What Does AI-Powered Commercial Intelligence Look Like?

You want to use data to drive the decisions in your company.

Of course you do.

But you’re probably thinking about data in the form of data from your CRM or your business intelligence tool or your ERP.

But you may not be thinking about your unstructured data.

I’m talking about all of those natural flows of communication, email, Slack, Zoom calls.

There’s more and more every day.

You probably aren’t thinking about that data.

Today we’re going to be talking about a new era in commercial intelligence.

An era that includes all of those data sources and helps you make the best decisions for your business.

Hi, I’m Courtney Baker and this is AI Knowhow from Knownwell, helping you reimagine your business in the AI era.

As always, I’m joined by Knownwell CEO, David DeWolf, Chief Product and Technology Officer, Mohan Rao and Chief Strategy Officer, Pete Buer.

Today, we also have a discussion with Chris Sorel of Catalyte about the promise of AI in areas far beyond generative AI.

But first, let’s tune in as David, Mohan and I dig into what this new era of commercial intelligence means for your business.

David, Mohan, the three of us have talked a lot about a term that I’m about to share with you over the last-

Spiritually aligned?

Yes, but we’ve been spiritually aligned on this topic for a while.

But we have never talked about it on this show, which is kind of fascinating.

I mean, we’ve talked about tenets of it, but never these exact words.

Mohan, I’m going to let David, this is like a special, this is the opposite of an all-skate.

Let’s let David have his moment in the middle.

We don’t need more spiritual alignment.

I want to talk about commercial intelligence.

This is maybe the first time people are hearing this term.

So David, I want you to just break down what we mean by commercial intelligence and specifically what it looks like and what it means for professional service firms.

Okay, well, let’s start by breaking it down.

There are two words in that phrase, commercial and intelligence, right?

Intelligence, I think we’ve talked about a lot, but let’s define it.

It’s the ability to learn and apply knowledge, right?

So to deepen our understanding, to learn and then be able to apply to a situation.

Now, let’s turn to the word commercial, okay?

The word commercial, we don’t need to add on TV.

Those are Super Bowl commercials, is that what you mean?

Exactly what I was saying, it doesn’t mean.

Yeah.

So the word commercial, right?

It is this craft of doing business together, right?

It’s the economic relationship that exists between two parties, right?

When we are in commercial business together, we are transacting with one another.

We have a relationship in which there’s an exchange of value, right?

And so commercial means the procurement and development of goods and then the marketing and sales of those goods, right?

It’s the core activities of business.

To perform commercial activities is to produce and then go exchange for value, okay?

And so when we’re talking about commercial intelligence, we’re talking about going deep into and really learning and understand about the inherent relationship that exists, that economic relationship between two parties, that we can then take that knowledge and apply it in order to improve that commercial relationship, in order to improve the value of the economics that are traded back and forth, okay?

So at the core, that’s what those two words mean.

Now, you put it together, we say we are building a commercial intelligence platform.

The commercial intelligence platform that we are building is one specifically for B2B service organizations, professional service organizations that, unlike so many other commercial businesses, they are relational in nature.

They don’t have a bunch of transactions where I can do a bunch of algorithmic data analysis in order to understand all these transactions flying back and forth.

That kind of math is actually kind of easy.

We’ve been doing it for years and years and years.

What these professional service organizations have, managed services businesses, any service business that’s highly dependent on people, they have relationships.

These relationships are full of, what’s the exhaust of a relationship?

What are we doing right here?

We’re having a conversation.

It’s full of natural language.

Unfortunately, these professional service organizations think all the time, I don’t really have transactional data.

I don’t have operational data I can use to drive my business.

Well, in fact, you do because you have all this communication, all this information flowing through the enterprise.

Just historically, we haven’t been able to digest it all in order to learn and apply what we learn to strengthen the commercial business.

Guess what?

Now, we do.

We have the ability to do it because artificial intelligence has been able to figure out how to learn and apply based on natural language, not just based on discrete data points that are structured data, right?

