AI in Sales Leadership: Where the Hell Do I Start?

1 00:00:00,090 --> 00:00:02,520 Richard Smith: And have never just kind of realised how AI can 2 00:00:02,610 --> 00:00:04,890 really automate and speed those processes up. 3 00:00:05,010 --> 00:00:07,800 Tom Ridley: There's loads of ways to like start finding time 4 00:00:07,950 --> 00:00:11,100 back, clawing back your time in terms of frankly, if you apply 5 00:00:11,160 --> 00:00:13,290 AI across all and many more areas. 6 00:00:13,680 --> 00:00:16,020 Richard Smith: Even those who have access to AI tools, their 7 00:00:16,170 --> 00:00:18,180 research is highly manual. 8 00:00:18,540 --> 00:00:21,260 Tom Ridley: So, how can I tell it about me, about what my 9 00:00:21,350 --> 00:00:25,880 business does, what we sell, what our typical ICP or persona 10 00:00:25,940 --> 00:00:26,690 might look like, 11 00:00:26,870 --> 00:00:28,730 Richard Smith: so yeah, there's two use cases that you can use 12 00:00:28,850 --> 00:00:31,250 for kind of making yourself look more better prepared for your, 13 00:00:31,340 --> 00:00:33,350 for your meetings with prospects, but also helping you 14 00:00:33,380 --> 00:00:44,200 with your messaging as well, I hosting. 15 00:00:44,320 --> 00:00:46,480 Ollie Whitfield: We've got rich, experienced sales leader, an AI 16 00:00:46,780 --> 00:00:49,450 void. You call yourself rich, like experimenter. Is that a bit 17 00:00:49,690 --> 00:00:50,260 undercut there? 18 00:00:50,409 --> 00:00:53,649 Richard Smith: Possibly I'd like to kind of maybe relatable to 19 00:00:53,709 --> 00:00:57,039 some people in this, in this room, is that I feel like my use 20 00:00:57,129 --> 00:01:00,659 of AI in sales is is growing, albeit feel like I'm probably 21 00:01:00,779 --> 00:01:04,139 still at a reasonably junior level. I'm here to learn as much 22 00:01:04,199 --> 00:01:04,709 as anything else. 23 00:01:04,739 --> 00:01:06,209 Ollie Whitfield: Very good. And Tom, what would you call 24 00:01:06,269 --> 00:01:06,629 yourself? 25 00:01:06,960 --> 00:01:09,420 Tom Ridley: AI, early adopter, guru, whatever you want to call 26 00:01:09,540 --> 00:01:12,450 it. I just love a technology, so I tend not to put a name on it. 27 00:01:12,600 --> 00:01:14,820 I'm just all about sales people getting the most out of the 28 00:01:14,850 --> 00:01:17,040 technology, and frankly, having great conversations. So, 29 00:01:17,280 --> 00:01:19,980 salesperson first, AI evangelist second. Let's say that. 30 00:01:20,100 --> 00:01:22,280 Ollie Whitfield: Cool, I like it. Well, we got a lot to get 31 00:01:22,340 --> 00:01:24,500 through, as I said. So, here's what we got. I got an 32 00:01:24,650 --> 00:01:27,260 icebreaker, a bit of fun for you to start off with. Bit of why to 33 00:01:27,320 --> 00:01:29,780 adopt AI right now. There's so much talk about it. I think it's 34 00:01:29,780 --> 00:01:32,240 important to remind ourselves of what's really going on, where it 35 00:01:32,270 --> 00:01:34,910 fits into your sales team, and some key use cases you can walk 36 00:01:34,970 --> 00:01:37,400 away with and start right now. We're sales people, we don't 37 00:01:37,400 --> 00:01:39,590 want to talk about something that's nothing useful for today. 38 00:01:39,800 --> 00:01:42,100 We want to be able to start tomorrow morning, so I've got my 39 00:01:42,550 --> 00:01:44,950 stopwatch ready. We're going to play a little rock paper 40 00:01:45,040 --> 00:01:47,800 scissors to decide who goes first, but I have 30 seconds up 41 00:01:48,040 --> 00:01:50,800 on my phone, and I'm going to make you pitch the best use case 42 00:01:50,890 --> 00:01:53,770 of AI you will personally execute in sales, and there will 43 00:01:53,860 --> 00:01:56,560 be a loser. So, rock paper scissors, please, dudes. Oh, 44 00:01:57,340 --> 00:01:57,850 Richard Smith: scissors wins, 45 00:01:58,090 --> 00:02:00,120 Ollie Whitfield: okay? Right, so on three, I'm going to tap, and 46 00:02:00,120 --> 00:02:03,690 I'm gonna cut you off on 30 seconds, 321, fire. 47 00:02:03,960 --> 00:02:05,670 Richard Smith: Yeah, mine's a little bit different. I'm a 48 00:02:05,820 --> 00:02:08,970 content creator, I guess. On LinkedIn, I post every day. One 49 00:02:08,970 --> 00:02:12,270 of the hardest things to do is kind of think of new ideas for 50 00:02:12,330 --> 00:02:15,720 posting content. What I have done is extracted a year's worth 51 00:02:15,810 --> 00:02:20,130 of my LinkedIn posts into a CSV sheet. I've then used AI to kind 52 00:02:20,160 --> 00:02:22,610 of categorise all of the different posts that I've done 53 00:02:22,700 --> 00:02:26,690 over the last 12 months. It's a few 100, tag them by topic, and 54 00:02:27,170 --> 00:02:29,690 Tom Ridley: then I'm 30 seconds. You better hope they saw 55 00:02:29,810 --> 00:02:31,850 Ollie Whitfield: where you were going, because we'll see. We'll 56 00:02:31,940 --> 00:02:35,720 see. So, Tom, I'm going to count you in: 321, fire. 57 00:02:36,079 --> 00:02:38,389 Tom Ridley: So, a few months ago, I built a 58 00:02:38,989 --> 00:02:42,009 hyper-personalized emailing system, or cold outreach system 59 00:02:42,219 --> 00:02:46,359 that takes insight from LinkedIn profiles, websites, industry, or 60 00:02:46,389 --> 00:02:48,669 publications about an organisation, even their 61 00:02:48,729 --> 00:02:51,579 financial documentation, if it's publicly available, and aligns 62 00:02:51,639 --> 00:02:54,159 all of that to your value proposition, and writes all your 63 00:02:54,249 --> 00:02:57,399 cold emailing scripts for you, and even puts you tasks in 64 00:02:57,459 --> 00:02:58,059 HubSpot. More 65 00:02:58,209 --> 00:03:00,009 Richard Smith: succinct than I am, I'm gonna have everybody 66 00:03:00,099 --> 00:03:02,819 like messaging me saying, tell me what happened at the end, 67 00:03:02,939 --> 00:03:03,119 Rich. 68 00:03:04,560 --> 00:03:06,750 Tom Ridley: It generated you a nice, lovely recipe for 69 00:03:06,780 --> 00:03:07,350 Yorkshire puddings. 70 00:03:08,580 --> 00:03:09,360 Richard Smith: Leave people hanging 71 00:03:09,600 --> 00:03:11,730 Ollie Whitfield: while it's not visible to everybody yet. It's 72 00:03:11,850 --> 00:03:14,460 not a whitewash, that's all right. So, we've got that, Tom. 73 00:03:14,700 --> 00:03:18,180 You had 81% Rich. I think you let's round that up to 20% 74 00:03:18,779 --> 00:03:19,319 Richard Smith: Thank you. Good 75 00:03:19,380 --> 00:03:20,930 Ollie Whitfield: effort. You had to go first, though. So that's 76 00:03:21,020 --> 00:03:24,440 worth 30% of the vote. So all good fun. Now let's get to the 77 00:03:24,560 --> 00:03:26,690 serious stuff. So Richard saying, let's start with you. 78 00:03:26,900 --> 00:03:29,270 You probably nudged me in this direction a while ago. I thought 79 00:03:29,390 --> 00:03:33,320 AI was the new NFT stupid thing that was gonna high and die, but 80 00:03:33,500 --> 00:03:36,770 it's not really the case. So I'm going into NFTs very soon. Why 81 00:03:36,890 --> 00:03:39,230 adopt now? I think you've had a real good beat on this. So 82 00:03:39,290 --> 00:03:41,500 what's what's the case? Why do we need to adopt right now? 83 00:03:41,800 --> 00:03:44,140 Richard Smith: I think a lot of sales people probably felt like, 84 00:03:44,260 --> 00:03:46,780 hey, no, I'm gonna push back against AI, it's here, take my 85 00:03:46,870 --> 00:03:49,660 job, and perhaps there's that realisation that it is here to 86 00:03:49,780 --> 00:03:53,320 stay, and not only that, but I think the realisation that if AI 87 00:03:53,320 --> 00:03:55,960 is gonna become, as you know, prolific, and maybe more 88 00:03:56,050 --> 00:03:59,350 prolific than using the likes of Google in your day-to-day life, 89 00:03:59,590 --> 00:04:02,580 and so the reality is that if you can't embrace it, then you 90 00:04:02,880 --> 00:04:05,550 are going to be left behind. That's you're probably already 91 00:04:05,610 --> 00:04:07,740 left being left behind, hence why you're possibly on this 92 00:04:07,800 --> 00:04:10,590 webinar today, because you're sat there thinking, I probably 93 00:04:10,830 --> 00:04:14,100 feel like I'm not capitalising on this, and you may have made 94 00:04:14,130 --> 00:04:18,930 very little to no progress. I've just came to realise that we all 95 00:04:18,990 --> 00:04:22,910 likely do tasks every single day in our sales jobs, which we've 96 00:04:23,000 --> 00:04:25,310 probably done for years, we've always done them a certain way, 97 00:04:25,610 --> 00:04:28,250 and I've never just kind of realised how AI can really 98 00:04:28,550 --> 00:04:31,250 automate and speed those processes up. And I think for 99 00:04:31,310 --> 00:04:33,680 some people, and I probably count myself in this, was I have 100 00:04:33,710 --> 00:04:36,020 this kind of embarrassment sometimes that, oh, what if I 101 00:04:36,260 --> 00:04:39,380 send this email to a prospect as like a follow-up to a meeting, 102 00:04:39,710 --> 00:04:42,400 and it can, they kind of get a sense that it's I've used AI for 103 00:04:42,520 --> 00:04:44,710 it. I think I've come to realisation that I shouldn't be 104 00:04:44,830 --> 00:04:47,830 embarrassed by it. Like, prospects should realise, and 105 00:04:47,920 --> 00:04:50,710 hopefully this is what the human being will realise, is that 106 00:04:50,830 --> 00:04:54,460 people who use AI to help them with these tasks is just part 107 00:04:54,490 --> 00:04:57,490 and parcel of how we're kind of moving with the world. But I do 108 00:04:57,550 --> 00:05:00,450 think there's a careful line to balance there I. Thing you know, 109 00:05:00,480 --> 00:05:04,350 the careful line between using AI to go really fast and 110 00:05:04,620 --> 00:05:07,470 removing the human element from the from what we do as 111 00:05:07,590 --> 00:05:11,700 salespeople, but I kind of one stat that really kind of stalled 112 00:05:11,760 --> 00:05:14,580 me that I came across is that