September 30, 2023

Spif Panel

Think Shopping & Women

It’s time to take chatbots out of the box

4 min read

Nilay Oza, CEO of Klevu, reveals how conversational AI can help brands free their chatbots to initiate more human-like interactions and build more positive two-way customer experiences.

The U.S. consumer is curious. They want to know more about products and companies before they buy. But all too often their in-app and on-site searches end in irrelevant products and information. And, if they choose the chatbot route, they get caught in basic Q&A scenarios that end in irrelevant and circular conversations that sap their time and leave them feeling annoyed. Which isn’t conducive to making a sale.

With 70% of customer conversations expected to be handled by AI-powered chatbots in 2023, it pays online retailers and e-commerce brands to get interactions right. Yet for many consumers automated chatbots are a source of disappointment. A recent study suggests that 80% of consumers believe chatbots increase their frustration and 72% feel that using them for customer service was a waste of time.

So why are so many bots turning bad?

A chatbot is a computer program that’s designed to automatically simulate interactions. Its conversations are governed by a set of predefined conditions, triggers and/or events around an online shopper’s buying journey.
However, if the rules are too simple or rigid, they effectively box the bot in, locking its logic into a conversation that leads to a dead end.

Most chatbots on the market today are governed by limited rules. By failing to establish a meaningful dialogue with the customer, it misses the opportunity to assist, problem solve or aid product discovery, rendering it — the shopper’s time and the merchant’s investment — ineffective.

Smart tech helps smash the rules

Now imagine what would happen if the chatbot could ‘think’ beyond its confines. If it could use its own intelligence to shape every potential sales interaction, connecting the dots between past experiences to deliver more positive outcomes for future ones. And do all this without any additional programming, rules setting or recalibration. Basically, we are talking about bots that learn through interacting — just like people.

Thanks to the latest AI this is no longer a pipe dream but a soon-to-be reality for retailers. Open AI and Chat GPT are already taking the world by storm. Commercial organizations are awash with excitement about how machine learning technologies can augment human abilities. At the same time, we can now purchase through voice-activated devices at home or via app-based chatbots on the smartphone, adding ‘Alexa’ and ‘Siri’ to our list of shopping ‘buddies’.

The same tech can take chatbot thinking out of the box — smashing the constraints of current rules engines and enable them to ‘freely associate’ language and context. Rather than repeating commands or bombarding shoppers with suggestions that confuse them more, these new smarter bots will cultivate a meaningful dialogue using their own logic to discern rather than guess what customers really want.

How to transform dumb bots into two-way ‘chat’ bots

So what does it take to deliver an intelligent conversational interface that understands shoppers’ questions or statements, allowing them to express their intent naturally?

Here are some things to look for:

  • Search overlays that allow shoppers to toggle between chatbots and search experiences. Shoppers already use the search bar on a website to get more and more specific each time they search for something.
  • Context analysis which can understand how a shopper’s current conversation and past behavior relates to the website context and use this to provide a hyper-tailored response.
  • Questioning skills that use semantics and natural language processing instead of pre-set rules and scripts, to ask more targeted and precise questions.
  • Text summarisation the ability to process large amounts of conversation and site behavior data to summarize shopper ‘play-back’ and garner more information.
  • Sentiment analysis tools that automatically assess how customers feel about certain products or services and make better suggestions and recommendations tailored to the active conversation.

It’s time to humanise how bots chat

Advanced AI functionality that goes further than traditional keyword searches by asking smart follow up questions that are tailored to each individual customer, will help close the current virtual/physical divide.

It will allow virtual stores to recreate real the real-life sales assistant in the digital world by helping them to:

  • Deliver even more personalized experiences at high intent moments.
  • Garner deeper conversational insight for more accurate content curation.
  • Better identify high-value customers and target with personal and preferential treatment.
  • Streamline and prioritize prospects with high intent to secure more sales.
  • Do the heavy lifting to qualify sales leads 24/7 and best optimize people resources.
  • Offer human-like support with powerful empathy that puts brands out in front.
  • Better guide customers to products and services they will love.

Curiosity will save the chatbot

In an ideal world, the chatbot provides a seamless and convenient e-commerce experience where the customer can complete all the stages of a purchase without navigating multiple websites or speaking to a customer service rep. Saving time, reducing abandonment and frustration, and improving the overall shopping experience with minimal use of merchant resource.

With next generation chatbot tech, there’s now no reason why websites and apps can’t deliver a personal one-to-one service that rivals the in-store experience. By making their chatbots more curious they can empower even the most indecisive shoppers to find what they’re looking for quickly, leading to improved conversion rates and greater customer loyalty.

CEO and Co-founder Nilay Oza is an entrepreneur with expertise in developing innovative, machine-learning software. His passion is to make a difference through continuous learning driven software-led innovation. Nilay previously served as a Project Director at the University of Helsinki and as a Senior Research Scientist at VTT, the leading research and technology company in the Nordic region. He holds a PhD in Software and Business Engineering from the University of Hertfordshire.

Copyright @ | Newsphere by AF themes.