And so what we’re doing is we’re building a commercial intelligence platform that helps B2B professional service organizations to understand the very nature of the economic relationship that they have with their customers, so that they can score it, really understand how healthy it is.

And by health, we mean the propensity for that economic relationship to sustain and grow over time.

That’s how healthy it is.

And then they can actually apply that knowledge because we provide those recommendations, those insights that actually lead to the next next best action.

So, that’s what we mean by commercial intelligence, and that’s how it sits at the core of what we’re building as a commercial intelligence platform.

Now, in the past, when we’ve used commercial, we would use what are the commercial terms to mean what was in the contract, right?

When now we talk about commercial intelligence, it’s obviously you’re alluding to something deeper.

What are sort of the strands that you can pull out?

What are the components of a commercial intelligence?

Yeah.

So if you look, one of the things I love to do when you’re naming something, and we’ve recently been looking at commercial intelligence, is that the right word?

And we’ve really validated that, yes, this is what we mean.

I love to just go to the dictionary and say, what does the dictionary say?

Right?

Well, interesting.

The first definition of commercial is not that helpful.

It says concerned with or engaged in commerce.

Okay, you’re using the word and the definition.

I don’t really like that.

But the second definition is actually right on, making or intended to make a profit.

Right?

And so that begins to give you a really good sense of what we’re talking about.

We’re talking about the core of business, where you are developing your value streams to be able to deliver goods or services to your clients, and then you’re transacting and selling those in order to produce a profit, which is the fuel of business.

Right?

And that is the essence of what we’re talking about.

So Mohan, let’s take that concept of what does it take to actually produce a profit for business?

Right?

What is this commercial?

Let’s double click on it and go inside of it.

I would propose that there’s actually five critical components to commercial intelligence.

Some of them we do fairly well as an industry.

A lot of them we don’t even look at just yet.

Right?

So the first one I think is market intelligence.

If you start all the way at the front end, you’ve got to understand market conditions, customer segmentation, competition, trends in the market.

Right?

If you’re going to have some sort of offering in market and you want to make profit off of it, you’ve got to understand the market itself.

What are you selling into?

The second piece is what I would call revenue intelligence, which I think is probably just a click up from sales intelligence which most people are aware of.

I’d say revenue intelligence is probably the piece of commercial intelligence that’s done the best in industry right now.

This is really analyzing revenue streams, understanding demand, forecasting growth, and really finding those patterns within your marketing and sales efforts to be able to optimize your marketing and sales.

I think on this podcast before we’ve talked about Sixth Sense, I would say Sixth Sense is a revenue intelligence platform, and they’re doing a phenomenal job of leveraging AI to consume all of these data points in the sales pipeline in order to drive great revenue intelligence.

And so I think that’s the second component of commercial intelligence.

You’ve got market intelligence.

You’ve got revenue intelligence.

The third one to me is client intelligence, right?

So often we’re maniacal about data while we’re dealing with prospects.

But as soon as we have a customer, especially in these relational businesses, we lose track of what is the relationship, what is the engagement, what is the direction, what’s the behavior, what is the satisfaction of that client?

And I think really getting to the heart of the client is the next component of commercial intelligence.

You want to create commercial intelligence, you’ve got to understand your existing customers, which should be the heart and soul of any business, right?

We talk about client centricity, but if you have no data driving that, you’re not really client centric, right?

And so I think that’s the third component.

Take a click down from there.

I would call it engagement intelligence, maybe delivery intelligence, right?

This is really interrogating the service delivery and the alignment of what has been sold to what’s actually being delivered and is it driving the outcomes that you’re looking for?

What’s the effectiveness of solutions for those clients?

And so it’s not just about the relationship with the client, it’s about the engagement itself and the delivery of that service and whether what the customer thought they were buying is delivering that intended value, right?

And so that and then the nature of that delivery, not just from the perspective of what’s our internal process to do it, but really how it’s driving the outcome within the customer would be that fourth level.

And then the fifth level, for me, the fifth component of commercial intelligence is what I call value stream intelligence.