this is from last year, by the 113 00:05:14,670 --> 00:05:17,250 way, so I can only imagine this number is quite a bit higher, 114 00:05:17,610 --> 00:05:22,460 71% of employers prefer AI skills rather than experience, 115 00:05:22,580 --> 00:05:25,430 right now, pretty staggering, right? If you can evidence that 116 00:05:25,550 --> 00:05:28,940 you've got high aptitude or even a competent aperture when it 117 00:05:28,940 --> 00:05:31,700 comes to AI, they will prioritise that before they look 118 00:05:31,820 --> 00:05:34,580 at kind of where you worked in your last job or what you 119 00:05:34,640 --> 00:05:37,670 actually did. And I just think you need to consider this. Let's 120 00:05:37,730 --> 00:05:41,440 imagine you are applying for a new role in sales. What do you 121 00:05:41,680 --> 00:05:45,910 think the employer, the VP of sales, the CRO, the sales 122 00:05:45,970 --> 00:05:47,860 manager, whoever's interviewing you, who do you think they're 123 00:05:47,860 --> 00:05:49,840 going to choose in a head to head? Do you think they're going 124 00:05:49,840 --> 00:05:53,470 to choose the candidate who has evidenced how they're using AI 125 00:05:53,740 --> 00:05:55,960 to help them become a more effective seller, or they're 126 00:05:56,020 --> 00:05:59,110 going to choose the person who doesn't really know how to use 127 00:05:59,230 --> 00:06:01,860 this and is kind of still doing things the manual way, and still 128 00:06:02,010 --> 00:06:05,010 spending huge amounts of their time doing manual tasks, like 129 00:06:05,040 --> 00:06:07,890 which person is going to stand out, and you think if you lay it 130 00:06:08,010 --> 00:06:10,560 out as kind of just sort of direct, is that it kind of the 131 00:06:10,680 --> 00:06:13,710 realisation of I need to embrace this, if I'm not embracing it. 132 00:06:13,890 --> 00:06:16,860 So there's kind of my, you know, realisation. I again, I feel 133 00:06:16,860 --> 00:06:20,040 like I'm by no means like an expert on this topic, I'm 134 00:06:20,100 --> 00:06:23,150 probably I'm not starting at the bottom, but I'm still probably 135 00:06:23,210 --> 00:06:26,240 quite average in how I leverage AI, quite frankly. But I think 136 00:06:26,270 --> 00:06:29,240 people need to realise that it's what companies are looking for, 137 00:06:29,330 --> 00:06:32,120 it's what you will need to have if you're gonna stay relevant in 138 00:06:32,270 --> 00:06:34,670 sales. And hopefully we can share some, some good starting 139 00:06:34,700 --> 00:06:35,330 points with people today. 140 00:06:35,480 --> 00:06:37,340 Ollie Whitfield: Anything to add real quick? Tom, shall I? Shall 141 00:06:37,370 --> 00:06:38,360 I kick us off on how we do that? 142 00:06:38,570 --> 00:06:40,550 Tom Ridley: Only, and this is not planned in any way, shape, 143 00:06:40,550 --> 00:06:42,640 or form. No one's gonna believe that, but it isn't. I didn't 144 00:06:42,730 --> 00:06:45,280 even know Rich was gonna give that example from an employment 145 00:06:45,280 --> 00:06:49,000 perspective, but I literally had a colleague of mine, his son's 146 00:06:49,060 --> 00:06:51,700 going into the first, his first proper sales role, or account 147 00:06:51,730 --> 00:06:54,100 executive role, should I say, they wanted someone with a black 148 00:06:54,190 --> 00:06:57,640 book, he didn't have one, but he spoke to me about how they could 149 00:06:57,640 --> 00:07:00,660 use AI to build out their funnel, got the role because of 150 00:07:00,720 --> 00:07:02,670 the fact that he was introducing some new ways to grow their 151 00:07:02,730 --> 00:07:05,430 business and actually expanded beyond his book, beyond his 152 00:07:05,460 --> 00:07:08,010 black book, which obviously would run out at some point, and 153 00:07:08,010 --> 00:07:10,890 moved on to actually, how like a sustainable way to maintain a 154 00:07:10,920 --> 00:07:14,070 pipeline and a funnel, so just evidence of Richard's point 155 00:07:14,070 --> 00:07:14,220 there. 156 00:07:14,580 --> 00:07:16,710 Ollie Whitfield: All right, Tom, talk me through this. This is 157 00:07:16,860 --> 00:07:18,960 something that was really eye-opening when we talked 158 00:07:18,960 --> 00:07:19,710 through this the first time. 159 00:07:20,010 --> 00:07:23,510 Tom Ridley: Yeah, so this is based upon entirely based upon 160 00:07:23,660 --> 00:07:26,360 data that both Salesforce and HubSpot did in order to 161 00:07:26,510 --> 00:07:31,550 understand what sales people are doing on their platform. We've 162 00:07:31,730 --> 00:07:34,010 given it different terminology here, but the actual original 163 00:07:34,070 --> 00:07:37,520 terminology was around, like, value add. Okay, so value add 164 00:07:37,640 --> 00:07:40,190 time, in my, from my perspective, and the perspective 165 00:07:40,190 --> 00:07:44,350 of this study was time spent engaging with prospects, with 166 00:07:44,470 --> 00:07:48,100 clients, selling right, doing the human things