Strategic Response Management – Techstrong AI Podcast EP29

Hello, and welcome to the Techstrong AI Podcast. I'm Amanda Ani, and I'm excited to be here today with Ganesh Shanker. He is the co-founder and CEO of Responsive.

How are you doing today? Hi, Amanda. First of all, thank you for having me on your show.

Uh, super, uh, excited to be, uh, uh, part of your podcast. Um, so pretty good. Thanks for asking.

How are you? Doing well. It's a lovely day today.

So, doing well. Can you share a little bit about responsive to our audience? What do you do and then maybe some of your background?

Yeah. Uh, responsive is the leader in strategic response management, uh, a space where we help a lot of our customers in, uh, automating, uh, you know, uh, strategic responses that they provide to their external stakeholders, uh, by means of RFPs, RFI, security questionnaire, due diligence question, so many things. Companies respond, uh, uh, while being a closing a deal or trying to get some investment or, um, you know, or trying to even, sometimes even trying to get Grant.

And I, that's where we come into play. We help our customers to respond to such kind of, uh, questionnaires in a more effective way and, um, in a, in a compliant way also. But per se, about myself, uh, prior to starting responsive, I was, uh, a product manager working for an enterprise software company.

Um, uh, you know, part of that is helping sales teams respond to RFPs That kind of morphed into, uh, a startup idea. Here we are, uh, uh, the response, uh, eight years later. Wonderful.

Well, that's a good segue into our discussion today, which is how large enterprises, including some of the top Fortune one hundreds, are leaning on AI to drive faster and better responses, deliver higher return on investment and revenue. And so y'all recently put out a strategic response management report. Can you share a little bit about this report?

What was it focused on? Who was surveyed and then maybe some statistics? Yeah, so what we mean by strategic response management is, you know, uh, it goes beyond just responding to RFP.

So it allows our customers to speak a unified voice across the board. You know, where when they, when they have been asked with a set of questions from external stakeholders, that could be your investors or that could be your clients or perspective customers. They're asking for information when, you know, when the companies wanted to share the most, uh, UpToDate information, which are compliant, and as well as, uh, you know, uh, which allows them to win, uh, deals.

Um, that information is what we preserve in our, in our, uh, platform, uh, our responsive, yeah, AI enabled platform. Uh, specifically about this report, uh, this is our second annual report, uh, uh, Amanda, this, uh, what we did is we kinda surveyed, uh, you know, a lot of companies, um, who are, uh, either, you know, uh, already using, uh, you know, technologies like responsive, fully adopted, or in the process of adopting it, or they've got it, you know, still not gone to that, or even sometimes people who have not even, you know, start thinking about a platform like this. Uh, you know, we, uh, in fact, just a little bit of a clientele.

We have, we have almost 2000 plus customers that includes, uh, 25 plus, uh, fortune hundred customers, uh, of responsive. Um, you know, uh, what interesting output that we, outcome that we got from this report is nearly 50% of, you know, a lot of these companies revenues are tied to RFPs, bids, you know, tenders and proposals. You, you can, there are different name to the these kind, but it was, it was astonishingly a bigger number.

It is not a small percentage. It's almost half of that. Their business or revenue is tied to these kind of answer to these, uh, uh, proposals and RFPs.

Um, and, uh, you know, uh, you know, what that translated to it is, is, uh, you know, 70% of that, you know, increasing, you know, uh, uh, uh, increasing direct revenue is coming from these strategic responses. The more you respond, it is actually more, it's ty to the more revenue that you're generating. It's, it's another finding that we, we came, uh, to know, uh, uh, you know, also, a lot of our customers have said almost 70, 77% of our, uh, responders to the survey said their volume of how they responded to the previous year, that is 2023 or no part of 2022, and partly in 2023 compared to 2023 to 2024, is gone up significantly compared to what they have done in the past.

And, and even more. The thing is, they're now, they, the companies are expecting these teams to do more with less, you know, they're expecting more revenue, uh, and more, you know, workload, but with less people and, you know, are less time in, in, so they are looking for technologies that can automate, uh, uh, uh, this, right, you know, what that translates into is, you know, uh, if, if you're, especially when you're operating with, uh, you know, uh, lower bandwidth, and if you don't have a technology, what we, the, the survey says is almost 64 4% of this, the, the respondent said, there is a high risk of misinformation going out the door if we don't communicate properly. If you don't have a unified voice, when everybody is spinning up their own piece of content, that puts the business at risk, it creates a liability for the business.