And this is what are all those internal value streams, those systems, those processes internally that all participate in that customer value proposition, in participate in delivering value, in driving those engagements, engaging with those customers to market and looking at those systems and processes.

And again, if commercial is all about and related to profit, right?

How do you optimize those to make sure you interrogate and understand every single one of those value streams so you’re optimizing those value streams to be effective and great at driving that commercial machine?

And so that’s how I look at it.

And I think we have way over indexed on revenue intelligence, and there’s some solutions in market for market intelligence.

What we are building at Knownwell ultimately will cover the entire commercial intelligence landscape, but is focused and starting on what I think is actually the most important of commercial intelligence, which is your existing customer.

And so that client intelligence, that engagement intelligence, and starting to poke into that value chain intelligence, that’s where our product, our platform is really analyzing all this natural communication and information that exists both between a service provider and the client, and in the market, just like open data that exists, consuming all of that to drive greater commercial intelligence for service providers.

I think that makes a lot of sense, you know, I, over and over again, sometimes it makes me laugh because a CRM in an organization is a client relationship management, and a lot of times it kind of sits in the hub.

But it actually has nothing to do with your clients.

It’s really, it’s acquisition, it’s top of funnel.

But it’s interesting how it’s like this big void right there in the center of the organization, the thing that should be the most important, there is just a big gap in a lot of organizations.

So when you think about intelligence, and we’re moving into this intelligence era, that’s where we’re coming from, this big gap.

How do you think businesses need to think differently about commercial health, their clients, this gap, to really be successful in this transition?

If we think about moving clients into the middle and combining that with this new era of intelligence.

Yeah.

Well, I think there’s two things that come to my mind immediately around this.

The first one is you’ve got to look and scratch your head and say why.

If a CRM was designed to be customer relationship management, yet it’s being used for sales and prospects, not for customers in most situations.

Top of funnel, like you said.

Even bottom of funnel, but prospect funnel, not existing.

Yeah.

Why?

I think it’s because it’s really, really hard to discipline individuals, people to keep data up to date.

A CRM is really a system of record is what it is.

The value that people are required to put in, rarely for the common user that has access to these things, is greater than the value they get out of it.

Now, that’s not true for the sales operations team.

It’s not true probably for the CRO, right?

It’s probably not true for the CMO, but for the common user, for the seller, for the account manager, for even more so the delivery team, right?

They’re not using it for customer and really understanding this client intelligence, engagement intelligence, value stream intelligence, and that’s where the bulk of the organization is spending their time.

And so we’ve really as an industry over indexed on, one of the hardest things is to go land new clients, but it’s not the most valuable thing.

Study after study shows that the most valuable thing is actually serving your existing customers incredibly well, and making sure that those value streams deliver the actual value you intend to deliver, and so your engagement, your client intelligence becomes even more important.

So I think understanding that matters.

In the age of intelligence, we have a fundamentally different thing, and this is where being an AI first platform is beneficial to Knownwell in that we can understand, we’ve done a lot of early tests in our beta, get this.

We can actually leverage the communications that exist in an organization to come up with a better list of who your clients are than your CRM can tell us.

Think about how shocking that is.

We started off looking at, well, let’s get a Salesforce connection, we’ll get the list of clients, and that data is so dirty.

We can actually do a better job leveraging the communications of the organization to be able to predict that.

That’s fascinating.

That’s where we are now, that we can leverage all of this information that’s already flowing in the enterprise.

And Courtney, I don’t have to have you go update HubSpot, or Mohan doesn’t have to go update Salesforce with, oh, we just won this deal, it’s now a customer, right?

Because the system, the intelligence can learn and apply knowledge.

It learned and applied by seeing the emails go back and forth, and the contract gets sent, and the customer initiation call.

And so we naturally know these things.

And I think that’s an exciting, exciting instant that’s going to shift the balance where we’re able to have better systems that inform our relationships and how we drive value to them.

So David, how do you think, obviously these things get done in some fashion today, probably poorly, but it gets done in some fashion.

How do you think it gets done today?

