This week we’ll be exploring how AI is helping to transform sales engagement with Laxman Papineni, CEO of Outplay. Outplay is a smart sales platform that automates and personalizes sequential sales communications based on past correspondence and personal interests. Laxman is a self-proclaimed “startup addict” who has founded multiple sales and marketing related ventures.
Laxman begins by discussing how he initially began in B2B sales, then goes onto elaborate on how Outplay leverages NLP to guide you through the sales cycle and transforms your correspondence. Deep and Laxman then go into detail about how tonal analysis and generative AI allow for the platform’s personalization & automation capabilities, increasing the user’s amount of qualified leads.
Learn more about Laxman here: https://www.linkedin.com/in/laxmanpapineni/
and Outplay here: https://outplayhq.com/
Deep: Welcome back to your AI injection. This week we'll be discussing how AI is helping transform sales engagement with Laxman Papineni, CEO of Outplay, a smart sales platform that automates and personalizes sequential sales communications. Based on past correspondence and personal interests, has founded multiple startups related to sales marketing. So we're excited to hear what you've learned about using AI to optimize the B2B sales process. Thanks so much for coming on the show. Laxman, can you get us started by telling us a little bit about your background in AI and what role you have at outplay?
Laxman: So first of all, thanks deep, uh, thanks for the opportunity, uh, and the slot to be on the podcast.
Um, so, uh, my background, like, uh, as you know, my name is Laxman I'm a co-founder and CEO at Outplay. Uh, before outplay I did a couple of startups and failed at a bunch of them, which includes AI and non-AI and all the basic stuff over the last 10. The long story short is, uh, right from the college days, I was a blogger, so I was one of the early bloggers in India that have started off blogging on how to blog, how to do this on WordPress, how to do that on blogger.
So that's, that's the kind of the days, the very early days of blogging, especially in India. So at that point I've kind of built a lot of trust with the advertisers. I think buy.com was one of the private advertising networks just coming up back then where all the companies used to do a banner advertising, uh, link building and all that stuff.
So I've built a lot of trust with a lot of these private advertisers that they. Kind of used to ask me if I know any other bloggers in a similar space, uh, that they can trust and buy an ad slot or a link on one of the blogs. So that's when we got the initial idea of building, uh, blog network, where kind of we became a platform for the bloggers where bloggers and advertisers come and transact with each other to do these blog ad placements.
So that was the time I. Felt the need for a solution like outplay. This is, we are talking about eight, 10 years ago. There was, there was no category called sales engagement, neither the AI or nothing. Yeah, so this was all manual through a Gmail and a Google Sheets with a WordPress template on the foreground that you kind of do all the business and do all the follow ups manually as a salesperson.
So that's when we built the mini version of Outplay it. It wasn't called OUTPLAY back then, but it was just a simple Chrome extension that would automate a bunch of manual tasks for me when I'm reaching out to hundreds of bloggers and advertisers.
Deep: So maybe walk us through that pre-sales engagement platform proliferation stage. As a salesperson, what's the problem that you faced back then? What did you typically do as a salesperson to solicit new leads? And I assume we're talking about kind of B2B context where you're trying to get deeper relationships. Yeah. But if, if so, gray, if not, maybe describe a little bit more. Yeah, no, it, it was a very simple problem that any, any typical sales guy would have been facing for ages and even today as well.
Laxman: So I was dealing with advertisers and bloggers at the same time. What does that mean is, let's say if you're a marketer in one of those companies, just raised funding, for example, um, that news would come up on Tech Crunch, on other bunch of peer platforms. So we would prospect those marketing manager.
Asking them if they would be interested in advertising on blocks of certain size with visitors, page domain authority and all that stuff. Uh, because as you mean you just raised money and you would be investing money in billing all that. Yeah.
Deep: So this involves sending emails. You had some kind of list from which you.
Candidate leads. In your case it was, um, you know, folks who just raised it sounds like. Yeah. Then you had some sort of script that told you what to do as a salesperson, like how to reach out, and maybe you had a number of permutations in terms of certain texts that maybe worked better. Then others. Then you sort of reached out and probably 98% of the people ignored you, but maybe a couple percent said something.
Laxman: Exactly. So it, it was just emails back then. Uh, I mean all the, all the tools that we have today, even LinkedIn Sales Navigator, I don't think it was so mature back then. Maybe I don't know much about it or the phone and all this data platforms that we have today. So it wasn't, uh, the same back then, eights or 10 years back.
So I used to just drop them emails and I used to fill their contact forms. Wait for three days, go back and do the same thing. Fill the contact form and drop an email to them. Um, and not even a phone call. So this was all manual I was doing just out of my G Suite, Google seats. Mm-hmm. and then bunch of these PR platforms, which would notify when there is a funding use nothing.
Rocket science there. And
Deep: then when, when they reached out, like. What caught their eye about your stuff and what did you learn from, like, how did you keep track of what worked and what didn't? And,
Laxman: uh, it was all manual again. So that was the, that was the main problem statement. So it was not just reaching out, but it was like, what kind of messages working, What kind of subject lines are working right.
