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Sales AI: Tools You Can Use It Right Now

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The promise of AI may be somewhere off in the future, but machine learning and data science can help you sell more today. Learn the main ways it’s being used, by whom, and how you can have little robots helping you sell more right now. 

For more information on remote selling and a complete list of links mentioned in this podcast, visit this remote selling article on our website.


Sales AI: Tools You Can Use It Right Now:

Full Transcript

Forget 10,000 hours. How much progress could you make in 45,000 years? Well, 32,000 years ago, humans made the earliest cave paintings ever discovered. About 15,000 years ago, we began domesticating dogs. 10,000 years ago, we started organizing in the settlements and developing agrarian societies. Empires started about 4,000 years ago and the first factories arose about 240 years ago. And my God, my friend, it’s been only 30 years since the invention of the worldwide website, if you can imagine that. Basically, every development of modern human history has happened in the last 45,000 years. Yet, in just 10 months, a computer logged 45,000 years of progress. In 2019 OpenAI created a bot they trained to play Dota 2, a complicated strategy and action video game. It faced off against the reigning human champion team OG, winners of over $25 million in prize money in 2018 when it won the Dota 2 world championship. And guess what? OpenAI beat that world class team OG reigning champion.

Of course, none of the players on the human team had 45,000 years of gameplay experience. How could they? When asked about openAI’s training program, founder and chairman, Greg Brockman quipped, “It hasn’t grown bold yet.” That’s the advantage machines have over us. They’re faster, they’re great at repetitive tasks, and they never ever get bored, sick or need a day off. In this episode of Modern Sales, we’re talking about Sales AI and how it’s being used today to support the sales process in organizations of all sizes.

Welcome to Modern Sales, a podcast that’ll help you sell more by understanding how people buy. I’m your host Liston Witherill, founder of Serve, Don’t Sell, and I dig through academic research, interview people inside and outside of sales, in nerd out on psychology, economics, and neuroscience to figure out how people make decisions. And I’m on a mission, my friend, to change the way 100 million people sell so that buying B2B services can be just as exciting as trip to the Apple store. Won’t that’d be nice? Speaking of Apple, seamless transition over on Apple podcasts, we’ve gotten a few reviews that I wanted to share with you. Practice Mog Draft says, love the Serve, Don’t Sell method. Just as important to represent a service product you stand behind is a true value you’re bringing to the table for potential clients and I get that from Liston’s methods. Check it out. You won’t be disappointed. Thank you. Practice Mog Draft for that review.

Jakelynn.com says, listen to Liston, he’s the real deal. Thanks also Jake for the shout out on LinkedIn, so that review comes from Jakelynn.com. And Havace or Havachi, certainly I’m saying your name wrong, but this person says, wow, I turned the show on during my morning commute and was blown away. We’ll be adding Modern Sales into my podcast rotation. Thank you so much for that review and if you are listening and you love this podcast, drop us a five star review on Apple podcasts. It really helps me get the word out so I can keep inching closer and closer and closer, one small step at a time to helping 100 million people change the way they sell, and I can’t possibly do it without you. So if you have a few minutes, do go and leave us a five star review on Apple podcasts.

This is part three of the Sales AI series on Modern Sales where we’re diving into the truth behind Artificial Intelligence and its impact on sales. If you’d like to go back and start from the top of the series, just subscribe and find episode 113 in your feed, it’s two episodes back. In today’s episode, I’ll be covering the current state of sales automation and AI and how organizations are using it right now. But before we get ahead of ourselves, it’s best not to drown in technology, which I hate to say it, we might be in danger of, I’ll tell you why right after this short break.

Everybody in sales has this problem right now. There’s a crushing amount of work you need to do in order to complete a sale these days. The more you charge, the more complicated it is, the longer it takes. More people are involved than ever. With all the progress we make in technology, it seems that human decision making has not kept up. And one of the reasons is there are just more tools than ever. There’s so much noise out there. And to complicate matters, your competition is adopting just about every tool under the sun in order to get their work done, which creates this thing, this sort of prisoner’s dilemma, this race to do more and more with technology. Marketing apps and technology or just Martech as it’s known, has over 7,000 tools available across hundreds of categories. I talked about drowning in technology and that’s kind of where we’re at.