And when we have these platforms in place, like the one that we’re building, how do you think the enterprise of tomorrow would be?

Like what, give us a flavor of how things might change for our customers when they start using this and using this well.

What does it mean to them?

Mohan, if you think about that, if you have this data and information at your fingertips, then you’re able to act on it, right?

And so, the whole premise behind Knownwell is we actually don’t have really good operational metrics and insights into how to improve our client relationships in the services industry, right?

And so, what we’re doing is, like before, it would have been impossible to get an account management team, a delivery team, everybody to go input enough data to be able to capture the breadth of information that we are scoring, summarizing, and then providing insights on, right?

You couldn’t, you don’t have enough time in the day to be able to add every single data point from every single one of those transcriptions and emails and everything, right?

So, there’s not enough data entry you can do.

But in a world where the intelligence can devour that and can actually process it better than you and I can, right?

In that world, it can connect dots, it can find the signal and the noise, and it can even document every single one of those data points, right?

What the AI calls a token, right?

Take every single one of those tokens and capture it and provide analysis on it, just serve it up so that all of a sudden in a world where I think relational means I have no transactional data and I can’t do analytics, actually now I have more robust analytics than I’ve ever had before, right?

And we’re able to present a holistic view of this is how strong your commercial relationship is, and most poignantly, not just the results, but then we can go dissect it and say, here’s what you should do because of it.

So now we are empowering delivery personnel, we’re empowering account managers, we’re empowering sellers to know your customer, KYC.

How many times have we said that?

They know it in spades and so much better than they’ve ever been able to before.

And then think how that plays out in professional service organizations.

So many professional service organizations are full of practitioners, not consultants, right?

Unless you’re a true consultancy.

And so now we can afford to double down more and more on those graphs, people that are practitioners and exceptional at what they do.

And we don’t necessarily need them to have that consulting mind of picking up these data signals in order to manage a customer better off of gut, because we actually have operational data that we can empower them with.

And it allows those kind of partner level people, the account managers, the client partners that exist to scale and to be able to do their job more effectively.

And, oh, by the way, takes their job and their view and passes it on to the rest of the organization so that everybody is pulling in the same direction, really working to improve that client relationship.

And ultimately, I think that’s one of the fundamental problem in professional services is we look at this as not a company initiative, right?

But it’s a departmental thing, right?

Delivery’s job is to deliver and to make sure the success is there, and the account managers worry about the relationship.

Well, the data shows the exact opposite.

This is a one-team problem.

This is a corporate level problem of it’s that holistic, integrated experience of delivering value and outcomes to a client that actually drives retention and growth over time.

And so now we can get everybody singing on the same sheet of music, even though not everybody has exposure to every single conversation and not everybody processes it the same way.

So I want to recap the five elements of commercial intelligence that we talked about.

There’s revenue intelligence, market intelligence, client intelligence, engagement intelligence, and value stream intelligence.

So I think that’s really helpful as you’re out there in market thinking about the future of your business and how you’re going to engage in the next era of decision intelligence.

I think these are really helpful, a really helpful lens to look through.

David, Mohan, thank you as always.

The new era of commercial intelligence, it’s here.

And if you’re interested in having real time objective intelligence on the health of your commercial relationships, you might be interested in trying out Knownwell.

Go to knownwell.com/demo for a guided tour and to set up time to speak with our Knownwell team.

Chris Sorel is the AI practice and lead at Catalyte, where he oversees all aspects of the company’s AI offerings.

He recently chatted with Pete Buer about why there’s so much more to AI than just generative AI.

Chris, welcome.

So great to have you on the podcast today.

Thanks, Pete, I’m glad to be here.

Would you mind a quick introduction to Catalyte and your role there so that we can give listeners some context?

Sure.

Catalyte is a consulting services firm.

We’re based out of Baltimore.

Our unique proposition is that we find talent from non-traditional sources.

We have a ML-based screening system that finds people who have the aptitude to be technologists and then we have an apprentice program where we train them up.

So we leverage them both as placements for our clients and also in our project services.

