Beyond Copilots, Coaching and Call Insights

We're here today to talk to you about the Connected Loop Sales Enablement. So look, AI is everywhere and AI in sales is no different either. But what you'll find is that it doesn't normally change what happens next. So most sales AI can live in fragmented toolkits, different systems. It can provide answers, give intelligence, but it doesn't always integrate together and connect what goes on in the background and how it really makes a difference to customers. So today we're going to explore the power of the Connected Loop AI enablements. And hopefully you'll see how this cycle links performance, links training, and links it to your performance opportunities without breaking a cycle, without that fragmented situation either.

Brilliant. Thanks, Dan. So I'd actually really like to start off with a question and get a sense check with where you are all right now as far as your revenue stack is concerned. So we'd love for you to participate in our quick poll. You can either join us via the QR code on screen or go to slido.com and add the code in. But we're really interested to understand which tools you are regularly using in your revenue stack today. There are a number of different options and clearly we don't cover them all on the screen, but it gives us a really good understanding of where you're at. And no surprises, 100% of you are using large language models such as Copilot, ChatGPT, or Claude, which seems to be everybody's current favorite. Just going to give it a couple of moments for you to participate into the poll. I'm sure there are other platforms being used within your organizations on a daily, weekly, and monthly basis. Not only by yourselves, but also by your, your salespeople and other people within the business. So again, you know, some of you are utilizing both AI roleplays and AI coaching, but there doesn't seem to be anybody currently using Conversa— ah, there we go. I knew some of you would be using Conversation Intelligence, and I'm also quite sure that some of you are also using sales enablement platforms as well. But we can see here that we have a few people participating. I trust that you're able to access the QR code correctly and easily so that you can join us in the poll. Let me just give it a couple more moments. The other interesting thing, I guess, to just mention while you're using the QR code is the fact that, you know, it's really interesting to see how advanced your stack is with regards to the AI products that you're using and that your salespeople are implementing on an ongoing basis. So let's just give it a moment to see if anybody else wants to join into the poll. So, okay, now, now you've answered the question. This is, this is the big question. How confident are you that the tools that you are currently using deliver measurable changed seller behavior in the moments that decide revenue for you on an ongoing basis. So again, please do click on the QR code and tell us whether you're seeing measurable changes in behavior on an ongoing basis. This is the question that really matters, particularly when you're accountable for results within your organization. And interestingly, what we found is that most AI helps you know more, but it doesn't necessarily help you perform better. And actually, this is where most AI conversations quietly fall apart. So I'm delighted to see that some of you are seeing some measurable changes. But equally, I'm not surprised to see that you're not confident that you can prove those measurable changes on an ongoing basis. We normally get a mixture from 1 to 5. We normally do see some 5s, which is really reassuring. But you can see by the results that whilst you have a number of different platforms that you're using on a regular basis, what you're not seeing is that measurable change in behavior. That is really important from a continuous improvement point of view, but also really important from a revenue point of view with regards to the impact that it has on your bottom line on an ongoing basis. So really interesting results there. Thank you so much for, for participating and engaging with us as far as the poll is concerned. I'm going to hand back over to Dan.

Thank you, Claire. And yes, some real interesting answers there. So part of the problem is there's so much choice out there. And while we try and understand what we should have, what we shouldn't have, if it's talking to each other and actually delivering what we need. So what we've designed here is a taxonomy of revenue enablement. And this is just an example, but it's a simplified view of a very complex landscape. So what we have here at the bottom is what we call the data layer or layer 0. So this is kind of your core information, CRM information, revenue intelligence, forecasting, data enrichment, intent. And you can get these from, you know, Salesforce, HubSpot, and the likes of Gong as well. Then what you have is layer 1, which is that enablement and tech assistance. So what you have is this data layer informing layer 1. And in here you'll have sales engagement, conversation intelligence such as Gong. You might have content enablement such as Seismic or HiSpot. And then probably what we're all familiar as well is our LMS, LXP. So again, some examples in here would be Degreed and MindTickle and Dachebo as well. We then move on to layer 2. Now this is where our capability comes in. So we're looking at kind of the methodologies, the IP, the training in the background. So for sales purposes here, you might have ourselves or Richardson or Korn Ferry. You might also be able to practice and again, look at role plays, do skills and assessments, which is usually AI-led, and then also deal execution or agentic workflow. So Claude Cowork, which is an emerging capability at the moment. And then you have that layer 3, so that orchestration layer, the revenue enablement. So you have that all-important orchestration, but also that AI governance and compliance as well, which is all important to this. And what tends to happen here is that we can use elements of these. We can use common things such as Copilot, or you can use assistants. But again, you still have to go into those fragmented layers and do these separately. They don't necessarily talk to each other, which creates a bit of a problem. Just highlighting this part of the slide here is that, you know, Imparta here plays all layers. So again, we can be that orchestrator. We have that methodology. And that conversation intelligence as well, right down to that, that data layer. So we'll hopefully take you through a bit more of that as we go through the presentation and to see how that integrates into the connected loop.

