Why Artificial Intelligence is Disrupting B2B Sales
Artificial Intelligence will revolutionize B2B sales.
AI is rapidly creeping its way into the software we use on a daily basis. Everything from CRM to Account Based Marketing (ABM) to marketing automation is getting “smarter.” The promise of AI powered systems to suggest qualified leads to a B2B sales person is very exciting.
One aspect of AI that is very exciting is its ability to tap into unstructured data to learn more about prospects as they engage with a brand’s digital channels. Examples of unstructured data include online engagement such as tweets, comments, likes, shares, etc.
Think about the potential for smarter systems to reduce much of the heavy lifting associated with identifying qualified sales opportunities.
Big Changes to B2B Sales Processes
As software continues to get smarter, we must also consider how the B2B sales person’s role and the sales process will change. The B2B sales professional must demonstrate in the long run that he/she can evolve and manage the new sales process, which will no longer be characterized as the sales process, but rather the buyer’s journey.
AI Will Flip the B2B Sales Process Upside Down
As AI technology becomes more readily available, it will change sales processes in mid to large enterprises. Consider that subject matter experts are employed throughout an organization. Traditionally, salespeople get assigned by geography, vertical industry or named accounts. As “leads” come in, they get assigned to a rep. However, in the future, AI will conduct “match making” by identifying internal SMEs who are “best fit” to follow up on leads.
This model will create a new sales culture that permeates across the entire business. SMEs across the company will “opt-in” to engage with prospective buyers. People who had not previously contributed directly to revenue producing activities will have the opportunity to participate. I anticipate a change in compensation plans to allow for more people across the business to participate in such revenue production activities.
The Role of the B2B Sales Person Will Change
The new B2B sales professional in an AI powered world will be part data scientist and part manager. She will be responsible for managing engagement between multiple prospective buyers and multiple internal SMEs. She’ll leverage analytics delivered through a dashboard-like interface. She’ll also use her management skills to navigate the complex intercommunications between prospects and SMEs.
Internal SMEs whose full-time jobs can range from customer care to analyst to engineer will leverage system-generated messaging – powered by AI of course – to enable engagement with prospects rapidly. In just a click or two, a personalized message from an SME will be delivered to a prospect that demonstrates relevancy and helpfulness. Here’s a potential scenario in the AI powered B2B selling eco-system.
An analyst is a member of a buying committee for a new enterprise system. He reads a technical blog post published by a vendor whose product is under consideration. He clicks on one of the links in the blog post to access more detail and opts in to download a spec sheet. The vendor’s system identifies two engineers who share common attributes with the analyst who downloaded the spec sheet. Such common attributes determined by the system might include recent activity on other blogs or social media, or an advanced degree from the same university as the two engineers, or any number of other common attributes, all of which are learned by the system.
One of the engineers accepts the “match” and reads a message that has been written by the AI powered system. Note, the message was not previously written by anyone. Deep learning and language processing technology is used to write a unique message by the system. The engineer accepts the message, but she chooses to make a minor edit before sending it. The highly-personalized message is sent to the analyst who downloaded the spec sheet.
Rather than getting a call or email from a sales person – who is far less likely to have something in common with this analyst – the system enabled a relevant match, followed by a highly-personalized message from someone who is far more relevant to the analyst.
Because the system is “smart” other possibilities include triggering yet another engagement from someone else that is like the analyst if the system doesn’t learn that a positive action occurred from the first outreach.
Meanwhile, the sales person is watching this through a dashboard-like interface. She is being told by the system where the buyer is in the journey – 27% or 39% or 78% – based on the productivity of the engagement activity.
The data science part of the sales person’s role is to monitor multiple scenarios like this. The management part is to orchestrate the process by making judgements on several variables. Similar to an airline pilot turning a nob to shift course, the sales person will make decisions to direct the system to engage other SMEs to aid the buyer’s journey.