So, a, you know, almost 64% of the people said that is gonna be the case, which is what brings to my last point, you know, that tells me, uh, what another important finding is. Almost a whooping 89 to 90% of the respondents said they are evaluating, or either they're already in the process of adopting or evaluating AI to bring any AI into the mix of how to do more with less. Um, where again, it's not a replacement.

I, again, I don't, I wanna say this is not a replacement for human beings. It is truly augmenting what humans can do. That's how we see, and that's how our customers are, you know, saying, because they see, uh, these are higher revenue growth is expected, and we, uh, and it is strongly, you know, evident from the report, customers are looking for AI forward SRM platforms like response.

I know there's a lot of stats. Hopefully that gives you some color. Yes, absolutely.

It makes sense that they're looking at technologies to make up for having a lesser staff. So when it comes to ai, we know everyone's trying to harness AI in one way or another. What are some of the top solutions for ai and how do people start implementing ai?

You, there's quite a few of, uh, AI revolution is happening. You know, this is, we'll say this, Amanda, this is something not new for our generation. When I say not new, we have seen this similar style come in.

I would say back in way two thousands when I would very similar is the mobile technology from people who started using mobile, you know, I would say mobile revolution. And in, in the later 2000, we also saw Cloud revolution companies moving from on term solutions to Cloud Revolution. I think this is the AI revolution, but the difference here is this is coming much, much, much faster pace than the other two.

At least in our, in my generation, I've seen the, the mobile revolution and the, and the cloud revolution. It, it was a little bit slower than it definitely at that time. It felt bad, it was fast, but compared to ai, it was nothing fast as this AI revolution that we're going through, you know?

But overall, I do think, you know, what is going on right now is finalizing the foundational element. Like, you know, uh, if you look at, uh, you know, the foundation like open ai, you know, even Google, Microsoft, these giant companies are in the process of, you know, uh, formulating this foundation. Right?

You know, what we, I would say, you know, what responsive is, is, is a layer on top of the foundation, which I call it as an application layer. We are an application, you know, of leveraging the foundation. Um, so there's going be a lot more, you know, uh, applications that are going to be stemming out of this foundational layer.

But right now, the, the, I would say the, uh, uh, the market is argumenting for the foundational layer or somebody's gonna prevail. Uh, some like how, if you look at how technology, there are a lot of mobile technologies back then, say, I have to name a few, right? You know, iOS came out out that Android came out of that, you know, later in the cloud, evolution, AWS Google, and you know, Microsoft Azure, and now Oracle is also joining and know we are seeing that trend.

I believe it is going to be the case with, um, with the AI also where we will find who's the foundational layer in a, in a, in the, in the, in the coming, uh, coming months and years. And then you will see a lot more applications are, are going to be evolving. And, uh, the good news is responsive is always be in the forefront of adopting these newer technologies.

So I'm super bullish about how responsive is going to leverage these foundational layer. So, um, and that the future is looking super, uh, uh, bullish, uh, for us, especially where we are going to help our customers augment their response process and help them win more businesses. So yeah, I'm, I'm, I'm looking forward for many more applications.

Yeah, that's the state we are in. When you're working with these company teams, do you have any specific use cases or journeys that you can share where they implemented, uh, these different technologies, including AI and the outcome, the return on investment, or anything that you could share like that? Absolutely.

So if you look at it, right, you know, in the, I think a lot of companies, uh, are under tremendous pressure to, you know, either integrate AI in their product, in their story, you know, for, whereas, you know, I feel fortunate where responsive as embrace ai, even from the very beginning, but at that time it was not generated ai. It is more of machine learning pattern matching. This is pre, you know, uh, chat g PT era, or you know, the open AI era.

So when we saw this opportunity, when we saw this, uh, you know, LLM models, uh, you know, coming into the market on mainstream, we saw a huge opportunity, Amanda. So what do I mean by that is so in, in a simple world, right? In our words, when you try to respond to set of questions, you know, what our technology prior to LLM did, is it kind of pattern match and provided with the best possible answer for those kind of questions, so that you don't need to, you know, sit and think and do, because it's that that contents already there somewhere with the ai, what we have done is we have layered, uh, on top of our proprietary, uh, engine.