Brilliant. Thanks, Dan. You can see how complicated the sales enablement arena has become with the use of AI and how those boundaries have become blurred. So this is the missing category as far as we're concerned, that connected loop enablement. What it really means is that we can deliver AI sales enablement that starts with a real goal. It influences behavior, and it also gives you the capability to be able to measure the change in behavior that you're looking for, and it fixes the gap. So this isn't about insight, it's not about learning, but this is about on-the-job execution on an ongoing basis. We say at Imparta that it's taken us 30 years to be able to create something that is so simple, that connects the performance that you do on a day-to-day basis with the ability to be able to develop and learn and continually enhance that performance. So the first thing that you're going to do is, is you're going to do some kind of preparation. So let's take on the persona of a salesperson. I'm going to go into a call with a new prospect and a stakeholder that I want to build a relationship with. Before that call, I'm going to do some preparation, and I can work with the connected loop from an AI point of view to be able to do the preparation that I need to understand my stakeholder, the organization that they work for, their objectives, their successes, and their challenges. Once I've done my preparation, I then move into actually doing the call. And having the conversation with my chosen stakeholder. And once I've completed the call, what I'm then going to do is assess how effective I am. So that could be through reviewing call transcripts or asking the AI to work with me to assess what I did well and what I could do differently. From that assessment piece, I'm then going to identify what it is that I need to do differently, what I need to improve on an ongoing basis, And once I've identified those areas that I need to improve upon, I'm going to follow up. And really importantly, I'm going to follow up with the AI and with my manager as well, because those two things also need to be connected. We know that the manager is the success criteria to our sales performance. So the connected loop is better before and during the call not just better informed after the call. Dan, I'll let you just bring that to life in a little bit more detail.

Yeah, and like we say, this connective loop and what can be missing here is it's not learning, it's not insight, it's not productivity, but it's a loop that starts with that real goal and that real opportunity that kind of can influence our behavior. But the problem is we're seeing at the moment is kind of bringing to life that first slide that I spoke about is actually if we go back to how we prepare, Yes, we might use Copilot, we'll get information from that data layer, and we perhaps do some pre-call coaching, but you'll be doing that in silos. You then actually do the interview or the meeting or whatever it may be, but again, that deal execution sits and content enablement sits in a different platform. We then might assess, but again, we'll do that on how we feel, or not with some concrete fax or someone review it for us. We'll discuss how we feel with our line manager. But again, we don't— we have to wait until we do that process. Might be for a one-to-one, or it could be something that we booked in. We then may find something that we want to improve on as part of that process. So again, we have to access our LMS. We may do some role plays, but again, it goes into that another ecosystem to find that training, to book it in, and we have to wait to do that. And then we come back through the process again. So actually we'll update our CRM. Hopefully we've moved that meeting along, that deal along, that sales engagement's improved, and hopefully we'll go through the process. But at the moment it's still fragmented. It kind of, you know, doesn't close the loop. And again, we're still in that fragmented ecosystem rather than that continuous connected loop that we spoke about.

Yeah, absolutely. So what we're seeing is that most sales AI is like a sat nav with no map data. So you've given the keys to your car to your teenage child and asked them to learn to drive using a sat nav that hasn't got any map data. And of course, we all know that the sat nav is also not going to teach your teenager how to drive. So it's really important that we give the AI the correct map data to be able to enable it to be effective, to give the teaching and learning that's required. So sitting behind the connected loop is a complete set of skills across all major contexts and customer-facing role. So historically at Imparta, we are a very effective Sales 3.0, CX, and Leadership training organization. So we have content that covers all of the key elements for those 3 key-facing, customer-facing roles. We have done over 25 years of continuous research around sales performance. We've also really importantly taken the time to study sales professionals across different industries, so we truly know what works and what doesn't work. And we also have a number of published books that support our methodology on an ongoing basis. Included in the MAP data as well is our faculty and our coaches, our studio team for customization, so we can create bespoke content for you, but also we can use your content and upload your data into the connected loop as well. Dan, back over to you.