that Rich so 167 00:07:48,430 --> 00:07:51,010 perfectly pointed out, that like really important activities 168 00:07:51,070 --> 00:07:53,710 we're doing. It's also, I reckon, if we took a poll of how 169 00:07:53,800 --> 00:07:56,800 many people enjoy doing the selling part, as opposed to 170 00:07:56,860 --> 00:08:01,260 doing the admin part, I think we'd have 100% vote for I like 171 00:08:01,350 --> 00:08:03,870 doing the selling, I like engaging with people, but the 172 00:08:04,020 --> 00:08:08,190 reality is, is that we spend as sales people, regardless of the 173 00:08:08,340 --> 00:08:11,010 level at which we operate, and being a sales leader, I can tell 174 00:08:11,070 --> 00:08:13,110 you it spends more time in the admin than you do the selling 175 00:08:13,260 --> 00:08:16,050 the further up you go. It's amazing how much time we spend 176 00:08:16,470 --> 00:08:21,050 on admin time. So that left hand side of today is showing us that 177 00:08:21,080 --> 00:08:24,470 we're spending somewhere in the region of between 75 80% of our 178 00:08:24,560 --> 00:08:27,290 time doing admin, and I would actually categorise that as, 179 00:08:27,620 --> 00:08:30,470 frankly, for the most part non-value add. It's not to say 180 00:08:30,500 --> 00:08:33,320 it's not without value, but it is to say that it doesn't 181 00:08:33,380 --> 00:08:36,230 necessarily deliver anything against your number directly. 182 00:08:36,350 --> 00:08:38,570 The engagements that you have with prospects and clients do. 183 00:08:38,720 --> 00:08:42,250 The goal would be, or the Mecca would be, how do we get to 184 00:08:42,310 --> 00:08:45,430 tomorrow? How do we flip that completely, so that we do much 185 00:08:45,520 --> 00:08:48,100 less admin time and spend way more of our time engaging with 186 00:08:48,130 --> 00:08:50,620 people, having more fun? Is the funny way of saying it from a 187 00:08:50,620 --> 00:08:51,790 salesperson's perspective, right? 188 00:08:51,999 --> 00:08:54,939 Richard Smith: Add on there as well, like whilst these pie 189 00:08:55,179 --> 00:08:58,779 charts are a stock when they kind of show you what you 190 00:08:58,929 --> 00:09:02,489 possibly are to where your time is being sunk today versus where 191 00:09:02,549 --> 00:09:05,849 it could be invested, the impact on sales teams with AI, we're so 192 00:09:06,179 --> 00:09:10,109 focused on time savings, which is true. However, like I think 193 00:09:10,109 --> 00:09:13,229 we need to focus on like how it can actually improve the quality 194 00:09:13,679 --> 00:09:15,629 of everything that Tom's talking about, of the actual 195 00:09:15,899 --> 00:09:18,899 interactions that we're having in our jobs, because there's no 196 00:09:19,079 --> 00:09:21,529 point increasing your selling time if you aren't actually 197 00:09:21,559 --> 00:09:23,659 getting better at selling, right, you're just basically 198 00:09:23,749 --> 00:09:27,229 doing more, perhaps mediocre, doing things maybe the way that 199 00:09:27,289 --> 00:09:30,049 you did it yesterday, which is maybe not optimum, and the 200 00:09:30,229 --> 00:09:33,979 impact of AI needs to be realised about how it can 201 00:09:33,979 --> 00:09:37,579 actually help you not just save time but have improved quality 202 00:09:37,669 --> 00:09:40,509 of interactions, how it can help you be more researched, more 203 00:09:40,599 --> 00:09:44,259 timely, more relevant, sound more expert to your prospects, 204 00:09:44,319 --> 00:09:47,049 all the things that we should be focused on. That's for me quite 205 00:09:47,049 --> 00:09:51,069 important to note. There is that yes, it's a massive time saver. 206 00:09:51,429 --> 00:09:54,249 Absolutely, but you have to also look at it from the sense of how 207 00:09:54,369 --> 00:09:56,349 can it help me be better at selling as well. 208 00:09:56,500 --> 00:09:58,930 Ollie Whitfield: Speaking of, let's look ahead, Tom, a couple 209 00:09:58,930 --> 00:10:01,950 of things that. Time, you could put back into place. Talk me 210 00:10:02,010 --> 00:10:02,100 through. 211 00:10:02,460 --> 00:10:04,380 Tom Ridley: Yeah, so the statistic up front and centre 212 00:10:04,440 --> 00:10:07,380 here is 22% of your time back, and actually this is from an 213 00:10:07,500 --> 00:10:10,260 individual productivity perspective. I think it was two, 214 00:10:11,250 --> 00:10:14,490 maybe two, almost two and a half years ago that this statistic 215 00:10:14,550 --> 00:10:17,130 came out. So it's probably most likely it's increased since 216 00:10:17,250 --> 00:10:20,130 then, but it seems like a crazy number to think that you can get 217 00:10:20,190 --> 00:10:23,870 22% of your time back in a given period, and I often frame that 218 00:10:23,960 --> 00:10:27,410 in the idea of who here has ever said I'd love to have an extra 219 00:10:27,590 --> 00:10:31,970 week in the month or a quarter in the year to close that deal, 220 00:10:32,450 --> 00:10:34,400 right? That's