Because since you, if you are a marketing manager of a travel company, for example, my push would say like, Hey, congrats on raising, uh, money. And then we are a blog network. We have about 20 odd blocks with page rank five and no domain authority over 80 with a 20 million user base. Would you like to have a featured article or a banner ad placed on our blog?
So it was a simple and sweet, but there are a lot of ations and combinations when you, starting from a subject line to your body, your call to action, which should kind of get attention from that marketing manager. That was only first step of the job. And once this marketing manager responds back saying, Okay, let's look at what type of blogs you got, and send me the list or send me more information.
Mm-hmm. . So that's when the real manual job starts. Because I'm not the owner of all those blogs. We a network. So I have to get the buy-in from all these blog owners. I used to reach out to hundreds of bloggers in the network with an opportunity, Hey guys, this is an opportunity and we are looking for blogs of these particular stats.
If you're interested, get back to us and then build the list and send it to the marketing manager. And they would select some of them and then the negotiations happen, and then we reach out to the bloggers again saying, Hey, we got the opportunity. This is the opportunity. Finish the job, write a blog article, or put this banner on your blog and then come back.
Right? So the, the whole job finishing all this job is completely manual and which involves a lot of manual task. So
Deep: this, this was, if I can take it up a level, like kind of make it more generic across customers. So you, you have a source of leads and, and then you have some script that, uh, is your initial point of contact.
Some small percentage comes back typically it sounds like, has a request. Um, like so do something for me. Yeah. Like rare. I'm reading into this, but rarely do people just immediately wanna jump on a call. Is that your goal in this case is to get them on a phone call or were you trying to like not do that?
Laxman: uh, it, it was not much about a phone call, uh, back then. I mean, I would do that if it's today. Back then it was the, the whole aim of the complete, uh, exercise of doing this outreach is to get them interested in asking for a list of blocks.
Deep: But your ultimate measure of success was somebody has to put a credit card somewhere or buy something from you.
At some point,
Laxman: right? Yeah. And it was not even that fancy. It was all PayPal. So people used to select the number of blocks and then, Okay, this is how much it would cost to get featured on these 10 blocks. And they would kind of just PayPal me. Yeah. And then I'm responsible to get the job done. And after the job I would pay for the bloggers.
I'm kind of a middleman or restaurant, uh, back there. So that's why there is a lot of manual communication involved between both the advertisers and the bloggers all through email mostly.
Deep: So my guess is you have some kind of. Dialogue decision tree that happens. You've got, yeah, someone, you know, you, you, you send this broadcast email, Somebody bites, asks for something.
Yeah. You might get somebody asking something unique, but you know, they're probably asking from a small set of potential things like the follow up is somewhere in your dialogue graph. You enter a node and now you start, you know what to say in response and at some point. Run out of ability to automate this conversation and you need to jump on and pick it up as a human.
Is that basically the bottom line behind this sales engagement platform?
Laxman: Exactly. So in the, in the first stage, everything is manual, but when we built that Chrome extension, a lot of these back and forth tasks for automated, um, the first template goes out automatically once you have the email address and particular based on a particular industry or a tag, the right kind of script would go into the.
And the call to action again. Right. So, Right. So
Deep: the right kind of script, meaning you've learned from a population of users of a sales engagement platform, what type of outreach works at any point in time with any type of audience?
Laxman: Exactly, So, So this was only us. Doing, uh, the outbound between those advertisers and bloggers at that point, and we've kind of built a mini version of outplay.
Again, as I said, it was not called outplay, it was not called sales engagement. But if there were 20 things that we were doing manually, we've tried to automate at least 10 50 of them so that we could reach out to more advertisers and more bloggers. Run more campaign site between both the blogger sanitizers and today it's a sales engagement.
And today probably it's not just email, but you have the option of doing a phone call. You have the option of doing the message. Exactly, exactly. A lot of multi-channel approaches enabled now because you have the data layer available and you have the engagement platforms available so that you could do those multiple touch points over a period of days and you could automate 50, 60% of them so that your efficiency is.
Deep: something kind of fun, cuz I don't, in, in our business here at xx, we don't, um, we don't do any outbound sales really. And you know, to be honest, I'm a bit of a skeptic on the whole thing, but like, so, so let's, let's you, you convinced me that, that we should do this into my audience. I promise not to spam you guys.
Um, so, uh, so why should we do this at all? Because, and I'll tell you the root problem that I have, the root problem I have is I and my partners. Very technical people and few things do we hate more than all the spam we get. Like we just can't stand it. And so the last thing I want to do is be spamming people, um, about our services.
Now that said, there's an awful lot of people that could really use, like in our case we do, um, you know, machine learning, AI consulting. So we build specialized, uh, machine learning components for folks and we help them, you know, integrate it into the products and such. There's tons of folks that could use.
Our value, we could certainly use more leads. We do almost exclusively just content marketing where we, we have a blog like this, we write some articles, people, you know, bite or don't, and um, usually they don't. I mean, that's just sort of the nature of it. And every once in a while somebody reaches out, but a lot of times nobody reaches out.
