Will AI Replace Salespeople?

I bet AI will not replace salespeople. Read on, decide for yourself, and tell me what you think!

Let us look at the 4 fundamental stages of the sales process. Regardless of organizations’ varied approaches depending on whether they are small or large, B2B or B2C, transactional or relational, every sales process must have them all. You will, however, see each stage bleeding into the next and lines getting blurred.

I. PLANNING: Demand Generation

Generally defined as getting the initial awareness of your offering in the market and identifying prospects. The actions that may be mimicked by AI include:

Demand Discovery:

The more data and analytics you have put in here, the more confident you feel. This is the classic use case of AI engines when you have big data, but you might otherwise be better off using old-fashioned human analysis and strategy here.

Personalized targeting:

Netflix and Amazon’s use of collaborative filtering, etc. to tell us what to buy/watch next is probably what jumps to every person’s mind first. In B2B, Account Based Marketing is also witnessing the impact of AI tech. AI recommendation engines and chat-bots take the cake on execution here, but the fact is that they are simply mimicking what (good) salespeople have been doing for ages. Buyers will decide how quickly or slowly this shift to AI occurs by making overarching privacy choices.

II. STRIKING: Getting A Foot in The Door:

You have identified respondents for your targeting tactics, and you need to start a conversation with them. This is the stage where current AI offerings are most active. Core AI competencies in play here are NLP/NLU and advanced predictive and prescriptive analytics. Consider the following examples of B2B sales processes:

Lead Scoring and Prioritization:

What starts as simple rule-based scoring in the most basic cases can quickly become a complex statistical model. Models harness data from a wide variety of sources that only the most enterprising sales rep would have ever tracked, as well as impute its own data based on other behavioral models. Faster (real-time), pervasive, omnichannel-scient AI to score leads for a sales org to pursue makes sales more effective.

Up-Sell and Cross-Sell Recommendations:

If the above was prime ground for hunters, this is the bread and butter of farmers. With improvements in CRM data, platforms as well as 3rd party analytics, large organizations are well placed to take advantage of these recommendations.

Following up Assistance:

There are dozens of sales bots that will follow up with prospects and schedule interactions for reps. The likes of Conversica and x.ai have been making giant strides in this space. Some would even promise to qualify leads for you.

III. EXECUTING: Walking with the Customer Through Their Buying Journey

A common misconception is that salespeople operate as an individual tour-de-force at this stage, which largely involves speaking well. Very “sell me this pen”/ “sell ice to an Eskimo” sort of thing. That is very misguided. All but the most trivial of sales processes involve a large cross-functional team working together over a substantial period. The most enterprise sales process for a single deal can include many stakeholders such as Sales Director with several Account Managers, Account Marketing, Product Marketing, Finance, Legal, Operations, etc.  I am a big proponent of Guided Buying as the new sales normal, where the customer is in control and your influence as a salesperson is welcome. The other side of the coin is Guided Selling. When we look at the ecosystem surrounding each deal, the potential impact of AI just blows up.

  1. Sales managers and Ops can use predictive analytics AI to forecast and manage for revenue. New strides in prescriptive AI can also help course correct
  2. Finance, Ops and Sales can use AI for price and quote (CPQ) optimization
  3. Sales reps can use conversational AI for administrative work such as updating the CRM, keeping data clean, pulling out pertinent info using natural language. People.ai, tact.ai, etc. are popular solutions here.
  4. Sales playbooks can be created on the go, contextualized to the specifics of a deal (prescriptive AI)

The impact of AI technologies in these cases has far exceeded that of rule-based automation we were using 10 years ago. Check out BRiDGEfunnel for example. It targets points 1, 2, and most specifically 4, mentioned above in a hyper-contextualized manner to bring you the best in guided selling technology. It recognizes the need to address not just the What and How questions, but also Why to become your AI partner and not a black-box.

IV. CLOSING: Deal Closure and Customer Retention

In older times and erstwhile sales cultures, one would have ended with “Closing the deal”. My love for the subscription economy says otherwise. We need to make sure the customer continues to delight in our offering.

Monitoring and Engagement would be the most important AI actions at this stage. Omni-channel watch-tower predicts issues before they crop up and a recommendation engine helps plug these gaps. And chat-bots provide 24×7 customer service. Sufficient performance by AI to displace Sales.

Clearly, there is a lot going on in AI in Sales space, and a lot more yet to happen. But not every technology has the largest impact to make on how we sell today. When we start looking deeper into it, we realize what an early point we are at in this journey right now. Most of these technologies targeting sales execution and management are ahead of their times. So, what does that mean for you? As a user of AI in sales, it means that being an early adopter of these high impact technologies can bring in a huge competitive advantage to your team. And for your customers, it means that they can expect the right touch-points from you as a salesperson, enhancing their Guided Buying experience.

Author: Toshe Prasad

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