what we're talking about here, you know. 221 00:10:34,760 --> 00:10:37,820 Essentially, a quarter of your time, we could find ways to 222 00:10:38,150 --> 00:10:41,830 speed up, get time back, or repurpose, or refocus onto more 223 00:10:41,860 --> 00:10:44,260 beneficial activities. The difference making things in 224 00:10:44,320 --> 00:10:48,760 terms of what that looks like, it could be on harder, more like 225 00:10:48,790 --> 00:10:51,490 in traditional sales activities, there like prospecting, 226 00:10:51,670 --> 00:10:54,970 discovery calls, follow-ups, proposal writing. It could also 227 00:10:55,030 --> 00:10:57,430 be on proving yourself, which is to Richard's point, role 228 00:10:57,490 --> 00:11:03,120 playing. I set up some real-time AI agents last month to help 229 00:11:03,270 --> 00:11:05,850 sales teams embed their new sales methodology, and they were 230 00:11:06,030 --> 00:11:09,690 role-playing scenarios based upon various ICPs they have or 231 00:11:09,750 --> 00:11:11,970 personas they've got within their, within their target 232 00:11:12,030 --> 00:11:14,580 audience. This was to an audience of typically non-sales 233 00:11:14,670 --> 00:11:17,400 people who hate role playing, and they said they got huge 234 00:11:17,490 --> 00:11:19,440 amounts of value out of it because they could do it in a 235 00:11:19,680 --> 00:11:23,390 non, in an environment that was was was comfortable and safe, as 236 00:11:23,450 --> 00:11:26,270 opposed to just doing it live, or with someone human that might 237 00:11:26,300 --> 00:11:30,680 be judging them, coaching both live with coaches, like we do 238 00:11:30,770 --> 00:11:34,070 here at High Sales Coach, but even to some degree coaching, or 239 00:11:34,070 --> 00:11:36,170 at least getting feedback on things that you're doing in 240 00:11:36,290 --> 00:11:39,710 calls and ways you might improve from call to call, and doing 241 00:11:39,740 --> 00:11:42,550 that right now is creating a bot that provides from call to call 242 00:11:42,670 --> 00:11:44,890 guidance on how that next call you're about to do in 10 minutes 243 00:11:44,980 --> 00:11:47,080 could be improved beyond your last one, just in the moment 244 00:11:47,140 --> 00:11:50,860 feedback. There's loads of ways to like start finding time back, 245 00:11:50,980 --> 00:11:53,860 clawing back your time in terms of frankly, if you apply AI 246 00:11:54,100 --> 00:11:56,980 across all and many more areas, you know the world's your 247 00:11:57,130 --> 00:11:59,500 oyster. And I think Richard, you said at the start, which was 248 00:11:59,590 --> 00:12:02,070 like there are so many ways to apply this, you could pretty 249 00:12:02,070 --> 00:12:05,190 much apply it to anything. It's a case of, for most part, people 250 00:12:05,250 --> 00:12:07,560 don't know where to start, and hopefully we'll give you a few 251 00:12:07,590 --> 00:12:10,530 of those guidance points here about ways that you could start 252 00:12:10,590 --> 00:12:14,400 leveraging AI, perhaps beyond the old tried and tested way of 253 00:12:14,670 --> 00:12:17,910 it's my new Google, or I'm going to rewrite this email. Right, 254 00:12:18,060 --> 00:12:19,920 there are much more sophisticated ways to do it. 255 00:12:19,920 --> 00:12:21,860 Ollie Whitfield: All right, so speaking of, I think you kind of 256 00:12:21,860 --> 00:12:24,200 hinted that we want to get to the two or three things that are 257 00:12:24,200 --> 00:12:27,440 the most actionable use cases to try today, but to give a broad 258 00:12:27,530 --> 00:12:30,080 spectrum, Tom, there's a lot of ways we could start. Right, 259 00:12:30,170 --> 00:12:30,230 yeah, 260 00:12:30,320 --> 00:12:32,690 Tom Ridley: there are. So this might replicate your business 261 00:12:32,750 --> 00:12:35,540 perfectly, but it was designed to be a generic sales funnel 262 00:12:35,570 --> 00:12:39,500 that we can all recognise. Down the left-hand side, you can see 263 00:12:39,950 --> 00:12:43,480 a quite a wide variety of actions loosely aligned to that 264 00:12:43,660 --> 00:12:47,350 sales process, but frankly, most of these could have some place 265 00:12:47,860 --> 00:12:51,130 regardless of the stage of the sales cycle that a prospect is 266 00:12:51,220 --> 00:12:53,590 in. On the right-hand side, we've got the impact over there. 