Sales technology is behind but not too far behind with over 1000 applications and tools, and that’s not even counting the Salesforce AppExchange. This is causing a race to automation. Once a few companies start doing it, you’re left with little choice, but to do it yourself. You need to keep up to some degree at least. The solution is to bring in some Sales AI to help close the gap. Well, once bring us back to earth. Shall we? Just bring in some automation? As I said in episode 114, the jobs that are most in danger of full automation are those jobs that are the most repeatable and require the least human interaction. Jobs that require more soft skills like actually directly talking to clients, which you’re probably doing now, those are safe. You’re safe, you’re not going to be replaced anytime soon. But those repeatable functions are also the parts of the sales process most likely to have the best automation and AI functionality right now.

Think of the Dota 2 AI bot that I talked about at the top of the episode. It won because it could be trained fast and repeatedly, but that thing wouldn’t be any good at basketball. It’s skills aren’t necessarily transferable to something else. Side note, the image of a Boston Dynamics dog robot dunking a basketball is beyond frightening, but I digress. In episode 113, I name several categories of sales, each with its own application of AI depending on the use case, and again, I’m using this term AI broadly, not necessarily to mean general intelligence, but I’m using it the way most people use it, which is to say any kind of automation that makes us slightly smarter and augments the work that we can do.

The different stages of the sales process that I’d like to cover in order to dig through what’s available right now, our research prospecting strategy, communication, project management, training and performance and recruiting. I’ll get into what each of these components is, but first I wanted to let you know about another podcast you might enjoy. If you’re a regular listener of the show, you’ll probably also really enjoy the B2B sales show from Sweet Fish Media. You might want to check out the episode on effective account multi-threading with Peter Chun, VP of Sales over at lucidchart.

Those categories I was talking about all start with research. And there’s lots of different ways that you can use Sales AI or automation or… I don’t even know what to call it anymore. The more I’ve worked on this series, the more I realize the term AI is just sort of BS and meaningless, but when it comes to research, there are lots of tools that can help you. There are a few tools that I use on a regular basis and I’m just a guy, I don’t have a big organization here, but LinkedIn Sales Navigator is absolutely crucial. It allows me to tag the accounts that I care about, it allows me to tag leads that I care about and automatically surface those people in those companies whenever new things are happening so that I can comment on their posts so that I can see when they’re hiring, so that I can see when they’re in the news. All of these things are just right there in my feed. I wouldn’t say it’s necessarily intelligent, but it does work that I couldn’t do on my own with 24 hours only in the day.

LinkedIn Sales Navigator is awesome. I also really love Crunchbase as a database. If you’re working with startups or you’re looking for startups. In my case, I use it as a pool of companies to reach out to, to advertise on this podcast. Crunchbase is absolutely fantastic great research tool for many different reasons, anybody interested in startups at all and contacting them for any reason whatsoever should probably be using that. Quick note here before I go any further, I thought about doing this episode several different ways and rather than just talking generally about the types of things you can do when it comes to research or prospecting or strategy, I want to give you some really specific tools and ideas and use cases for how all of these things are put into play.

Now, if you’re looking for just the basics, I do have an episode called Minimum Viable Sales Stack that was recorded about a year ago. It’s episode 66 in the feed, but it’s still pretty much applicable, if you want some ideas for just the bare minimum of how to make it in modern selling, you can go check that out. On the research front, I mentioned LinkedIn Sales Navigator and Crunchbase, there’s another tool out there that works like a Google alert, it’s called Aula and this fits into the prospecting category as well as research, but you can go in there, identify your accounts and it will surface news and other different updates that are relevant to the accounts that you or your team might be tracking. So Aula is another good one and they send a daily newsletter as well, which is free I believe.

