Sales Intelligence with AI

Sales insights, delivered by artificial intelligence, allows sales professionals to develop trust and build relationships by being in the know.

How does artificial intelligence change sales intelligence?

Artificial Intelligence is changing almost every aspect of the corporate landscape.  Jobs that were common are being eliminated, fractured, or changed to an unrecognizable state.  Anyone who is not seriously contemplating the future of their discipline in an AI-led world may be in for some uncomfortable shocks.  With that in mind, let’s look at the evolving role of sales intelligence in a world driven and enabled by AI.

It’s important to remember that Artificial Intelligence is only good at certain tasks, rather than entire job categories.  This means that most jobs are due for significant change rather than elimination as AI will fundamentally change key aspects of the job, but leave others in place or even elevate their importance.  Sales intelligence is definitely an area that is due for massive change and evolution, but not replacement in its entirety.

Value of Sales Intelligence

At a first glance, the value of sales intelligence seems obvious. It’s difficult or impossible to sell to a person or organization without knowing about who they are and what they focus on.  However, on closer inspection, in today’s era, the basic facts are too readily available to count as intelligence at all.  A quick search or a visit to the company’s website will usually provide the basics of what you need to know.  However, these basic facts usually don’t provide anything useful to work with as a sales person.

The litmus test of sales intelligence is its ability to enable a sales professional to sell better.  This can be better access to new accounts, better positioning of solutions against pain points, better price optimization, or better ability to navigate a deal towards close.  Everything that sales intelligence strives to do should contribute to more effective or efficient sales behaviour.

Four main pillars of sales intelligence

With this in mind, there are four main pillars of sales intelligence, all of which are changed significantly by the advent of AI.  Sales intelligence needs to be timely, and deliver crucial insights quickly so they can be acted on before others have had a chance.  It needs to be relevant, not just a flood of noise that a sales person must dig through.  Good intelligence should take into account the context of existing relationships with the person or company in question.  Lasly, sales intelligence is of limited use if it’s not very tightly tied to an ability to take action.

Looking at each pillar in turn, we can see the ways in which artificial intelligence will affect the sales function in coming years:

1. Timeliness

When an event happens at company you would like to sell to, or a person you are trying to get in touch with is involved in something interesting, a clock starts.  If you are first to put that new development in context, offer help, extend congratulations, or whatever the appropriate response is, you have an advantage.  If you are a day or two late, your chance of making an impact on the person in question is limited.  Sales intelligence needs to be fast.

This need for timeliness plays in favour of artificial intelligence in two main ways.  The simplest is that all research that is done by humans will be inherently too slow.  There is no way for a human to out-race an AI-based system at understanding and categorizing a piece of content.  The more interesting point, however, is that the only way to truly be timely with the use of your insights is to have an AI-based system determine that they are the most interesting and relevant insights of the day, and push them to the sales team proactively.

nudge news mentions

2. Relevance

There is a lot of noise out there.  Asking a sales team to filter through noise in order to tease out true intelligence from fluff is a quick path to failure.  Success is driven by surfacing just the relevant insights and making optimal use of the sales person’s time. However, relevance is a tricky concept to pin down.  At first pass, obviously a sales territory must be taken into account and in most cases only insights that are relevant to the territory and possibly deals at a certain stage of pipe should be surfaced.

Within the insights though, each selling organization can use different insights in unique ways.  For some, executive changes are relevant and mergers are not, while for others, scandals are very interesting, but only if there’s an element of security involved.  Having an AI-based system that can provide only the types and topics of insights that are needed is crucial to making your sales intelligence efforts relevant enough to see sales teams actually engage.

As a third, and more challenging area, some organizations and people are in the news very frequently and much is known about them.  On the other side of the coin, a VP of IT at a manufacturing company may have almost no online presence.  AI that can optimize towards the intelligence that is most relevant, taking into account the online footprint of each buyer is AI that can deliver intelligence a sales team will use.

3. Network Context

Far more important than raw facts and figures is the context of who the person or company is and how they relate to you and the people you know.  People buy from people they trust, and people trust people they know.  If you can identify a social relationship or network context, perhaps as simple as a name drop, or as impactful as an introduction, you are on your way to a much stronger relationship at that account.

Sales intelligence systems that fail to include the very human aspect of relationships and network context will struggle as the AI-led world is increasingly undifferentiated on mere facts and figures.

Similarly, knowing the context of a sales person’s own relationship with each person is innately valuable.  Suggesting insights to keep in touch with a buyer where the relationship is strong and the most recent communication was a week ago is noise and a distraction to someone in sales.

Network access through relationship intelligence

4. Actionability

As every sales enablement professional knows, the closer a sales intelligence system is tied to the action it needs to drive, the more it becomes impact, rather that just noise.  Much of this, of course, is simply good design, but artificial intelligence plays an important role.  By mapping your network, the most likely people you would engage with can easily be known and highlighted.  Removing the burden on a sales person’s memory brings action one step closer.

Identifying occasions where a light action is a better option than a heavy outreach can also drive action more effectively.  For example, if you have a relationship that is not in an active deal cycle, but you eventually anticipate will be active, you just want to stay in touch and remain top of mind.  In this case, an intelligent system might suggest a quick congratulations on Twitter for a recent award, rather than a deeply thoughtful sales outreach.

Reducing the burden of action makes it simpler still, and if the insight is understood by the sales intelligence system, the next action or best positioning could be suggested with a few options, making the role of the sales person much simpler.

The future of sales intelligence

Artificial intelligence is here and is remaking almost every aspect of the corporate world. Sales intelligence as a discipline will be affected in many different ways, but all for the better. AI-based sales intelligence promises to enable sales teams to be more human by giving them timely, relevant, and actionable insights that are guided by the context of the relationship graph and who knows the buyer and their team.