267 00:12:53,710 --> 00:12:56,740 So, roughly speaking, what kind of things would we expect to see 268 00:12:56,920 --> 00:12:59,890 from using tools like this? What's the impact potentially on 269 00:12:59,950 --> 00:13:02,850 that stage of the sales cycle, and for any sales leaders or 270 00:13:02,940 --> 00:13:06,120 managers that are on the call, we've also got the strategic use 271 00:13:06,210 --> 00:13:08,790 cases at the top there, and again, none of this is 272 00:13:08,850 --> 00:13:12,090 exhaustive, this is constantly evolving, evolving. We pull out 273 00:13:12,270 --> 00:13:15,120 three of these to have a conversation about today, but 274 00:13:15,210 --> 00:13:19,410 the idea here being, look at the wealth of opportunities to start 275 00:13:19,530 --> 00:13:23,360 leveraging AI that go beyond send an email or research a 276 00:13:23,390 --> 00:13:25,700 prospect, and although we are going to cover, we're going to 277 00:13:25,700 --> 00:13:28,010 dip into those. The way we're going to do it's much more 278 00:13:28,070 --> 00:13:30,380 sophisticated, I imagine, than the ways you've been doing it. 279 00:13:30,440 --> 00:13:34,220 But there are lots of ways to start injecting AI to save you 280 00:13:34,400 --> 00:13:36,470 time, and I think Richard, actually, your example, which 281 00:13:36,560 --> 00:13:39,050 you would have got to your case study had you had a minute or a 282 00:13:39,110 --> 00:13:41,950 minute and a half to finish explaining, it was getting to 283 00:13:42,100 --> 00:13:45,610 some of those, which like strategic or longer term view of 284 00:13:45,820 --> 00:13:49,270 data, which is really, really powerful, which I don't think 285 00:13:49,390 --> 00:13:51,580 probably sales people take the time to think about, for the 286 00:13:51,640 --> 00:13:54,400 most part, in their actions. It's like, done that deal, it's 287 00:13:54,460 --> 00:13:57,250 closed, it's closed one, closed last, doesn't matter, on to the 288 00:13:57,340 --> 00:13:59,680 next deal, on to the next deal, on to the next deal, right? In 289 00:13:59,710 --> 00:14:02,610 pursuit of our targets, AI can help us do that analysis much 290 00:14:02,730 --> 00:14:04,950 faster, and I think it's a great way of using it, particularly as 291 00:14:04,950 --> 00:14:07,740 we end up down this funnel towards the end, and we're into 292 00:14:07,770 --> 00:14:08,100 growing. 293 00:14:08,280 --> 00:14:09,660 Ollie Whitfield: And it's the new and average, or should we go 294 00:14:09,720 --> 00:14:10,410 into the first one? 295 00:14:10,530 --> 00:14:12,810 Richard Smith: Let's, let's get into the first one. I think you 296 00:14:12,840 --> 00:14:16,440 know, I know that we have geared this webinar to the people who 297 00:14:16,560 --> 00:14:18,720 are perhaps kind of sat there thinking, where do I get 298 00:14:18,840 --> 00:14:23,300 started? How do I kind of achieve that level one of of use 299 00:14:23,420 --> 00:14:25,550 case, and hopefully we're going to show that, and I know what 300 00:14:25,580 --> 00:14:29,000 we've got planned for future webinars. This over between now 301 00:14:29,060 --> 00:14:32,090 and the end of the year is more advanced use cases where we can 302 00:14:32,150 --> 00:14:34,730 dive into some of these more complex examples in a bit more 303 00:14:34,790 --> 00:14:35,360 detail. So 304 00:14:35,689 --> 00:14:36,679 Ollie Whitfield: here are the ones we're going to cover. 305 00:14:37,039 --> 00:14:39,859 Research, before we go too much into it, we're going to explain 306 00:14:40,069 --> 00:14:42,069 a little bit of the what's it like today, and I think there's 307 00:14:42,099 --> 00:14:44,799 a bit of a stark truth that we're kind of unaware of. It's a 308 00:14:44,799 --> 00:14:47,649 little bit under our nose. I really like doing research on a 309 00:14:47,679 --> 00:14:50,529 prospect. What I've considered is that I don't like the 310 00:14:50,769 --> 00:14:54,399 researching, I like picking what bit of the research to lean on, 311 00:14:54,609 --> 00:14:57,189 and that's I think the key difference as we come to what is 312 00:14:57,399 --> 00:14:59,949 it like to do research today. So maybe I'll start with Rich to. 313 00:14:59,999 --> 00:15:02,669 Is probably something you can speak really well to. What of 314 00:15:02,699 --> 00:15:04,889 this really stands out to you? What do you do? What takes the 315 00:15:05,009 --> 00:15:07,349 longest? Is it.. you know, how bad of a pain is this at the 316 00:15:07,409 --> 00:15:07,619 minute? 317 00:15:07,680 --> 00:15:09,330 Richard Smith: I think for a lot of people, they haven't actually 318 00:15:09,570 --> 00:15:12,900 sat there and actually realised the extent of the pain. You 319 00:15:12,900 --> 00:15:16,410 know, if I think of how a lot of people research today, for 320 00:15:16,500 --> 00:15:19,650 whether it's they're about to cold call someone, they're about 321 00:15:19,680 --> 00:15:22,910 to jump on a discovery call with a prospect, they're probably 322 00:15:23,300 --> 00:15:25,550 kind of going on the prospect's LinkedIn profile, and they're 323 00:15:25,550 --> 00:15:28,520 probably scouring the profile or trying to pick out something 324 00:15:28,610 --> 00:15:32,750 relevant on the profile. They may even go to the company's 325 00:15:32,840 --> 00:15:36,350 website, and they may even click into the latest news. But here's 326 00:15:36,500 --> 00:15:38,750 the thing, for a lot of people, that's probably where they stop. 327 00:15:38,990 --> 00:15:42,040 They've probably, by that point, spent 1015, minutes and thought, 328 00:15:42,340 --> 