This LLM has been layered. So now our customers can say, okay, this is the answer, which is amazing, which is good, which is good fit, but looks passive tone. We want to make it in an active tone.

I want that elaborate. We want to make it grammatically correct. We want to make it emphasis on certain, you know, technologies or we want, they may emphasis on certain strategies that we use.

We have leveraged AI to help them strengthen their responses. Even, you know, uh, like, you know, ever before, they are now going stronger with the right machine, but fundamentally, the content is not hallucinating. The AI is not, that is why we are very careful about not let the ai, ai to hallucinate, rather leverage your enterprise knowledge and use the AI to fine tune it often asset so that you are communicating with the right tone, with the, with the, you know, with the proper messaging that you wanted to communicate.

So, you know, you know, a lot of our customers who have leveraged our, you know, uh, or are leveraging our ai, uh, especially for example, right? You one of one of our customers, they said it used to be, you know, prior to implementing the response, it used to be, you know, for each question, you know, it used to be taking about 20 minutes for them to answer With our prior ai, they were able to do it in 12 minutes. That is almost 40% saving with ai.

Now, I think they are looking at about seven or six to seven minutes of answer. So you can imagine no solution was 20 minutes with, with machine learning prior to eight was 12 minutes. Now we are looking at about seven or six to seven minutes per question.

These questions can have anywhere between 200 to three or sometimes even thousands of questions that come and get our, you know, customers. You can imagine how much automation, how much time. More importantly, what we are realizing Amanda, is not just the time saving, time savings, and especially the technologies that we have.

You know, I think it is expected. What are we, you know, what are we doing with the time saving is more important. Now, our customers are saying they are now responding to more RFPs, more proposals than ever before, which means they're approaching more opportunities that they were passing on before because they didn't have the bandwidth.

Now they're saying, I'm trying to be on a deal that used to be, I'm not, I wasn't part of it before because we didn't have the bandwidth. Now I am actually being part of it that even if you look at our prior, you know, report, last year's report, it is very evident, you know, that people who have adopted, they respond to 16% higher, you know, RFPs that they, the other compared to their peers, that 16% translated to almost 35% of revenue, their dollar income for them, which means that they're adding 35% more revenue compared to what they're not doing it for. So that is what, you know, you can talk about ROI, it not just about time saving.

It is the opportunity that I'm part of a new deal, part of a new, new, new opportunity is exciting, and that is the revenue impact that responsive is making to our customers. Significant positive impacts in many areas. Yeah.

S indeed s indeed. So if there was one key takeaway you could leave for business leaders, what would that be? See, uh, most important right now, everybody is, you know, in a way good and bad, positively.

AI is giving a lot of efficiency, creating a lot of, a lot of opportunity. Also, it's creating a lot of noise, you know, and getting a lot of noise and, you know, a lot of distractions. You know, uh, each e business leaders have business to run.

It is very difficult for them to evaluate on, because I, I'm seeing technologies coming up every single day. It is, you know, it is a distraction somewhere, you know, it is, it is. First thing is for leaders, especially even for us at Responsive, we did this exercise.

We want to understand what are we trying to accomplish as a business goal and align our business goals to the technologies that we want to evaluate. And then instead of starting from scratch, sometimes it is okay to go to your existing, you know, partners or vendors and see what are in their roadmap. You know, these are technologies that are getting mature instead of, there's always going to be a new, new, uh, shiny object in the market.

You know, it is important, should we evaluate or should we look into our existing opportunities that we already have to see that the, the roadmap is there, or we, with the maturity that can we be part of the process? Can we influence your partners to roadmap? So that is the step number one, because otherwise it's going to be a lot of distraction, a lot of noise in the market.

So the most important thing I would say is to, you know, uh, find, uh, uh, you know, what is your business objective and align to that because there's going to be so much of, uh, new shiny objects in the market. So, you know, the most money is not get distracted. Yeah, absolutely.

Sometimes AI might not be the best tool to solve the problem. Exactly. Yeah.

Alright, well thank you so much for coming on our show and sharing your insights with us today. Absolutely, Amanda, thanks for having me. Super excited to, to uh, listen in, uh, to your progress once we go live.

So hopefully it helps your audience, uh, uh, in a good way. Thanks for the opportunity. Yes, most definitely.

And thank you to our audience for staying tuned. And there's more coming up.