Thank you. So we're just going to look a little deeper at that connected loop now and just to kind of introduce you to some of the agents we have in the background. So what you can see here is around 20 agents assisting in different elements. So you've got analysis and assessments, learning and insights, application, and coaching and follow-up. I won't read all of these out to you, but you can see here kind of the sort of things that where these agents it. What's important here is that the orchestrator or these agents, depending on the prompts, depending on the questions you ask, will reach out to the right agent. And importantly, it's connected to the Imparta IP. So you may get generic responses if you're using, say, Copilot or Claude, because they've also read the books, they've also looked at the methodology, but they don't always bring that together in one cohesive loop and one cohesive engine. So the beauty of iCoachAI is it will do that for you, orchestrated by these agents. So there's a huge range of expertise in here that will support you in the moment and bring that consistency to your sales force. And then hopefully what we get here is a follow-on about— so the same loop that Claire took you through is now brought to life by this connected loop. So we now prepare and we use the one platform. So it's actually orchestrating, it's deal coaching, it allows you to do your preparation, it pulls information from your CRM, it pulls information from your notes, your transcripts, whatever it may be to help you prepare for these meetings. When you're doing the meeting, depending how you're doing it, it will also, it could help you on live calls as well with a series of prompts on how you're actually doing in that meeting. What elements have you missed? Have you asked the right questions? Have you considered where the client is in the buying cycle? And if it's not going to plan, it will also prompt you as well on how you should perhaps adapt for it. We can do that assessment in real time. So rather than waiting for a one-to-one with a manager or a colleague, you can actually share your meeting notes or your transcripts with the AI, and it will assess how you did in that moment. You can do that via some more coaching. It will give you a role play or there's specific competency assessments that are built into the system as well. What this also do then is direct you straight to the learning that's going to help you. So if there's learning on this ecosystem, either in part IP or your IP or something else, it will take you to the relevant training. So you get that adaptive learning. You don't have to go through a linear process. You'll go straight to the piece that's going to make a big difference to close a gap in your knowledge. Improve your skills and also improves your mindset as well. A byproduct of actually doing this is actually the telemetry that it bases on. So whilst we'll never read, you know, what people are typing into the AI, we will give analysis and we'll have access to the coach, so the agents that are being accessed. And what that allows us to do is understand where are the sales force really needing help? What agents are being accessed the most? And this might be a sign that you need to do some more training. It could be a workshop, it could be some deal coaching, a bit more focus as a group for your organization. And then the follow-through. So again, this is where coaching comes into play in the moment. Actions and next steps for the call you've just had and allows you to move that deal on and make a difference rather than having to wait through these different ecosystems through these different AI agents. It will do it all in this continuous loop for you.

Claire. So let me bring this to life using an example. We've talked very theoretically up until this point. So the example that I'm going to share with you is a salesperson working to unblock a stalled account. So the first thing to note is that the iCoach AI is proactive. It doesn't just wait for you to engage with it. It will engage with you based on the conversations that you're, you're having with it. So you'll receive nudges either via email or via your Teams, and it will remind you of particular topics that you've been working on and nudge you to continue working with them. It will also encourage you to be able to create a plan. So it might pull some context from your CRM or from past rules. It's going to work to coach the seller, and it's going to give you an opportunity to be able to rehearse a role play. So your preparation is giving you the best opportunity to be able to succeed because you are working with a stakeholder that the AI is currently aware of. You then go into a situation where you do it, and so it's going to provide in the moment real-time guidance at critical points, not just a transcript after the call. Once you've done the call, then it's going to work with you to assess and review what you did well. It's going to immediately convert evidence into clear skills diagnosis. So not, you talked too much, but it will also give you enough— it will give you concrete feedback around you conceded too early, or you failed to anchor value, which is really, really impactful. Once you've been through that assessment, it then works with you to identify key topics for you to be able to target, to enable you to improve. That might be right microlearning, it might be a video to watch, it might encourage you to create a plan to enable you to really work on your next actions, your follow-through, So it drives you to the next step in the opportunity. It will also nudge your manager so that they know what they should be coaching you on, and it absolutely helps you embed that new behavior into the next execution moment. So this is what we mean by AI that changes what happens next. It doesn't just talk about the game, it changes the next play.

