Conversational AI Solution Series
Who is Jane Smith? Jane is a New York-based lawyer who lives in the middle-income neighborhood of Queens. She is an American earning an average annual income of $74,664 before taxes. She uses cash and her debit card to pay her bills.
Her bank has recently launched a conversational AI app and she is curious to experience conversing with an AI chatbot. As a sensible spender, she uses the Spend Analyzer through her bank’s app to get a glimpse of her spending in the previous month of November. In this post, you will get a snapshot of their conversation.
In this 3 part Conversational AI Solution series, we will discuss AI-powered solutions using live conversations between a conversational AI chatbot and customers.
• The 1st part of the series we will cover Smart Discovery, Smart Recommendations, and Smart Conversion solutions useful to upsell banking products and services.
• The 2nd part of the series will cover Smart Conversion solutions useful in cross-selling.
• The 3rd part of the series will cover Smart Transactional Recommendations useful in enhancing the customer experience (CX).
How conversational AI bots understand and assist customers better
The AI bot of Jane’s bank instantly provides Jane with a snapshot of her spending habits, it also gives specific results as requested. The AI chatbot, pre-built with machine learning models, processes unstructured data into structured data based on specific requests. This is how Smart Discovery helps to deliver the best customer experience:
•Responds and resolves in real-time – The AI chatbot provides ‘first call’ resolution and responds to customer queries and requests in real-time.
•Allows customer service teams to focus on strategic aspects – By handling up to 30% of support inquiries, AI chatbots give customer service teams time to focus on aspects such as customization and personalization.
While processing unstructured data at lightning speed is a smart feature, there is nothing genius about it. If you think an AI chatbot is capable of only so much, think again.
How conversational AI bots give customers what they need before they ask for it
What the AI bot does here is that it uses ‘deep learning’ and artificial neural networks to emulate the functions of the human brain, conduct predictive analytics and provide smart recommendations.
In the conversation with Jane, the AI chatbot observes her high travel spend in the month. Using ‘deep learning’ techniques, the bot recognizes Jane’s need for a travel credit card that would help her to save money and earn reward points.By making a recommendation, the bot intelligently offers Jane a product that she possibly needs but didn’t know about.
How conversational AI bots help close the deal with ease
A sale is never complete unless it’s signed on the dotted line. More often than not, the opportunities to upsell when handling customer queries is lost. Moreover, the time-consuming paperwork to be submitted to attain any banking product usually dissuades customers from signing on the dotted line. AI bots guide the customer to ensure forms are filled and documents are uploaded ensuring a smooth transition between phone apps to website applications.
In Jane’s example, the AI chatbot simplifies the credit card application process.If you observe in their conversation, once Jane chooses to upload documents, she is directed to a website app and the AI bot continues their conversation through the website application, therefore ensuring an omnichannel experience.
Using Intelligent Navigation, the bot is able to guide her through filling the form and uploading documents. The AI application uses optical character recognition (OCR) to scan and verify uploaded documents. A conversational AI chatbot not only identifies opportunities to upsell it makes sure the process to complete the sale is made as convenient as possible for the customer.
Crank it Up a Notch! Progressive Banks Use Conversational AI Bots to Upsell
With the onset of AI technology adoption in the banking sector, traditional banks need to switch gears. Nimble banks using AI banking technology are able to adopt an ‘AI Analytics first’ approach. Using elite analytics to create exceptional experiences, data scientists can facilitate data-driven marketing and streamline marketing initiatives. With the focus on predictive analytics, banks can understand their customers better and design customer-centric products. Similar to Jane’s example, banks can also identify opportunities to upsell using Smart Discovery, Smart Recommendations, and Smart Conversion solutions.