Emerging tech to meet B2B buyer expectations 

It is estimated that the US alone will generate over $1.2 trillion in business to business  ecommerce sales by 2021. With a market of that  size, B2B organizations need to  start planning now as to how they’ll  compete for a piece of that trillion-dollar share.   In order to compete, companies must differentiate – and that comes down to the customer experiences they deliver.  

B2B buyers want  the same digital commerce  experiences they are receiving on B2C channels.   

Here are three emerging tech trends B2B organizations need to include in their 2019 plans if they want even a sliver of the B2B ecommerce market in 2021.   

Mobile  

B2B buyers are spending more time on mobile devices, both personally and professionally.  Plus, the workforce is getting younger with more technologically savvy employees who will  expect the  ease of use via a mobile device in B2B.

Anheuser-Busch, an American brewing company, is capitalizing on mobile very well with their B2B  mobile app  offering,  Tapwiser.  Tapwiser allows for a simpler path to purchase by enabling quick order submission via the app instead of with a sales rep. Anheuser-Busch also allows for on-demand delivery service with the Bud Light Button, a one-tap beer delivery app.

Artificial  Intelligence  (AI)  

The rise of artificial intelligence in the workforce to support and accelerate processes is rapidly unfolding.  AI allows for better automation and the use of predictive insights deliver smoother transactions and better personalization for B2B customers.  

Hill & Markes, a distributor based in upstate New York, had an inundated call center until they took advantage of AI. They launched the AI-powered messaging platform, LivePerson, to communicate with their B2B buyers online and in real-time. The AI solution empowers customer service reps with conversational marketing tools to cross-sell or upsell when inventory is out of stock.  

Machine  Learning  (ML)  

A subset of the AI phenomenon, machine learning allows for a streamlined approach to account management. ML allows organizations to utilize past and present customer data to project future behavior and commerce trends. ML can monitor customers better by delivering stronger data on who the customers are and what they want, when they want it.   

Although this is more of a B2C use case, there is a lot to be learned from Mazda and how they utilized machine learning for a new car campaign.  

The ML technology crawled across various social media networks, searching for the right people via their posts with the right preset indicators (content) to be selected for a promotion during SXSW. Mazda was then able to locate who the key influencers were to include in their new car promotion at the event.  

B2B organizations can learn from this data-centric approach and how Mazda was able to personalize content to better engage with a very specific crowd vs a general audience segment. Investing in ML will give B2B organizations the data and opportunity to  better understand their  buyer persona.