Brilliant.

Thank you, Claire. And we have some tests for you. So some tests of connected loop enablement. And this is our view of the world, I guess, and kind of AI that you should be looking out for. So this is what you get through iCoachAI, but also, you know, the sort of things you should be looking out for in that kind of taxonomy. So we believe that the AI should be personalized. So iCoachAI will know you, it will know your role, it will know your goals, it will know your deals, it will know your accounts. And any competency gaps. It's proactive, so you don't have to wait for prompts. It initiates actions through that follow-through. It remembers that follow-through, and you can book time in with the AI to actually go through these as well. We've already mentioned that it's primed with our methodology, so it follows a one, one, you know, sales path no matter where we go, and that's all about IP as well. But we can also bring IP in there around your business and your clients' deals. It should be pool-based. So again, this is around changing behavior through coaching. You know, this isn't about just telling you stuff or getting answers right. This is about changing behaviors in the moments that matter. And it should be present. So an important part of this is that you don't actually have to use our platform for this. It can work headlessly and sit above or integrate with any of your systems. In place. So the agents work in the background. You don't actually know they're there, and it's pulling information and working with different parts of your business. And most importantly, that it's protected. We want to make sure that it's safe. You have the right protection, the right security in place as well.

So I just want to take a moment to talk about that pull-based aspect of AI. What we're seeing through research is a high level of cognitive offloading, which means that AI is giving us the capability to stop thinking, and that is absolutely not what we want. We want the AI to work with us to enable us to think more deeply and to improve what it is that we're doing on an ongoing basis. So the AI that, that we have is linked to the International Coaching Foundation standards, which looks at 8 key areas to ensure that it is ethical and performing in the right way.

Thank you, Clare. And this is just, you know, again, looking at kind of that agentic integration as well. So it's just a mock-up really of what we've done with other clients and what things can look like. So again, you already have invested heavily into different systems such as Teams, Salesforce, and maybe Gong. There are other vendors and agents out there. But what we're talking about here is the orchestrator. So again, you could use the Imparta orchestrator or any orchestrator that you have existing and actually just making sure it's pulling in the right direction using the agents that make the difference when it's needed. But does it work? So we spend a lot of time looking at the impact. A big part of Imparta and what we do is looking at return on investment and really taking the time to look at adoption of our programs, but also the measurements and results as well. So this is based on a 2-year study covering 8 clients, 350 people, and looking at the impact which has been validated by managers and leaders. So across this study, there was a $143,000 per person per year validated increase in revenue. As we said, we had to validate that quite stringently in the fact that most managers and Sales individuals had this more around 500,000 per person, but we want to be realistic about this and challenged what we were saying. On average, we're seeing behavior change that's taking kind of 4 to 6 weeks and an ROI of over 1,600%. More importantly, we've got a huge amount of anecdotal feedback around, you know, people that would recommend this to others and absolutely ensure that, you know, this makes a big difference to what people can do. We've also got a huge amount of recognition on here as well. So again, I won't read these out, but I've got our friends at Selling Power here, but also other industry standards as well. These are recent rewards that we're very proud of, not just us saying so. I think we won another one at EdTech last week as well.

Yeah, I think the important thing with this slide is the fact that we're not getting recognized just for Sales 3.0 now. We also are getting recognized within that AI space for learning and for enablement, which of course we are incredibly proud of.

Absolutely. And look, this, this kind of makes the end of our presentation today. If you'd love to find out more, you can contact myself and Claire, and we could also look to look at work out a pilot with you as well, if that was appropriate. Thank you for your time.

Thank you so much for sharing this with us, Claire and Dan. We have a question from Joel Cohn in the chat. He says— and I wrote this very similar question down— what new skills do the sales leaders need to acquire in order to manage AI when AI becomes a true member of the team and not just a new technology? And I couldn't help thinking of that skill set. Right now, you've got a checklist. Checklist kind of person versus a relationship person. Those are typically two different people. So what does that look like? What's the data that you're seeing? How does this really fit in and does it change who we're hiring?