So why should we switch? And like, how can we do it in a way that's true to our values? That doesn't make us really annoying? So
Laxman: I would not call it as a switch. Uh, typically in order to grow business, it's, uh, doesn't matter if it's SaaS or consulting, you typically need to have all the engines firing up at certain level, probably if you're just ratting up.
In our case for outplay, for the first one year, we were just dependent on ourone sales by the nature of the tool that we are building by, by the nature of the thought leadership that we have. And it's not, again, uh, any of those inbound things that we are doing. Right? Mm-hmm. . But the reason was I pick a phone and just call someone and ask if they're interested in that service.
If they have, the pain is much more easier than a long journey of doing a blog or doing a bunch of inbound dimension stuff. And when you're a startup, when you're a team of two or three people, you can't afford to wait for a six months or a 12 months for all of your inbound techniques to kick in like a sea or a podcast for that matter, right?
Any of the activities that you wanna do. But three of you can get onto a phone and call probably a hundred prospects every day. Again, as you said, the span is the biggest issue for everyone in the industry. But as far as you can identify the right accounts with the right pain points, probably you'll build five or six meaningful conversations every.
Deep: that's quite a, uh, claim. So let's, let's say I'm intrigued cuz I kind of am. So we say, okay, five or six of the right conversations every day seems like a bold claim. Um, that would be quite transformative. You know, in our case, for our business, what do I do? I, I like download or, or like I sign up for a SAS based sales engagement platform like outplay and then I've got this, um, system.
So the first thing I have to do is somehow put my leads.
Laxman: Yeah, you have to get the right set of accounts, Uhhuh, and right set of leads as in the personas that you wanna go after. Who would be the, So I have to like plug
Deep: in my LinkedIn somehow, and then I have to somehow I can upload a list of email addresses or a list of LinkedIn URLs or something like that.
Yeah. Okay. So then my first question, cuz this is an AI podcast, is at that point in time, presumably you help me with some AI to like, recommend like I give you a seed list and you start helping me with additional people that are maybe like my targets, uh, leads. Is that correct? Yeah. So walk us through, how does the AI piece on your side work to provide those recommendations?
What kinds of signals do you use? How do you train those models
Laxman: and that sort of thing? Yeah, so So you have to provide some triggering points. Trigger points as in like what kind of accounts are like most probable accounts that will buy your solution. And what kind of personas, like are the engineering manager or a CT or someone looking into ai, who are those people that kind of typically responsible for this kind of a service or the.
And what's the time, at what time they feel the pain. So if there is a way to identify that time, like for example, if you're hiring for AI engineers, probably that could be a triggering point or a signal for you that, okay, this, this company or this team is started to invest in AI technologies, for example.
Right. Yeah. Yeah.
Deep: Fundraising's a common one for us too. A bunch of, Exactly. VCs are like, Where's your AI story? And then they're like, Oh, I don't have one . Then somehow somebody finds
Laxman: us. Exactly. So you could use multiple sources to source all these signals. Once the signals are ready, your account list is ready every day for your sales reps.
So how do I do that?
Deep: Unpack that for me a little bit, like in my case, like. What do I exactly give you to get to that point, to those candidate
Laxman: leads? Yeah, so you have to define your icp, uh, and once you define your I, what's an I. I customer profile. Mm-hmm. . So you would, you would put a i customer profile saying that.
Okay. These are the accounts. I mean, uh, any, any company in this particular industry from this geography who have raised more than this much of funding. Having a team of like more than 50 people, or 20 people at least 20 AI engineer. So you have to define all this triggering criteria for your ICP metrics or, Okay, this is the account for me.
And once you've set up all these I accounts either on outplay, one of the data platforms like Zoom info, for example. Mm-hmm. , and these platforms would build those list for you every day, uh, based on all the new signals that they get from different partners. Like for example, Crunch Base would give you the fundraise inform.
And an XYZ tool could give you the job posting information. For example, clear. It is one example, and there are a bunch of other alternative also that you'd get all these signals. And once your account list is ready for your account executive, by the time they log into outplay, these are the 10 accounts that are ready.
And of those 10 accounts, these are three people from each of those accounts. So you have 30 leads to go after today, and all these 30 leads will go into a sequence. And a sequence would say that a sequence would run for 15. With seven or eight touch points. Mm-hmm. , and these seven or eight touch points are across three or four different channel.
There are two emails in that there are two phone calls in there and probably there are two text messages or any other different channels where your particular person has typically spend more time on. Uh, in our case, sales people spend more time on LinkedIn, so sending a LinkedIn InMail or a message or a connection request is more relevant for us versus for you, maybe they must be spending some time on a GitHub or somewhere.
I don't. So you
Deep: would tens they're, they're fairly prevalent on LinkedIn for sure, but like at that point I'm reaching out to them. So a couple of things happened. One is you got from company profiles and attributes to people, right? But like if I'm talking about reasonably sized companies, even a midsized company might have 25, 30, 50 potential project managers working on projects.
How do you get below the company surface and get to the individual project people? Are you building some kind of database at that level, or is it always at the exact level for, For
Laxman: companies? Yeah, so we do have the company information and the contact information as well. So it's not there with an outplay today, but, but as I said, uh, we have that product launch coming very soon, so once you have a list of accounts identified, we can help you with identifying those particular contact.