Next up is prospecting and I would break prospecting really into three main categories. One is data sources, the second is engagement tools, and the third is ABM, Account-based marketing, which is a topic that I’ve not covered on this podcast but you’ve probably heard the term before and so I’m going to just touch on it really briefly. But first up, let’s talk about data sources. So if you want a situation where you can just go into a database, look up contact information based on different search criteria and filters, a few that come to mind immediately Apollo discover or ZoomInfo again, you can consider these automations and not Artificial Intelligence, but those are excellent sources of data.

If you’re like me and you really like to start with sales navigator first in order to do your searches and then from find contact information depending on who comes up in your searches, a great source for contact info that’s much cheaper than the other ones I mentioned is called lead IQ, excellent product. It also has direct dial numbers as well as email addresses and it’s just a Chrome extension so you don’t have to worry about bouncing around to different databases or anything like that. You can just find the contact information really easily.

Some of these tools will just automatically generate leads on a daily or weekly basis for you, meaning you can go in and tell it what types of accounts you’re looking for, how many employees, what their funding is, where they’re located, what industry they’re in. You can tell it what types of titles you’re looking for, owners, VPs, C-level folks, whatever you’re looking for, and it’ll just give you a new batch of contacts that match your criteria on a daily, weekly, monthly basis, however you set it up.

There are plenty of other tools out there like that that’ll run that way, that’s one option for you to just generate more and more leads. Now, the second category within prospecting is engagement. And there are lots of options for sales engagement out there. Of course, one of my favorites and our show sponsor, Mixmax is one of them. There’s also SalesLoft and Outreach and Groove, and the list goes on and on, but basically what all of these tools will allow you to do is reach out in a more personalized way to lots of people simultaneously, even creating different personas that have different messaging, they have builtin dialers, they have task management. So if you wanted to put people through cadences where there’s emails, phone calls, LinkedIn messages, snail mail, whatever you name it, it can manage that whole process for you. Some better than others. The devil’s in the details, my friend, but they will all do a pretty good job of that.

And then the last category I mentioned is ABM or Account-based marketing. And ABM is this idea that since we have hyper-targeted methods of reaching people, we don’t need to do mass advertising, we could just advertise to say our 100 best dream accounts and just only spend our advertising dollars to show them our ads. And one of the tools that’s leading the way in this category is called Terminus, it allows you to do marketing campaigns to specific accounts across multiple channels. I’ve personally not used it, but it seems really cool honestly. A couple others out there are called RollWorks and Engagio. Again, I’m not an expert in this area, I don’t know the difference between them. You may also check out a tool like Demandbase, but all of these allow you to do account-based marketing and manage really hyper-targeted advertising in order to warm up your leads and your prospects and really stay top of mind with these people that you’re trying to reach.

The next category is strategy. So this one’s a little bit of a murky one, right? Because when I think of strategy, I think of like a go to market plan or an overarching sales strategy. And I’m personally not aware of an AI or an automation that can give you the answers. There are plenty of different software tools that can help you answer targeted and specific questions, but it’s not the same as something that’s truly intelligent and I’m just not aware of one. But I do want to give you two big examples and one is CRM. So the more and the deeper the data you have, the better the analytics and insights you can draw from it. So if you sell to a lot of clients or a lot of customers and you have a lot of support tickets and you have a lot of searches on your website and you have a lot of won and lost deals, that starts to create a really rich picture of data.

A good friend of mine is an expert in Tableau, data visualization software. She can make absolute magic happen with data. By the way, if you’re looking for someone to help you with data visualization, contact me. I’ll put you in touch with her. I mean it, by the way. And this idea of having deep data and deep analytics, it’s both amazing, but it also hurts because if you don’t have the data available, you can’t make use of it. And the larger the dataset, the more you have in your CRM, the more you have in your support system, the more you have in your accounting system. And especially if all of those things are connected, the better and more interesting the data and insights we can pull from it and that should inform our strategy.