Awesome.

How does AI fit into your world?

So I lead up the AI advisory services practice.

We are focused on providing really fundamentals-based AI guidance, advisory services, and implementation services for our clients.

Obviously, it’s a critical component of everybody’s technology roadmap.

We’re just trying to make sure people are talking about it in a way that’s realistic and based on actual business value.

You’ve got the bird’s-eye view of what patterns there are in customer needs and where companies are making progress with AI.

Are you able to give us a feel for where the majority of your energy is going in focusing on customer work?

I’ve broken this down myself into three different real large buckets.

The first one is productivity AI.

You can think of ChatGPT or co-pilot or GitHub co-pilot, things that are helping businesses be more productive.

The second bucket is really what I’m calling concierge.

It’s really just engagement at the customer level using AI in various ways, whether that’s a chat bot or it’s marketing and using AI to automate that and personalize it.

Then the third piece is really what I’m calling platform services where you might be integrating some AI component into an application or a workflow, things like document intelligence where you’re maybe automating the process of scanning documents and bringing that data in or making decisions.

Those are all, to me, the three major components that we see where AI is being really successful.

I think the challenge sometimes is that there’s a little bit of ambiguity because we say AI, and it just means everything.

Those are the top three.

Is that them in priority?

Do people look at those opportunities sequentially?

How do they show up?

That’s a great question.

I think that it really depends on the organization and really the business driver.

If you consider something like retail CPG, where they’re very focused on customer engagement, they’re probably moving in that direction of concierge first, whereas other organizations where maybe it’s really information-worker heavy are looking at productivity first.

I think everybody sees potential and then the challenge is, how do we actually measure this against productivity or real ROI?

What’s the metric?

For each organization, I think it’s different lines of business are saying, we need this, we need to be more efficient, we need to have better customer engagement, etc.

At the executive level, you’re having to make decisions about where do you place your money and your effort.

I would say, I’m not sure that there’s one that’s greater than the other.

It’s really going to be business dependent.

When you’re brought in to provide advisory services, diagnosing challenges and pointing to opportunities, what’s getting in companies’ way?

What do teams need from you?

What are they trying to overcome in order to tap into the benefits of AI as you’re laying these options out?

What we’ve encountered a lot is frankly, a lot of internal resistance and it’s understandable.

You might have somebody who sees the potential but doesn’t see the risk.

Then legal or insurance or some other aspect of the organization says, well, let’s tap the brakes.

This is a big challenge.

That fear as well as the uncertainty around how do we measure this and say we’re productive and successful is a lot of it.

A big part of what we’re doing when we go in is saying, okay, let’s start with the evaluation.

What’s your security posture?

How well are you engaged in your cybersecurity?

What’s the actual risk that you’re dealing with when you talk about AI?

If you’re dealing with PHI data, that’s a big difference from just some customer data on a chat bot.

Well, okay, the exposure and risk level is potentially higher.

Those type of things, we start with, how do we evaluate the state of the organization and their business goals, and then how do we overcome objections like, this is risky, okay, well, we need a risk management framework, or this is very expensive.

Okay, well, we have to tie that to, how is it improving productivity?

So I think that’s the biggest challenge is just sort of that inertia of, we’ve been doing it this way forever, why do we need to add AI and this whole complexity into it?

And so when you’re on an engagement and you discover the leadership team isn’t all that facile with the tools, do you have like a sort of an immersion program?

How do you force them to get their sleeves rolled up and get their fingers dirty?

It’s a little intangible, there’s this moment, and I’ve seen it differently with different organizations.

So a lot of times I’m working with senior developers, like architects and software developers, and they may not really see the value in it, and then you just hand them one thing and there’s light bulb just snaps and they go, whoa.

And I had that moment some years ago.

I had GPT write a class library to access some API, and it took me a half hour instead of four hours, and I just had that moment of like, oh, I get it.

And so I think that that’s the trick is finding what really resonates with them.

Some people, if they’re marketing maybe and they’re spending a ton of time writing marketing content for their products, and you can say, okay, here’s what we’re going to do.