Email addresses and phone numbers of those particular contacts so that when they're going into a sequence, yeah, sales rep has all the information to go after.
Deep: Need help with computer vision, natural language processing, automated content creation, conversational understanding, time series forecasting, customer behavior analytics.mReach out to email@example.com. That's X-Y-O-N-I-X.com. Maybe we can help.
No, my question is like, let's say that I'm a company targeting larger companies and your product comes back and says, Hey, you know, you need to contact the CEO of ibo. Well, sure, but that's kind of a pointless exercise, right? Yeah. Like that's not who I'm sell. I'm not selling to the C like, you know, somebody 40 levels up in an ibo.
I'm selling to a project manager way down on the ground. Yeah. How are you getting down? Yeah,
Laxman: so in your case, you have to go to the product manager based on the company size. If it is a 50 member company, probably you may want to go and touch your C level people as well. Mm-hmm. . So you can set up those triggers based on the company size.
Mm-hmm. and your account executive also can go through that information before they start the outreach type. So if this company is off a bigger size, then no point in going after C expos probably you have to go at the product manager level or an engineering manager.
Deep: Got it. So like on your side, when you build your repository, uh, your database of contacts for, cuz you're building it across all of the types of customers that are using your platform.
So you're, you have to go in at a people level. So presumably you're mining LinkedIn and a bunch of other sources to be able to like, know that, yeah, okay, this product manager works at company X or Y this is the type of projects they're working on. Your machine learning system can hang, hold in on the keywords around their most, most current project, like current job description that they're at, and then presumably you're able to match based on some of those criteria.
Is that ballpark?
Laxman: Yeah, exactly. There will be a lot of signals, uh, both on the person and the organization as well. Have you raised money? Have you received any award? Have you posted anything on LinkedIn recently? Right. So there there are different levels of personalization points. Mm-hmm. , uh, that we can get from all these public sources like LinkedIn, Twitter, Crunch, Waste, and Oler, and multiple other platforms.
And all this information will be used for you. Generate that first AI drafted email to personalize. So on outplay, the moment all these leads go into the sequence, the first step of the email, for example, if that is an email sequence, the email step that you have chose. Yeah. The moment you click on the.
Task outplay would automatically draft an email for you based on all this information. So as a sales rep, you would go through that three or four liner first email, and if it all looks good, you click on send. If not, you can, you have the option to modify before you click on send.
Deep: So at, let's talk about that a little bit.
So let me just sort of summarize this. We've now identified. Candidates to whom are the targets to whom I'm gonna send an email. Now you're and your system helped me navigate this large space of people that are out there. Yeah. Um, and companies. So now I have to formulate an email for my very first email.
And so you are recommending to me, like right out of the gate, you asked me a bunch of questions about my business, my product presumably to like help author something. So what are you do? Like are you using G P T three to do some kind of generative suggestions or do you have like templates, you know, that you know work and that you're sort of tracking them?
Like how does that recommendation happen? Exactly? Yeah.
Laxman: We use G P T three and some custom models as well. Mm-hmm. , which will take all these personization public source information as an input one is on. Prospect level, the the person that you're trying to reach out to and information of their company and information about what you're trying to sell as well.
So combination of all these three will go into drafting the email for you. The first email. It doesn't stop you. It doesn't stop there when that person responds, you back. It also reads the response and then suggest your response back again. What kind of, uh, response that you've got. Is it positive, negative, neutral?
Is it Objection. Or whatever it is, like there are different options or maybe a more information or, Exactly, yeah.
Deep: Uhhuh, you have a set of classifiers, um, at that point. And, you know, generally how people respond, which, you know, we all kind of have probably responded in all of those ways. At some point, ignoring is probably the most common.
Followed by like, take me off your list, or unsubscribe or something like that. Um, probably that's frequently, currently followed by like, I don't usually reply to these, but something you said was interesting and you know, tell me more about X, Y, or Z. Something like that. Yeah. Okay, so now you've got that piece.
Now I have to create the subsequent emails to each of those. Category. So if they say unsubscribe, you say, Sure, no problem. And then presumably your platform like helps me automatically take them off the list or something. Is that right? Yeah, exactly. But if they say, Tell me more about X, then maybe when I'm first configuring the system, it's the, if it's the first time I've seen a response like that, you might flag me to write something and then assist me in the authoring of
Exactly for the first time when you, when you get a response, you will have multiple options to choose from, whether that's an objection, whether that's more information. So this AI model has to learn a little bit about your platform for a month or two probably. And when you do that based on what kind of an objection or a response that you get, the system would automatically suggest you a draft of the response as well.
So that. Thinking about it, you're not spending five minutes on drafting that, and it'll give you all the information, not just based on what the prospect has asked, but also look at multiple other sources as well. Let's say if I'm a SaaS platform, if you have already signed up to the platform after responding.
To my email address. So system would also look at, uh, because we connect with all these product analytics platforms like Mixpanel Amplitude, and we connect with the customer success tools, customer support tools like Intercom, HubSpot, it'll also look for all the information of what this particular prospect has did on the platform, have signed up, have they submitted a support ticket?