Now, of course the downside of all of that is it’s all backwards looking, right? It’s all evaluating what’s already happened and it’s looking for patterns, which is helpful for sure. But in terms of having a vision for the future, it’s not capable of that, just looking at historical data. Now, bringing all this data together, it’s something called a data lake, a repository of all enterprise data that can be accessed, analyzed and transformed to create insights that weren’t possible any other way. Now, this is strictly the realm of very large, very well resourced, very wealthy companies, but it’s worth mentioning because data lakes combined with machine learning and data science is perhaps the most exciting application of AI available now. But it’s only available to really large companies and so you and me, my friend, we’re out of the game. This is not going to help us. But surely, IBM is doing some exciting things with Watson, but that’s out of reach for most of us.

There’s a lot going on on the communication front and I want to break this into a few different types of tools. One is assistance, like Conversica or Drift or a variety of other chat tools available out there. Basically what they’ll do is they’ll chat with people on your behalf, they won’t necessarily have great deep insightful conversations, what they’re going to do is essentially run sales plays that are programmed into them. So they’re not going to be able to think on that feed like a person would, but you might think of them as an SDR on their first day. They might get some things right, they might get some things wrong, they certainly have a lot to learn and depending on how well they’re trained, will determine how useful they are in the future.

Now, there’s a form of intelligence that has to do with tracking. And one tool that’s been around for a long time is ClearSlide, where you could send a sales deck to someone and you could see who logged in, what slides they looked at, how long they spent on those slides. There’s a variety of other tools out there and the other big one that I personally know of is called Showpad. There’s more of those. Basically, they’re content management systems that allow you to send content to your prospects and see what happens once they receive it. If anything, I do want to make a side note here, tools that are quote unquote intelligent because they surreptitiously gather analytics. I have to wonder how long those are going to be available.

Given the push towards privacy and I think the push will only get stronger as we see new and even more egregious violations of privacy moving forward, I would expect that something like GDPR will start to be adopted all across the world. This is absolutely, totally speculation on my part, but my thinking is the policy of data privacy is far behind our capability of violating people’s privacy and so I would expect to see some of these analytics that are privately collecting data without telling the user their business models will be disrupted or at least they’ll require people to opt into data gathering, which some will, some won’t.

The next category under communication is Power Dialers. So again, not super intelligent but a CRM like Close.io, which is fantastic or other engagement tools I mentioned already, including a tool like ConnectLeader, which is building out a lot of its capabilities in sales engagement right now. These tools have what’s called a Power Dialer built in, which means it will dial down a list for you, and some of them have what’s called a predictive dialer where it will dial numbers off of a list in parallel and then only connect to you with the people who actually pick up and all of the others it’ll just drop a voicemail for you or just move on to the next one, which is amazing and also a gigantic problem because we all hate getting spam calls. Most of my spam calls a robocalls. They’re not people on the other end, but still I think we’re all being trained to not pick up our phone, but I find personally that a warm call, even if I’m using a Power Dialer, is by far the best way to advance a sales conversation.

Then of course there’s meeting scheduling, which again, not really smart, connects to your calendar, allows people to book a meeting for themselves. I mentioned Mixmax, once again, full disclosure, a sponsor of this podcast, their calendaring system is great. That’s what I use. And now project management. I wasn’t sure if I should include this, but sales are getting so complicated that I’m starting to see tools show up in this category where there’s kind of a project management element within teams, which could just be a layer built on top of Salesforce or whatever CRM you use, but we may also call this buyer engagement or mutual action planning on more complex accounts. It’s not AI or very intelligent at all, but it can automate and organize the delivery of collateral and buying enablement materials.

Think about, if you could create a custom webpage that had all of the different slide decks and case studies and videos and messages and contact information that you gave your prospects. Imagine if all of that was on one page and you could dynamically and quickly create those for each and every prospect you spoke to. I know it sounds like a lot of work. I actually got a trial recently of a tool called SalesReach, which looks amazing. There’s also a tool here locally called DealPoint, which also looks amazing and they both seem to be new entrance in the sales technology space. Now, one of the areas that I think has the most promise for AI in sales and something that starts to look like intelligence is training and performance management. And I don’t have time to do a deep dive on any of that stuff, so I want to focus on two different areas. One is sales training and enablement and the second is call training. So a lot of the technology that we’re seeing coming into the sales technology space is really focused on the SDR role.