It's a really good question, Tricia, and I'd love to take the opportunity to, to answer it. So I think for me it's all about the combination of human and AI, and that's where we see biggest impact. So from a recruitment point of view, I can speak personally about the type of people that I'm looking for, and those people don't change. I want people that have that sales experience, that have the hunger, have the skills, have the attitude, but also really importantly, linked to the attitude, have the desire to want to be able to continually improve their performance. And so For me, the two things go hand in hand. I think the other really important point to make is that it's important that the AI is intuitive so that it works with you regardless of what you're putting in there, that, you know, your prompt becomes less important because you have all of the agents sitting in the background and whatever you input into it, the AI will intuitively know which agent to draw upon in order to be able to give you the best results with what you're, with what you're doing. I trust that answers your question.

Absolutely. Gerhard, you may have another question.

Yeah, I'd like to ask Claire, give me some, an example, because you said that AI can provide guidance in real time. How does that work?

Yeah, absolutely. So this is something that we're currently working on. And there's a number of different ways that it, that it could work. And one of the, one of the ways that we are, that we're currently delivering it is that it could send you a Teams message whilst you're in a call. But the thing that we're, we're considering is that that might be slightly distracting. And so in this kind of environment, if Dan and I were on a sales call together and I was leading the conversation, Actually, the AI would send the prompt to Dan rather than to me. So Dan would be able to naturally interject and add to the conversation without distracting what it is that I'm saying and doing. So there's a couple of different ways that we can create that live moment. Very powerful.

The way I understand it is that you have 3 phases. You have the preparation for the call, which is handled by an agent. Then you have the sort of whisper function doing the call that you're still working out. And then you have the analysis of the call results that becomes then subject to coaching and training prescriptions.

It's probably worth noting there as well is that we shared the loop today on, you know, for that preparation stage, but you can actually enter the loop anywhere. It's an important bit to understand. It depends on the users. So interestingly, for the assess stage, for instance, you might be a sales leader, you might be an HR function or a learning function, and actually you might want to start with assessing your team first. And that's, that assessing can be looking at kind of current performance and the last conversations they've had, or it could be a competency or a skills assessment, a 180, something like that as well. So then start working around that loop in a different way. So it's important to understand that that loop is continuous, but you can enter anywhere.

Yeah, good point, Dan. Thank you.

Well, it sounds like that you have cracked the code when it comes to orchestrating agents so that you are connected with all the data lakes in the company, in the— so you have one source of truth. So the final question is, how do you avoid complexity and potential confabulations on the part of AI?

So it's a good question. I think I'm working with a client right now to actually do that. And I think what we have at the moment is that we do have that complexity because we have so many different systems. And then what we don't want to create is another avenue, another portal for someone to go into, which is available. But what I'm working at the client at the moment is actually minimizing that noise. So we're working on some very simple Ts&Cs that have just been signed off off, and we're just about to start a rollout of where customers will be using their own orchestrator. We're helping them with prompts and understanding how their customers are using this, and then start to make life easier, if anything, in the fact that actually the orchestrator— people won't even know it's there in the background. The orchestrator, if you ask it a question, the orchestrator will take you directly to the right agent. And that may be our agent, it may be another organization's agent. But what we can do is furnish that organization with the data about what's getting accessed, how often, the amount of interactions you're having. And as we said, the real nice part of the telemetry is actually what is the bigger picture? What is that telling us?

Okay, final, final, final question. How do you measure that learning has happened?

Yeah, there are a number of different ways that we can measure how learning has happened and the AI will do that for us. So if we think about interaction with the learning on the platform, then there are knowledge checks that take place so that we can understand how well the knowledge has been embedded. We can also send out what we describe as e-cards, which are moments for people to be able to interact with the learning on an ongoing basis. Again, so that you can see that movement from a continuous improvement point of view.

And I think the one thing from, from for that, it's all very well that knowledge has happened, but what we're really interested in is how is it applied and what difference does it make to the bottom line? So we're really careful to work with customers about actually what, what things do you want to, what behaviors do you want to change, but what metrics do you want to move as well? And really work closely with our customers on A, seeing that behavior change, and then B, seeing how that correlates into winning more business, improving margins, win rates, building your pipeline. And that's where we kind of really see the great stuff.

Well, Empower has been known for delivering ROI for its customers for more than a decade. I commend you on your success and for being proactive and embracing the challenge of AI in an intelligent way that helps your clients win more business. Thank you.

Thank you.

Thank you.