Have they created something on the platform? All this goes back to the ation as. So now as a sales rep, you're not going and checking all this information. You're not spending a lot of time, but still you are drafting a really great email, which shows that you know everything about that prospect. I missed
Deep: that part.
Like what? What would this prospect have done? Maybe talk to some other salesperson in my
Laxman: organization. Probably not, not just a salesperson, but probably you would've, you would've gone to our website and there is a chat option there. You would've asked them a question about pricing or a feature. Ah,
Uhhuh. Right. So I see that's interesting. So you. So you're trying to connect not just the world of the salesperson emailing privately, but you're trying to like track that. So you're putting some instrumentation on my website, uh, for example, to track their interest levels. Like maybe I offer, like in our case, you know, we, we do cons, custom work for national language processing projects, for computer vision project.
So, and, and the people looking, you know, and for like business data, customer analysis, that kind of different categories. So, Imagine your customers have similar things and you wanna know that this person's only interested in computer vision, for example, or, and then that gives the salesperson what something to maybe bite onto, Hey, I saw you read a couple of articles about blah.
You know, what did you, I don't know. What did you think about them? Or something?
Laxman: Exactly. I mean, not, not being too creepy. Yeah. Not being too creepy. But the, the salesperson will have some context around whether this particular prospect. Gone through a case study or a blog article have or spent about like 30 seconds on the pricing page so that more information will help them understand how, what's the interest level of this prospect?
Probably if it is too much interesting and if this prospect is spending a lot of time on some of our pages, I rather kind of draft my own personalization email based on all that stuff, because this particular lead or the prospect is so valuable.
Deep: If I draft a personal email, does your system, then presumably you would gimme feedback on that.
Like, Hey, this sounds a little, is this like a two point, like a, a 0.9 on a creepy scale and a,
Laxman: you know, Exactly, exactly. Like, like the, like the thing that you see on the platforms, like grammar leaf for example, is, is it a friendly tone or is it like two? So you
Deep: do some tonal analysis. Exactly. Interesting.
That's okay. So then, so there's almost like an educational component to the sales folks, like you're trying to turn them into better sellers
Laxman: as well. Exactly. So it's assisting them so that they don't have to spend a lot of time, and it's kind of impossible for any sales rep to kind of be that kind of an efficient and personalization as well, because you're, you're not just going after one or 10 particular leads every day.
You're doing hundred. Probably 150 activities every day. Activity as in emails, calls, following up with the people. You've got lot, many things to do in a day to be able to hit your numbers on a monthly or a quarterly basis, right? So where outplay comes in, like outplay almost kind of becomes an assistant for you and gives you a hand holding throughout the process.
Be it reminding you the follow up, be it giving you the right kind of scripts, helping you with the right kind of objections, giving you more information on where this prospect is spending more time, and how likely are they going to engage with you, What timings you can call them, even for that matter. So based on what kind of people and what geography you making, phone calls and emails.
We will also tell you what are the optimal timings to make phone calls. In this particular region for this prospect. So what are the right optimal times to email them? So you'll have all that information. Sure. Once we start learning more about the way you reach out to the people.
Deep: So one of the things that really successful sales orgs do is they, you know, they'll have a playbook, if you will, that they sort of evolve. And so like if a new seller comes on, they sort of have these optimal emails at, you know, like messages at different sort of stages of the pipe. And they'll have like the full life cycle of the lead mapped out is just wandering around the internet and.
Some kind of initial outreach. What do you do? You don't immediately say, Jump on a phone call with us. Maybe you kind of coax them towards, you know, some more information. They start consuming information. My question is like, you know, and I've, I've been a sort of CTO data scientist type, but like, I've spent a lot of time in with high quality sales organizations and sellers, and one of the things that the really, you know, good ones do is they, they really dial an in depth understanding of their target persona.
So do you help in that sort of persona building process? And then the other thing that they do is they translate that into very specific feedback to like more junior sales folks in particular context. Because like a lot of what you're describing so far feels very like bottoms up, data driven, population driven types of feedback, um, which is fantastic.
One of the things these folks do is they're coming very top down, like they're sort of performing that function. Is there some way to sort of marry the two in your approach?
Laxman: Yeah, that's a great question. So that's, it's kind of the whole concept of the, the sales playbook, right? Mm-hmm. . So as a, as a new rep, once you onboard a team, how does VR onboarding look like?
How does your ramp look like to be, to make you successful here? So there where Outlook can help is the bunch of data points that we already acquired from all your team members that are already using the platform. From the day one Outplay will guide. How to navigate through each of those objections, each of those conversations.
Uh, when somebody asks for more information as a new person, you don't know where that more information is exactly. Or how to respond back. So Outplay AI will give you all the suggestions as to, That's why I said I like to say it as an assistant to the sales steps is more like, because outplay is giving you all that information as how to navigate to each of those points, each of those.