The sales person must oversee the internal “match making” generated by AI powered systems, ultimately ensuring the prospect has a great experience with much emphasis on the buyer’s journey experience. She will also monitor the prospective buyer’s engagement with competitors and her management skills will enable her to determine next steps, including when she should insert herself into the conversation.
B2B AI Software in Action
The scenario described above is not sci-fi. It’s real. If it’s not available today, it’s months or quarters away, not years.
The following companies are a small sampling of those delivering AI powered systems in B2B marketing and sales.
Available Today for B2B Marketing and Sales
In B2B, Salesforce Einstein is the closest to delivering an experience as described above. It learns from your data and makes predictions and recommendations for customer engagement that can lead to more sales.
IBM Watson Commerce
IBM Watson Commerce uses AI for cognitive learning to deliver personalized, omni-channel experiences to give customers what they want, where and when they want it.
Demandbase DemandGraph uses AI to identify business behavior and relationships by understanding the digital footprint of web activity by businesses, including unstructured data across the web.
Scoop.it Content Director uses predictive insights to content that has a good probability of being useful to your buyer.
Ceralytics uses AI-powered content intelligence to identify content that has performed well in the past from your brand and from your competitors, so you can make decisions on the content you should produce with a higher probability of performing well.
The Nuance Customer Engagement platform provides conversion marketing through a smart live-chat agent to approach customers without being intrusive.
When Lithium acquired Klout, the online community and social media technology company was well positioned to branch out from its community roots to build a workflow publishing product targeted at social networks. “We could do that with our investment over the years on AI and machine learning behind Klout. That’s been our biggest move so far and we’ve already helped some great brands,” Lithium Technologies CEO, Rob Tarkoff said.
AI Software Watch List
While not considered a B2B force to reckon with, we cannot ignore the massive work underway on AI at Facebook through Facebook AI Research (FAIR). Facebook has been using AI in the user experience for some time. Look for Facebook to one day encroach on B2B tech leaders such as Salesforce.
At the time of this writing, Microsoft’s primary AI offering is focused on voice recognition via Cortana and chatbots. In September 2016, Microsoft announced creation of a new AI and Research Group. An excerpted quote from Microsoft CEO, Satya Nadella says…”We are focused on empowering both people and organizations by democratizing access to intelligence to help solve our most pressing challenges. To do this, we are infusing AI into everything we deliver across our computing platforms and experiences.”
What About LinkedIn?
Likewise, at the time of this writing most of what is known about LinkedIn’s AI endeavors is tied to their Talent Solutions division which has delivered more than 60% of their revenues. LinkedIn’s Vice President of Engineering, Deepak Agarwal says “Data is our biggest asset. Without AI and machine learning, you’re not going to be able to surface the right insights to the right users and customers.” Considering that Microsoft now owns LinkedIn, I anticipate seeing more AI integrated into their offerings in the coming months and years to come.
A Crowded AI Sales and Marketing Tech Market
The list of technology companies harnessing AI is long. Oracle is in the game with Oracle Adaptive Intelligent Applications. SAP is also telling their AI story with SAP S/4HANA. The growing list of well-funded AI startups is also growing at a dizzying pace.
What You Should Do Now about AI in B2B Sales
If you’re focused on this quarter and next quarter, go ahead and ignore this blog post. However, if you’re focused on navigating the next two years, the advice we’re giving our clients is to dip your toe in the water with AI. No need to dive in head first. Start out by harnessing AI technology to develop a more effective content marketing plan that will deliver improved sales leads.
In the meantime, keep an eye on these companies and others that get on your radar with AI powered marketing and sales technology. Ground yourself in the reality that AI is not going away. Many have said that AI is the biggest thing in technology EVER – even bigger than the Internet!
If you’re a B2B marketer and you want to understand how to use AI in your digital strategy, schedule a 30 minute call with me. This is a consultative call. Be sure to outline (bullets) your current marketing strategy, how your sales team is organized (bullets) and your questions (bullets) about how to dip your toes in the water with AI powered tech.
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