The conversational commerce market will touch $13.9 billion by 2025, hitting a 3x mark in a matter of 5 years. Such rapid growth means a growing demand for conversational commerce technologies and a wide range of use-cases.
The term ‘conversational commerce,’ originally coined by Chris Messina in 2015, focused only on the intersection of messaging and eCommerce. However, as the technology has found new backers and takers around the globe, it has evolved into a larger ecosystem of platforms and services that offer solutions in the form of conversational AI systems that can help in providing an interactive layer to eCommerce.
4 Common Conversational Commerce Use Cases
1. Zest Money Addresses 43% More Queries with 66% Lesser Resources.
Zest Money is one of India’s leading NBFCs, which already has an active customer base. The company had a team of 120 customer support executives handling over 3500-4000 queries in a day. The resource and a load of queries were not optimally matched, resulting in a lack of intelligence around each query. At their productive best, agents were able to just resolve the query – without any focusing on acquiring customer intelligence.
The company then implemented an omnichannel solution focusing on the website and using the WhatsApp for Business API. The company ensured a seamless integration between a conversational chatbot for handling most of the redundant queries and a Live Chat functionality, largely for idiosyncratic queries that require human intervention.
With the conversational commerce platform in place, Zest Money was able to use the same system of conversational AI for both query resolution and minimizing loan defaults. The bot was able to send automated reminders to borrowers, prompting them to pay the upcoming EMI and avoid the penalties, just a few days before the EMI would be due.
Within the next 90 days of implementation, as India started witnessing more cases of COVID and the entire business ecosystem, including the human agents, got disrupted, Zest Money and its conversational commerce system was able to resolve over 5000 queries in a day, with the help of just 40 agents. The query resolution time further went down by about 75% and reached 2-3 minutes.
2. Domino’s India Augments Customer Experience and Reduced Load on Agents with an Omnichannel Digital Assistant.
Domino’s is one of India’s most recognized food brands, having a strong footprint across the physical outlet and delivery segments. As a result, the company is also prone to dealing with a high number of customer queries. For a long time, Domino’s India had accepted orders on the phone and deployed human agents to increase customer queries. That strategy needed a dash of conversational commerce to unlock value for the customers and provide the company with better economics per query.
With the help of an intelligent conversational commerce platform, Domino’s provided a unique multi-channel experience to its customers. The Domino’s Virtual Assistant was launched across four channels – the website, the brand’s dedicated app, IVR system, and WhatsApp. Since the brand has a presence across India, the conversational platform had to support three languages for maximizing interaction approachability.
The platform was primarily designed to augment customer experience and increase agent productivity. It ended up becoming one of the central elements in the brand’s entire customer experience value-chain. The conversational platform was also able to lead by notifying the customers about the nearest stores and updated offers to keep engagement high.
At the end of each consumption cycle, the same conversational platform was able to collect feedback from the customers and aggregate insights on the product, delivery operations, and customer interaction efficacy.
3. Purvankara Reduces Redundant Queries for Sales Team by 70% Using A Chatbot.
The Purvankara Group is one of the most recognized real estate brands with an extensive presence in India, the UK, and the UAE. The conglomerate has been operating for over 45 years and has a land bank of 125 million square feet. The company, being a firm with a global presence in a high-value product & service category, was also dealing with a range of problems in terms of customer interactions. It had to generate new leads almost consistently. Its customer service agents had to manage repetitive queries, which came across multiple channels and made it extremely difficult for them to track. Lastly, the turnaround times were clearly becoming a challenge.
The company wanted to implement a conversation commerce solution that would allow it to offer standardized and streamlined offerings across different touchpoints and still provide a personalized experience at scale.
Finally, the company deployed an end-to-end conversation commerce suite of products. Leveraging the WhatsApp for Business API, the chatbot was able to recognize the lead’s first name from Facebook and use it to provide a personalized communication experience. With this, the chatbot is able to send information on qualified leads to the project managers.
Plus, the platform supported a seamless change to Live Agent Chat as well as Video & Voice Calling, since it allowed qualified leads to get more personalized details about the project along with a human touch exactly where it is necessary – just a little before the conversion.
The chatbot was already trained on 25 most commonly asked FAQs and was able to provide conversational responses to each one of them. It was also seamlessly integrated with Salesforce CRM to create a structured approach for lead management.
At the end of the implementation cycle, the chatbot was able to take care of 70% of customer queries, which were largely redundant and earlier used to consume the enterprise’s resources.
4. United Bank of Africa Gets 1 million global users in 1 year of launching ‘Leo.’
Banks tend to have a very varied set of consumers, who are now seeking services and advisory from the chatbots instead of just the query resolution. Hence, the focus on conversational commerce is helping banks and NBFCs globally focus on a comprehensive and value-creating experience instead of producing interfaces that are optimized only for transactions.
United Bank of Africa launched its chatbot called ‘Leo’ in 2018. The idea was to provide a standardized and interactive experience to its users without making the chatbot sound ‘programmed’ for each response. The bank knew that the chatbot would have to deal with a diversified range of queries, focusing on products, transactions, requests, and other services.
Leo now provides 15 different services via its conversational interface and is integrated with Facebook Messenger, WhatsApp, and Apple Business Chat. It is helping customers open accounts, transfer capital, and even request loans. In just a span of one year, Leo was able to garner 1 million users spread across 14 countries.
The above-shown conversational commerce use cases are just the beginning of how businesses can augment the capabilities across different touchpoints in their customer interactions. Chatbot service providers tend to focus on the commoditized features of their chatbots. Many such bots are available online, for free.
A conversational commerce platform will help you generate more value with each customer interaction. With Yellow.ai’s Cognitive Engagement Cloud, you can match the results of virtually any of these use cases as 3/4th of them were actually engineered and implanted by the team at Yellow.ai. To know more about how the Yellow.ai AI-powered virtual assistant platform can help you generate more revenues with each customer interaction. Connect with us for more information