On the lead flow or the prospect flow that you're talking about, and then if it is suggesting you to use a particular response template, it's not just that outplay suggesting you to use, but it's backed by all the metrics and analytics, how many times that particular template has been used for a similar objection and how many times that objection handling was successful in getting a response or booking a meeting.
So it's not just telling you to use this, but it's kind of also giving you the confidence. This has been used by these many times and it has a 80% success rate. Yeah.
Deep: But do all, like, let's say I have a hundred people in my sales org. Do, does every one of them have to go through that learning process or can we learn it as an organization?
Laxman: it's as an organization, but typically as a sales rep, you not go through all that suggestions. I mean, all that training modules one by one. It's kind of at the moment. So
Deep: when you, So it's like a collective knowledge base that's being built across the organization, but any one salesperson might get there.
And then is there a review capability? So like the sales management can come in and like review?
Laxman: Yeah, so they, there'll be an analytics section and we also have a section called Experimentation Lab because as a sales a, if you're saying that we have a hundred people, each of those reps, each of those sales managers would want to run a bunch of experiments.
So next moment could be between A and B variants of this subject line. Which one works best in this particular geography for this particular job role or a persona? And as a sales manager, if I am running that experiment, and if I decide, A, is the winner over B, how am I deciding? So today, typically people use Google Sheets and Excel sheets to maintain all these experiments.
But in outplay, this is all backed by data. The platform logs, everything so that even if this sales rep or this sales manager moves out of the organization, the next one coming has all the context of why we have to use this variant over a different variant. So the learning
Deep: process of the training data is maintained like, Hey, we sent out this.
Response to our initial in inbound a thousand times and this one 1200 times and you know, this one outperformed. So you can go back to that, uh, that source data and analysis that led to the
Laxman: recommendation. Yeah, so the learning curves, the learning curve continues to betterment. With the time, and it'll never go back to the point A saying that, Okay, we don't know.
We have to experiment again versus we already did this experiment and here is the data and this is why you should not do it again. You should not use a variant versus B because it has already failed this many times.
Deep: Gotcha. Let's just shift gears a little bit. How is the environment changing across the past?
You, I think you said 10 years you guys have been up to this. How much immunity is the collective audience of recipients of like all of the sales engagement automation that's happening across multiple companies, but outplay as well? Are they developing immunity to this, uh, these sorts of techniques? Are you seeing trends over time where maybe you had to send out x number of initial outreaches on Y platforms 10 years ago, and now you have to do like 10 x and five y or something?
Like what's, what's happening to the overall ecosystem? Yeah. And how is that changing the, the lessons of your, of your system?
Laxman: Our, our play is around for the last three years and 10 years is something on my personal journey. I've been doing a bunch of things, but definitely today there are a lot more platforms available in terms of data, in terms of sales engagement, in terms of AI features as well, right?
So now it's very easy for anyone to go after a bunch of contacts in a short amount of time. It was not the. Back then, like five years or eight years back. So, which is a result of all the emails and spam that you get today, right? Mm-hmm. . So, which means that it's really tough to get a response from someone these days, and that's where the whole personalization plays a big game.
You have to personalize to an extent. Like, hey, if I send you just an email saying like, Hey, the, I've gone through this podcast. I really love this point that you're talking to . What do you think about abc? Or where do you see this whole industry is going? And that being a call to action may get a, as.
Points from you versus if I just say, Hey Dave, it's nice meeting you. I saw you on LinkedIn. You're doing great stuff, and then a call to action asking you to gimme 30 minutes. Why would you gimme that time? Because you, you get 10, 10 emails a day probably of that sort. Mm-hmm. , all these platforms, all these technologies have made the whole game very easy for anyone to start.
Reaching out, upload a list and blast number of emails within seconds. But what wins still today is the, is the one that invests a lot of time in personalization and invest a lot of time in multichannel approach, trying to reach you out on different places so that you keep seeing my face. So you keep seeing my logo and you kind of get the familiarity with my logo or my face.
And that's when you would respond back to me so no one would respond to the first, uh, second touch point. These days you'll have to do multiple, and based on the stats as we see at outplay and other platforms as well, it requires at least 12 touch points to get a response from someone these days. That's a scale of.
Outreach on the spam that's happening these days.
Deep: So let's you know if we jump out a few years, your system's getting, like systems like yours are getting better at making it appear as if I've personalized my outreach to people. So now people have gone from getting generic, easy to spot. Spam. Yeah. To getting more sophisticated and intriguing inbounds that they'll have to get better at detecting to, in order to avoid and stay productive.
Presumably they will. What's the end destination of this? I mean, it feels like the cynic in me wants to say like, all spam is bad, but the realist in me says, Well, sometimes I really do wanna talk to somebody and I really do have a problem. Like this whole conversation is interesting. Okay. I. You know, I lead a, a, a small consulting organization.
I wound up in some database somewhere, you know, that said I was CEO or something. So I probably get 10. Just grow your lead types of spam inbounds a day, and I probably get about the same. Grow your marketing presence things , you know, a day. At least, and I don't even know that's not even including all the ones that Google caught and everybody else caught and kind of compartmentalized.
