon be the standard for customer service.

Conversational AI is:

  • Building interfaces that enable near-human conversation
  • Enabling hyper-personalized and instant care that customers are getting used to
  • Collecting customer feedback on products and brands in real-time and in much larger quantities
  • Helping make better investments, sharpen customer targeting
  • Offer multilingual support to serve more customers
  • Earning customer loyalty
  • Increasing efficiency of enterprises by eliminating repetition and intelligent allocation of resources

Once a somewhat restricted concept, today conversational AI is for everyone, enterprises and customers alike. Thanks to increased democratization through a low code-no code model, even non-techies can immediately deploy and start using conversational AI in their businesses. Overall, conversational AI is becoming an asset of choice for businesses.

Conversational AI in the customer journey

Conversational AI is not restricted to just one place in the entire customer journey. It is omnipresent. Think of it like a running program in the background that always captures data, analyses, and learns about customers, their needs, preferences, biases, etc. Therefore, brands can offer the right solution packaged in the right way at the right time.
Conversational AI makes much sense today because it helps Brands not just convert leads but start right at the beginning of the entire customer journey – how people engage with them, what led customers to them, what factors are influencing the conversion, the relationship is formed, the time and platform preferred to make purchases and finally the decision to make a purchase.

Opus Research found that the average amount banks save per AI bot interaction is $0.60. JP Morgan saved more than 360,000 hours of labor using its chatbot to analyze complex back-end contracts quickly.

We’ll leave with a few Conversational AI use cases for some industries:

Conversational AI in the banking and Insurance sectors can automate mundane day-to-day tasks. As a result, the agents can concentrate on growing the brand. Here are few user cases-

  • 24/7 customer support.
  • Multilingual Conversational AI bots let the users easily interact in their own language and get their issues resolved quickly.
  • Contact and engage with the customers regarding the payment reminders, policy updates, and other actions that need customers’ knowledge.
  • Cross-sell and upsell products based on the user’s requirement.
  • Data-driven product recommendations for improving conversions.
  • Periodically engage with deep lapse renewal customers and improve conversion rate.

Another place where Conversational AI is creating a big impact is E-commerce and retail stores. Here are a few use cases-

  • Real-time, 24/7 support
  • Help customers with their orders, returns, and payments
  • Personalized product recommendations based on the user’s previous interactions
  • Help customers throughout the shopping journey.