The B2B e-commerce trends 2020 study by Magento shows that 75% of buyers purchase from the same supplier again if they had excellent omnichannel capabilities; 45% of customers believe that retailers don't spend enough effort on delivering multichannel experience; and 61% state they are not able to switch channels due to the valuable support services (or the lack thereof on other available channels).
The clients’ demand for omnichannel capabilities is driven by their wish to use familiar communication tools. If they use a particular messenger in their working environment, they wish to have all their procurement talks in the same messenger. If they deal with multiple suppliers, they want all these suppliers to use similar communication tools. To be close to their client and build strong customer relationships, a B2B enterprise must provide a selection of communication channels to choose from at each phase of the B2B relations. Michelle D. Steward, et al., point in their paper on B2B buying process evolution:
'Understanding when and why potential customers interact with an omnichannel experience better enables the supplier to understand what information might be helpful to a customer at which time during the buying process. Potential customers may enter one channel, for example, before a need and budget for that need is fully determined in an effort to keep up with industry trends. Then later in the buying process, a potential customer may wish to pick up on that exploration in a different channel, without loss of the insights gained in the earlier search.'
Regarding B2B chatbots, there are two omnichannel aspects:
The first aspect is obvious: people want more familiar channels, and a chatbot may serve as one. Businesses cite a lack of resources and technical expertise as the reason for the lack of omnichannel support; well, a chatbot is relatively easy to deploy.
The second aspect shows an AI chatbot as a content generation and processing tool, not just a simple messenger text interface. An omnichannel AI chatbot utilizes different communication methods, depending on the message type and urgency. Some content is better suited for an unhurried reading from a computer; an e-mail is an ideal carrier for it. Some messages need to be pushed into the client's phone: for example, they forgot to place an order before the national holidays. In some cases, such a bot may even prepare a customized web page for the client's perusal. In all these scenarios, the bot still works on a deep personalization level, knows the customer's history, needs, habits, speaks their language and predicts their wishes.
But can such AI contraptions be categorized as 'chatbots'? Will they still remain 'chatbots' once they enter the AR field, for example? Well, who knows? The term 'customer's virtual assistant' is used in some publications. But, as stated earlier, the technology itself is undergoing such a rapid evolution, that coining the right term may be a bit premature, so let's stick with 'chatbots' for the time being.