The truth is, I really do need to have a conversation just like this with somebody, but like you're literally the first person I'm talking to after four years of getting these of these messages. And I'm only talking to you because I have a podcast and the topic is really interesting and we're talking about it from a totally different angle.
We're not talking about it from me and my business. We're talking about it from like, Hey, how does this stuff even work? Um, you know, cuz we, we actually built a couple of like, you know, sales conversation bots for some folks along the way, and I just got kind of curious about how, how, what the state of that
Laxman: the space is.
Yeah. So like, it's very interesting and we are spending a lot of time on outbound use case itself, but the bigger use case is for the inbound. For the companies that get a lot of leads on a daily basis. Okay. But it still has to happen at scale. And even your inbound leads also expect a level of personalization and they want you to know more about them and their business.
Deep: Somebody who got caught by some of our marketing content filled at a farm, and now we're replying to them. Is that what you mean?
Laxman: Exactly. It's not the, it's not just the marketing content, but let's imagine you're in a real pain for a solution. Mm-hmm. . You're not going to fill a demo request or a signup form just on outplay today.
You're going to open a bunch of outplay alternatives as well, and you're going to just spend five or 10 minutes filling out three or four different forms with different vendors, and then now you wanna talk to all of them and figure out what's the best solution for you. For the sales reps who will reach out to you first, will have more chances of getting your 30.
And that's where also the sales engagement platforms play a bigger role because as a sales rep, you're going to get 10 or 20 of those leads every day, and you still have to navigate through all those 12 different touch points, a multi-channel approach to get the attention of this particular inbound lead as well.
This inbound lead also expect you to learn a lot about them and learn a lot about their. Before you reach out to them, have you already read a couple of case studies on my blog? Have you already gone through a pricing page? Have you already gone through a particular landing page which talks about a particular AI feature?
Because I would assume that that's your primary pain point and I have to talk to you about that particular pain point or email to get your 30 minutes. Yeah, so, so while outbound is a very interesting, uh, case, inbound is more interesting than outbound for sales engagement platforms with all the things that we are talking about because outbound is becoming spam, outbound is becoming not efficient and all that stuff where it still works for certain level of, uh, deal sizes.
But inbound is where it gets more interesting and AI plays a bigger role in inbound more than the out. Where do you
Deep: focus? You have the word out in your name, so I'm assuming it's on the outbound side. Is that
Laxman: correct? It's on the outbound. That's how all the sales engagement platforms have been kind of presumed so far.
Mm-hmm. , it's kind of turning the tables at outplay. We are focusing more on the inbound as well. Because all the customers that we work with also gets about 500 a thousand leads or even more on a monthly basis on their signup form and a demo request form. And all these leads will go into their sales reps.
And now your 10 sales reps have got thousand leads to
Deep: go through. And so you're offering tooling that's similar to what you have to do on the outbound side. You have to understand what somebody's saying in as they fill out the form, and then you kind of help with the preparation of maybe the follow up qualifying emails.
I mean, we, we did something like that where, you know, somebody fills out our form, you know, a good chunk of them are just some crazy person on the internet, you know, talking about aliens and AI injecting into people and who God knows what. So, you know, a, a standard follow up email is like, Hey, tell us about your specific problem.
What type of data you, you know, like, Something that if you can't answer these questions, you, you have no need for our service. And so, So presumably you're helping author that and Yeah. And there is a dialogue. Even there, there is a dialogue and now that I think about it, it goes back like three or four, uh, exchanges before somebody gets on a call because like our time's limited and we don't wanna jump on a 15 minute, 30 minute call with somebody unless we know that there's a good chance we can help.
Laxman: Yeah, exactly. And even so if, if you, if you're doing at scale, uh, I mean, in your case probably, I, I understand the, the number of leads or the kind of a qualification criteria is a little different. You don't want to talk to everyone. But at a SAS platform, getting about like hundred signups a day, and you will have certain leads putting mechanisms in.
And all the leads that kind of hits 30 certain threshold on the lead scoring, You'd love to talk to them and they're also busy and they're also willing to talk to multiple vendors. You still have to compete though it's an inbound lead, you still have to convince them. You still have to impress them. You still have to make sure you know everything about them because your prospect loves you when they're sure you know about that particular person and you know about their pain point.
You know about their organiz. So
Deep: let's fast forward 10 years. Okay. Your system and systems like yours get really good at helping people on, basically like both on the inbound and outbound side, but let's focus more on the outbound, helping them identify their lead candidates, reach out to them, convince them to to come in once they are, show some interest now, I guess that's the equivalent of the inbound side, sort of helps them sort of sell their story.
And you get really good at that. And the flip side is everyone else does too. So everyone's kind of collective immunity, like hackles go up if you will, and, and things change. What's the end game here like? Is the world better off because sales engagement platforms work well and how is it? Or is it only better off for those selling things?
Um, but, or is it, or can you make the case that it's better off for pairing buyers with sellers, which it's everybody's getting is better off? Yeah. Because they're all getting matched with a service that makes
Laxman: sense for them. Yeah. It's better off for the reps who truly care about their prospects or the customers.
