AI with Intelligent Automation (IA) is the secret sauce to conversational results

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AI with Intelligent Automation (IA) is the secret sauce to conversational results! 


Customer experience is now at the centre of modern business strategies. Such a customer-centric approach is growing in our times due to massive competition and options available to consumers. But how do brands create a competitive edge and offer an exceptional customer experience? 


AI allow us to hit that sweet spot and deliver impeccable sales as well as customer service. It enables consumers to get a hyper-personalized experience that is quick and efficient. 


When you consider it from a customer’s perspective, creating a better experience is all about simplification. Conversational AI can help simplify the entire consumer experience from product understanding to purchase and from post-sales services to customer claims.


But in order to simplify the process, we also need to look at the pre-existing data and make the best use of it.


Behind every great AI is a lot of data. 


The more data that’s available, the more training it will have and the better it will perform. There’s a clear correlation between the amount of data that is used to bootstrap an AI’s knowledge base and its accuracy in carrying on conversations with your customers correctly.  


To be accurate, data is the building block behind Conversation AI. Through the help of available data and patterns, AI defines the understanding of a customer’s message and looks for the desired information. 


Let’s take an example here.


Imagine that you're creating a virtual agent, and the virtual agent sits on a website or landing page.


The website is going to be connected to a tech stack such as a CRM, Marketing automation tool, etc. Systems that will give you insight into historical data, historical and real time actions of a customer.


To know more on how you can use messaging platforms to capture first party customer data - view our blog piece here. 


Maybe the user is on the returns page. Or they have added a product to the cart, or have just logged in - at each instance, they would want to talk about a different problem and have a different conversation. Several common scenarios may include:


  • I recently purchased a shirt but I received the wrong colour.


  • When will I get my package? I ordered a product from your site a few days ago!!


  • I tried to purchase a subscription for your platform. The amount is deducted but I still don’t have access. Help!


Now, they may connect with your sales assistants, who in return can recognize their phone number, understand what their previous interaction with the company was, and whether this conversation is likely to be relevant to a previous conversation.


If you smartly use the data that you already have on your customers, their data from their conversations, data on their preferences, based on previous customer interactions, or contextual, based on the actions that the customer has taken, then you're able to provide truly personalized, truly contextual AI assistance that is going to create a superior customer experience.


Why You Should Be Concerned With The Quality Of Data?


While the quantity and availability of data is a necessity to train a Machine Learning model, it is equally important to have accurate, precise, and useful data. 


Data that is inaccurately collected or extracted would make Conversational AI inefficient. As such poorly collected data can actually defeat the purpose of quick, efficient, and automated sales as well as customer support. Therefore any solution that we build with Machine Learning has to use a verified and accurate set of data in order to be useful and improvised over time.


Quality Data In Conversational AI can lead to numerous performance advantages:


  • Good quality data can allow Conversational AI to fulfill any customer requests or questions accurately, creating a better experience for them. In turn, it helps brands gain customer loyalty. A win-win situation, right?
  • Accurate data can allow you to be safe against false promises and inaccurate customer expectations.
  • Efficient Conversational AI solutions can provide you with an idea of consumer interest and frequent concerns. This can help businesses to gain feedback on where and how they can improvise. Lending results beyond the solution itself!
  • A Machine Learning models can improve over time if it is fed the right data. Much like a positive feedback loop, such a Conversational AI solution would get better over time.
  • Only high-quality data can give expected outcomes. Without a verified Conversational AI solution, there’s constant room for error and such a Machine Learning system must be supervised throughout the implementation.


In the end, it’s all about the right dataset.


Conversational AI carries great potential to transform the customer experience, and we might get to experience it commonly very soon. However, it is essential to understand that such a solution can only be beneficial to you if it is built upon the right dataset.



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