29/01/2021

Are you tired of hearing about artificial intelligence (AI)? We wouldn’t be surprised if you are, considering the fact that pretty much every company nowadays manages to infuse AI into their value proposition. Whether they are a technology service provider or a simple grocery store, it seems that mysterious sentient robots are somehow part of the process.  Despite the flimsiness of many of these claims, there are some actual use cases, particularly within B2B Marketing and Sales, where AI can play a genuinely beneficial role. Specifically, conversational AI solutions have a number of valuable applications for enterprises to consider.

Conversational AI is a set of technologies that automates communication at scale through text or speech-based virtual assistants (also known as chatbots) to personalise the experience of prospective buyers and existing customers alike.

In this article, we’ll explore some of the opportunities for conversational AI to support B2B Marketing and Sales teams, to help grow your pipeline and concurrently increase conversions.

Data Gather and Lead Qualification

It’s never easy to turn a website visitor into a paying customer, however, deploying chatbots can help streamline lead routing systems and consequently decrease the sales cycle to grow conversions. 

A well-built conversational AI can ask the right questions to determine the type of products or services the lead is looking for, as well as gather valuable information and data points on the prospect. This can help lead grading and scoring to ensure the best leads are prioritised by the sales team. More advanced chatbots can even be used to determine these patterns automatically, ensuring no extra manual work is involved.

Furthermore, using this added data the sales team can narrow down the type of content and messaging that would best suit each lead, improving conversion success and the buying experience for any prospective customer. 

Customer Service 

Conversational AI can vastly increase customer response rates, giving immediate and personalised responses to most issues at any hour. Not only is human error minimised, but human operators are able to focus on more complicated issues where manual interference is needed. 

Concurrently, through the use of machine learning, chatbots improve their responses over time, optimising the process in the long-term.

With the wide variety of chatbot providers available to choose from, the costs of supporting a customer service system with conversational AI is strikingly low, especially when compared to hiring extra personnel. This is further compounded when considering that Conversational AI can be implemented to respond to any language, removing the necessity to hire extra customer service agents for new regions. 

Supporting Omnichannel Approaches

Marketing communication is constantly expanding to include new channels to engage with potential prospects while simultaneously maintaining a coherent buying experience. Whether the channel is email, social media, phone or chat, all experiences need to remain integrated. This is corroborated by a study from Genesys, that found that 83% of consumers have confirmed that they want the option to move between channels when interacting with companies. Despite this, only 50% of companies have installed the necessary capabilities to provide these omnichannel experiences.

Through the data gathered with the implementation of chatbots, it becomes clearer when to reach customers on different channels, and how to communicate with leads at each touchpoint, while conjointly creating a more unified buying experience overall. 

Content Promotion 

Creating content such as articles, videos, ebooks, and webinars, can be a long and expensive process. Moreover, getting leads to actually read the content can be just as challenging, if not more. 

This is another area where conversational AI can bring notable results. Chatbots can greet visitors and answer their questions with videos or blog articles, and provide increasingly relevant content to repeat visitors. Through pattern recognition, AI can determine buyer preferences, employing sentiment analysis to determine the most appropriate marketing communications and personalising content for different stages of the sales funnel. 

Integrating with Robotic Process Automation 

Robotic Process Automation is the execution of repetitive manual tasks that were previously carried out by humans, across different applications by a machine. This can be used to process transactions, manipulate data, signal certain responses and communicate with other digital systems. 

RPA can be combined with conversational AI to manage the execution of business processes that arise from the human interactions realised by conversational AI. Essentially, RPA picks up where conversational AI leaves off, creating a more automated, consistent and personalised customer journey. In fact, Gartner predicts that by 2020, automation will decrease the need for employees in business service centres by 65%, which signals the merging of RPA and conversational AI.