So you really have to identify the right set of accounts, right set of persons with the pain point, and you have to hit them at the right time. Be genuinely helpful about that, not just for the sake of doing it. AI is helping you to personalize. You can still blast a lot of emails, but probably you may not going to get a lot of responses, or you may not going to have a lot of success with that.
So whether you have an AI assistant or not as a sales rep, you have to genuinely care for your prospects. Right, So AI is, again, it's, it's not going to replace the ramps. It's not going to automatically bring in all the deals and dollars onto the bank. It will just enable you to be more efficient and to be more successful.
Deep: You're listening to your AI injection, brought to you by xyonix.com. That's X Y O N I X.com. Check out our website for more content, or if you need help injecting AI into your organization.
Deep: It feels like humans 20, 30 years ago had a certain level of like a certain rate at which they could author, customized communication. Machine learning can help get you to a comparable level of. Quality with less effort, but it's also doing that with everybody. Presumably the bar just got raised. If you want to stand out across this new crowd of folks who are all powered by similar AI techniques, then you have to still do something.
Different, and maybe you leverage the efficiencies, but maybe you have a unique style or a unique way of expressing yourself or something is that seems to be maybe where we're heading is like in an ocean, a vastly increasing ocean or of content that's getting, you know, bought. Generated. And. We're just, we're already drowning in it, but it's gonna only get bigger and bigger and bigger.
At some point. We either just get filter bubbled into our narrow little interests, which is sadly what's happening today largely. Or maybe we rely more on sort, like trust or you know, like we, we get a lot more careful about who's content we even will let enter into our eyes or. Definitely. I agree. As I
Laxman: said, uh, it's not just about outbound or it's not just about sales people.
Even the marketing folks has got a lot of, uh, AI capabilities and assistance type. You don't have to write a full blog today, Uh, Right. You can just give context and then boom, you have a fine words. Blog is generated out of GT three. Automatically you do, but
Deep: at some point it's still garbage. Like if you look at it, you're like GT three.
Yeah. I mean it's like a smart parrot, but it's still a parrot, so you still have to so that massage it and turn it into something that sounds like it would come out of your mouth.
Laxman: True. It's still going to be a lot of hustle. It's still going to be a lot of time and energy that you obtain with to stand out from the crowd.
As I said, it's, it's getting easy for everyone to get. But still, it's not that hundred percent that everyone with the same kind of features or the capability is going to compete with each other. You still have to stand out from all that crowd by doing some hustle around how you do D things differently.
Deep: Yeah, and it's also not just about GT three, it's about G G B T four and five and six and 28. Like what, If you look at the trajectory, it's just kind of mind boggling how much better it's getting. And so then you know, at some point you'll be able to just hone in on style. You know, you're writing like Sylvia Plath, you know, mixed with a little Poe and you know, and maybe Barack Obama, and comes like this like narrative style that you would never have come up with on your own.
All right. Well, thanks so much for coming on. Like I've learned a lot in a space that I unfortunately been avoiding for probably too long. I should probably dig into this area with respect to my, my actual business. I feel like I learned a lot more about where this is heading and it does. I dunno, my takeaway is that twiddling Google's spreadsheets and like doing things seven or eight years ago, 10 years ago is, is, is maybe not the right way to go.
Maybe we should invest in, uh, you know, in checking out some of these more modern sales engagement platforms.
Laxman: So, Oh yeah, definitely that. That's kind of a very inefficient way to do sales. Back then, I was not sure of all these platforms, but today any sales guy would search for all these platforms and will demand you that, okay, I need this stack to be able to excel in my job.
The more education, more tools, and then helpful for all the sales people who really care about their prospects. You wanna really spend time and be helpful to your prospects. Those are the ones that who gonna win.
Deep: So I got one last question for you. Like, let's say that we, you know, decide to like, try out your platform.
Like how long is it from start to being able to start using it? I mean, is it like, you know, an hour or two of time, you know, where a smart person can figure out how to get the thing to start? Doing something. Yeah. Or are we constantly like freaked out that it's gonna go rogue and start emailing a billion people and like, you know, Or do we need like a consultant from your side to help us have some white glove service to like, you know, get the thing off the ground?
Like, gimme a sense of how hard it is to use a service like yours.
Laxman: No, it's very easy to use a self-serve platform unless you have hiring member team already with a bunch of other processes that you already have. That's where you're gonna spend some time on figuring out how to do the migration, how to set up and all that stuff.
But a but a small team just starting out, it's very easy. It's a self-serve platform. You can just sign up on outplay.com and start using it. Everything is there, self serve. It'll help you on how to navigate on the platform as well. And the moment you start using it, that's when AI will start learning about how your business stays and how you kind of do the outbound inbound, where the leads comes from, what kind of objections and all that stuff.
So that, that gonna take some time, about a month or two to help you start helping you. But otherwise, it's very easy to get started.
Deep: That's all for this episode of your AI injection. Thank you so much for tuning in. If you enjoyed this episode on AI and smart sales, check out our past episodes on AI and content Generation for marketing with Kate Bradley. Turn. As always, please feel free to tell your friends about us. Give us a review and check out our past episodes at xyonix.com. That's podcast dot xyonix.com.