We’re going to have GPT just, or some generative AI look at your photos, your photography and create descriptions from it.

And then we’re going to run it against this database of personalized information and create personalized marketing.

If you can create those kind of demos where you just say, look, here’s a point problem that I know you’re having.

Here’s pain, here’s cost, and here’s the way that AI can help you with that.

And I go back to, we’re talking about this concept of co-pilots a lot.

And although Microsoft is co-opting it, it’s more broadly the sense that AI should be helping you to solve your problems.

It’s not going to solve all your problems, but it’s your co-pilot.

Hey, how do I get to the Jersey turnpike?

Well, you got to turn right here.

I’m realizing we’re getting to time, so I’m going to stop there and say a very big thank you.

It’s been a pleasure to spend time with you today.

Absolutely, Pete.

I really appreciate it.

I love talking about this and thank you so much for your time as well.

Pete Buer joins us this week with a new segment we’re calling, What’s Your 9-1-1.

Pete, according to the New York Times article, Dr.

Chatbot will see you now.

A large number of our fellow Americans are turning to ChatGBT for their medical advice.

What should business leaders take away from this?

The article is worth reading.

It starts out with a pretty jarring emotional start.

So, a woman suffering serious pain, physical duress, at its end, types her symptoms into ChatGBT.

She had seen the ER doctors the previous day, and they sent her home, calling her symptoms benign.

She continued to suffer, so into ChatGBT she goes.

The ChatGBT chose to disagree and suggested Bell’s palsy as a potential root cause of her suffering, which by the way is something requiring urgent and immediate treatment in order to avoid lasting damage.

Back to the ER she goes, faces a new doctor, shares the diagnosis, gets it confirmed, and proper course of treatment ensues.

These are the kind of stories we’ve been looking for and hoping for all along as we’ve been in the wild with AI.

This is an example of AI making the world a better place.

Of course, it’s not perfect.

It won’t work every single time.

It’s prone to hallucination.

You will always want a second opinion as is the case with anything serious with a human doctor, and therefore one of the places where I suspect humans will stay in the loop.

But what a wonderful place to get to where augmented by the human, and AI can deliver a great first round of advice.

I think if I’m a business leader listening to this story, and I learned from the New York Times article that roughly one in six US adults use AI chat bots for medical advice at least once a month, I kind of got to start believing that my customers are going to be willing to use my AI chat bot, you know, some meaningful amount of time to get advice from my business around products and services and whatever AI powered offerings I happen to have in the lineup.

So I think a hopeful story that has implications beyond the four walls of the medical community.

Yeah, I love this.

And I think it also shows where the consumer is getting smarter about the technology and the tool.

You know, they obviously didn’t think automatically like, oh, this is right, I’m going to run with it.

But, you know, they knew like, hey, this may be, this is a really great source to turn to when I feel like I have no one to turn to.

And it’s much better than just going to WebMD and, you know, feeling like you’re about to die, which isn’t a great feeling.

So I think it is really encouraging.

I think for business leaders looking at things that you have, information that you have, that people are coming to on an ongoing basis, might be a really great place to start to think about, could this be turned in to a more dynamic, knowledge-based AI platform that could be used.

Pete, really interesting stuff.

Love these stories.

Thank you, as always.

Thank you, Courtney.

Thanks as always for listening or watching over on YouTube.

Don’t forget to leave us a review.

It’s really helpful so that other people can find this show.

At the end of every episode, we’d like to ask one of our AI friends to weigh in on the topic at hand.

Hey Gemini, what’s happening?

Welcome to the show.

This episode, we’re talking about commercial intelligence and what the new era of commercial intelligence looks like for business.

So what do you think?

Hey there, commercial intelligence is super important for businesses to stay ahead of the curve.

I think the future looks bright with advancements in data analytics and AI.

Imagine having real-time insights into market trends and customer behavior.

And now you’re in the know.

Thanks as always for listening.

We’ll see you next week with more AI applications, discussions and experts.