Sales development representatives, business development representatives, people who are on the front lines trying to produce more targeted account-based opportunities. And the reason we’re seeing a lot sales technology in that space is that it’s very labor intensive, the job is fairly repetitious and pretty much all of the communications can be tracked and are digital. So call recording and analysis is really interesting and there’s two companies leading the way on this front. One is called Chorus and the other is called Gong. And essentially what they’ll do is record and analyze all of the sales calls that representatives make and then start to look for insights depending on how these calls are conducted. And you can tie the calls to downstream events like whether or not a deal is won or lost. Now, I think that’s a really interesting dataset, but once again, only going to work for larger companies making lots of calls with lots of representatives.

I don’t know if that applies to you, but I think that that’s one of the most interesting things going on now because I am so interested in what happens in conversation and I just absolutely love the content that both companies are putting out because I think it really starts to demonstrate what’s possible with all of the sales technology stuff. And most interestingly, how it can shed insight into human interactions. Next up is sales training. And I think this is another area that I’m really excited about, not for me personally, but for larger companies because I think with the data that they have and the scale that they have, there’s some really interesting things that they can do. And so I’m looking at companies like MindTickle, like Lessonly, like Brainshark or Showpad coach or Allego or Seismic. What these platforms will do is allow you to deliver your training content and start to assess how effective is it and start to personalize the learning path for different people based on their strengths or their weaknesses, depending on how you set up the core competencies.

I think that that’s really exciting. Again, this is like applying learning science to sales and to sales education and training. I think that that’s really interesting, but not necessarily something you can take personal action on today. The last category is hiring. And hiring is really hard. In my quick cursory understanding of Google’s absolutely tedious and horrible hiring process, what I understand is that even as difficult as they make their hiring process, it tends not to do a good job of predicting who’s actually going to work out and who’s not. So there is one hiring tool out there that I found, I’m sure there’s more, the one I found is called Highspot and what it does is predictive talent intelligence. It claims that it can predict who’s going to work out and who won’t, particularly in sales roles. Lots of these tools exist I think simply because hiring is so difficult.

The key takeaway I want to leave with you in this episode and the key takeaway I want to leave you with from this entire Sales AI series is that the AI revolution isn’t here, at least not in the way that startups pitch themselves. There is no such thing as general intelligence. The AI revolution today is more of a technological evolution. It’s speeding up and it’s a huge part of the story, but the big part of the story is people, how are people going to use all of this technology? How are people going to organize the technology? How are people going to pull the valuable insights and make strategic decisions based on this technology that they have in place? As much as there is great and wonderful and interesting and cool and slick technology out there, ultimately sales, my friend, still is about you and me, the people.

That’s it for the Sales AI series here on Modern Sales. Once again, if you’d like to go back and listen to all Sales AI episodes, just scroll back in your feed to find the last two episodes, 113 and 114 and give those a listen. If you aren’t already subscribed to this podcast, please do so by clicking the subscribe button. You can also sign up for my daily sales insights newsletter where you’ll get one sales tip or idea sent to you every single day along with notifications of new episodes all with the express purpose of helping you sell more services. Just head over to servedontsell.com/newsletter to sign up. It’s totally free and it is linked in the show notes. Thank you to everyone who makes this podcast possible. Juan Perez is our editor. Mary Ann Nocum is our show assistant. Our theme and ad music is produced by me, Liston Witherill and show music is by Logan Nicholson at Music for Makers. Thanks for listening. I am Liston Witherill of servedontsell.com, and I hope you have a fantastic day.

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Check out the four sales fundamentals every top performer masters, how to use value-based selling to increase your leverage, and how to improve your remote selling skills as the world becomes more virtual.

And check out the SDS method if you want to improve your sales process.

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