00:15:45,970 "Wow, I'm struggling to find anything relevant here, and 329 00:15:46,000 --> 00:15:48,880 their frustration just kind of leads them to just, "I'm just 330 00:15:48,880 --> 00:15:50,980 going to stop there, I'm going to cut corners, I'm just going 331 00:15:50,980 --> 00:15:54,610 to kind of jump on the call with the prospect, and maybe not show 332 00:15:54,730 --> 00:15:57,400 that I've done my research, because they actually spend 1520 333 00:15:57,700 --> 00:16:00,240 minutes and didn't actually find anything. I mean, I'm sure a lot 334 00:16:00,240 --> 00:16:03,450 of people here are sat there thinking of the amount of times 335 00:16:03,540 --> 00:16:06,090 they've, they've started their research, not actually made 336 00:16:06,180 --> 00:16:09,180 progress, and kind of given up, right? You multiply that by the 337 00:16:09,210 --> 00:16:11,760 amount of meetings that you've, that you've got that week, the 338 00:16:11,790 --> 00:16:14,340 amount of calls that you've made, and actually those 15 339 00:16:14,400 --> 00:16:17,550 minutes starts to multiply by, in some cases, a significant 340 00:16:17,580 --> 00:16:21,230 number. So, I think the reality is that for so many people 341 00:16:21,410 --> 00:16:24,470 today, even those who have access to AI tools, their 342 00:16:24,620 --> 00:16:28,670 research is highly manual. It's largely starting, probably on a 343 00:16:28,730 --> 00:16:32,240 prospect's LinkedIn profile. It might extend to their website, 344 00:16:32,330 --> 00:16:34,940 or maybe looking at a couple of notes in the CRM system, but 345 00:16:34,940 --> 00:16:38,000 that's probably where it stops. And a lot of that is because 346 00:16:38,300 --> 00:16:41,350 it's a time commitment, and they get frustrated when they don't 347 00:16:41,410 --> 00:16:44,770 actually find anything relevant or something that they can bring 348 00:16:44,830 --> 00:16:45,700 to the conversation, 349 00:16:45,970 --> 00:16:48,340 Tom Ridley: so I want to just caveat anything I show you 350 00:16:48,460 --> 00:16:52,150 today, whether it's a tool or whether I'm mentioning other 351 00:16:52,240 --> 00:16:56,770 tools, which we'll get to. There is a wide range of expenditure 352 00:16:57,160 --> 00:17:00,160 and time investment into getting some of those up and running, 353 00:17:00,310 --> 00:17:04,590 from nothing free and very little like instantaneous value 354 00:17:05,130 --> 00:17:07,800 to set up time, but huge amounts of value if you take the time to 355 00:17:07,860 --> 00:17:12,150 do it, and obviously with it cost. So, whatever I want to try 356 00:17:12,300 --> 00:17:16,110 to do these things, my general feeling on this guys is that I'm 357 00:17:16,260 --> 00:17:19,590 always about experiment with something cheap, free, prove the 358 00:17:19,740 --> 00:17:22,700 concept first. It might have some manual steps in it. It 359 00:17:22,730 --> 00:17:26,390 might feel a bit clunky. If you're using AI, there is 100% a 360 00:17:26,420 --> 00:17:28,760 way to automate it. And this first one about research 361 00:17:28,850 --> 00:17:32,210 specifically shows that, and the example of automation I show you 362 00:17:32,240 --> 00:17:35,300 is even a super simple one. It can go way beyond that. So, the 363 00:17:35,300 --> 00:17:38,420 first tool I'm going to mention is Perplexity. Perplexity is an 364 00:17:38,450 --> 00:17:41,650 amazing tool. It's just so good. It's been out a long time. I 365 00:17:41,830 --> 00:17:45,340 want to say it's a little over two years now. And essentially, 366 00:17:45,610 --> 00:17:49,000 Perlexi was originally created for in the education space for 367 00:17:49,060 --> 00:17:53,050 people to be able to feed in documentation research papers, 368 00:17:53,080 --> 00:17:56,530 which can be massive in length, and be able to understand the 369 00:17:56,590 --> 00:17:59,320 context of it inside those documents from specific sources, 370 00:17:59,710 --> 00:18:02,370 and then draw conclusions as it's evolved. It's added in 371 00:18:02,490 --> 00:18:05,910 other functionality, like they just came out of a browser that 372 00:18:05,970 --> 00:18:09,060 you can use that rivals Chrome. In some cases, they've added 373 00:18:09,120 --> 00:18:11,040 projects and all this kind of stuff to it. It's really good. 374 00:18:11,190 --> 00:18:13,440 Oh, and they've added creative writing capabilities to it, 375 00:18:13,440 --> 00:18:15,570 which is an important one as well. At its core, it still 376 00:18:15,630 --> 00:18:18,180 remains a research tool, and what's great about it has 377 00:18:18,240 --> 00:18:21,530 citations and amazing features that really just well designed 378 00:18:21,830 --> 00:18:25,310 out of the box for going and doing well or good quality 379 00:18:25,400 --> 00:18:28,760 research? So, if anybody's ever used Chat GPT and Gemini, I can 380 00:18:28,880 --> 00:18:32,270 see Ash does sticks with Chat GPT and Gemini. If you find you 381 00:18:32,330 --> 00:18:35,120 get hallucinations or things that you don't think are quite 382 00:18:35,210 --> 00:18:37,850 true, or where did that data come from, those tools are 383 00:18:37,850 --> 00:18:40,900 better now, but Perplexity actively tries to remove those, 384 00:18:40,960 --> 00:18:44,110 it won't publish you information that's incorrect, for the most 385 00:18:44,170 --> 00:18:46,750 part. All right, the thing I like about Perplexity, you don't 386 00:18:46,840 --> 00:18:50,560 need to share any public data, like personal data or data about 387 00:18:50,590 --> 00:18:53,140 your company. You can just go and research, so there shouldn't 388 00:18:53,170 --> 00:18:56,080 be any issues for you being able to use it in your businesses 389 00:18:56,170 --> 00:18:58,180 today, because you don't have to share any financials or anything 390 00:18:58,180 --> 00:18:59,980 like that if you don't want to, any customer information 391 00:19:00,040 --> 00:19:03,090 specifically. It's faster, and the fact that can go into 392 00:19:03,180 --> 00:19:06,540 websites and scrape them as a whole website instead of having 393 00:19:06,540 --> 00:19:09,600 to point to individual URLs is massive importance. It's a great 394 00:19:09,660 --> 00:19:12,300 research tool. I'm going to share my screen for a second. 395 00:19:12,600 --> 00:19:14,880 So, perplexity.. I'm not going to go.. it's not a deep dive 396 00:19:15,000 --> 00:19:17,550 tour of it. You can come and use it. It's a similar chat 397 00:19:17,610 --> 00:19:20,600 interface to everything else. I have a prompt. It's a good 398 00:19:20,690 --> 00:19:23,870 prompt, I've written much more comprehensive prompts in my day, 399 00:19:24,260 --> 00:19:26,780 but this is a good one to start account planning and account 400 00:19:26,870 --> 00:19:29,960 research, and I'm just going to stick this in. It's on an old 401 00:19:30,110 --> 00:19:33,260 company I used to engage with frequently, so I know them, I 402 00:19:33,260 --> 00:19:35,540 don't know if it's pulling good stuff or not. What I'm doing in 403 00:19:35,540 --> 00:19:38,480 this prompt, real quick, and it's not as not designed to be 404 00:19:38,510 --> 00:19:42,010 about prompt engineering, I'm pushing into perplexity, exactly 405 00:19:42,130 --> 00:19:44,350 what I want. I'm giving it, obviously, a role. We've all 406 00:19:44,500 --> 00:19:47,020 probably seen that in prompt stuff. I'm giving it a singular 407 00:19:47,110 --> 00:19:49,300 URL in this instance for this company Transform 408 00:19:49,360 --> 00:19:52,810 performance.com I'm also feeding in - I'll separate, as you can 409 00:19:52,900 --> 00:19:56,170 see it - the value proposition of my company. So, really 410 00:19:56,200 --> 00:19:58,240 important, when I typically see people engaging with these 411 00:19:58,300 --> 00:20:00,420 tools, they go do me some research. Search on this 412 00:20:00,510 --> 00:20:02,610 company, but what they're not doing is giving it enough 413 00:20:02,700 --> 00:20:06,090 context, it being the AI. So, how can I tell it about me, 414 00:20:06,720 --> 00:20:10,230 about what my business does, what we sell, what our typical 415 00:20:10,920 --> 00:20:12,690 ICP or persona might look like? 416 00:20:13,350 --> 00:20:16,350 The all of that stuff is super relevant for giving the AI 417 00:20:16,590 --> 00:20:20,070 context for what good would look like. You could even say this is 418 00:20:20,190 --> 00:20:22,340 what good would look like, and give actual examples, but that 419 00:20:22,430 --> 00:20:25,130 context is massively important, and if there's something to 420 00:20:25,220 --> 00:20:28,130 elevate your prompting, regardless of this, it's giving 421 00:20:28,220 --> 00:20:32,300 it context about what you would do or what you want to see, see 422 00:20:32,360 --> 00:20:35,480 it take into account when doing its activity. And then the 423 00:20:35,480 --> 00:20:38,870 second part of this is the structured brief, obviously you 424 00:20:38,930 --> 00:20:41,710 can change this to be whatever works for you, right, but the 425 00:20:41,860 --> 00:20:44,260 idea here is I'm being very, very clear about what I want 426 00:20:44,320 --> 00:20:46,750 from this. I want to have a company overview, I want their 427 00:20:46,780 --> 00:20:49,960 products and services, who they target, any recent news, all 428 00:20:50,020 --> 00:20:52,420 that kind of stuff. Okay, plunk that into here, and I'm just 429 00:20:52,420 --> 00:20:56,260 gonna hit go quite rapidly. You can now see that I have a 430 00:20:57,100 --> 00:20:59,800 relatively comprehensive plan about this organisation. What I 431 00:20:59,860 --> 00:21:02,970 love about perplexity is a fact. I could, they can now do a deep 432 00:21:03,030 --> 00:21:06,150 dive if I wanted to, right? Yes, I can ask follow-up questions, I 433 00:21:06,180 --> 00:21:10,530 can go into more, more detail, but I've also got citations for 434 00:21:10,560 --> 00:21:13,200 exactly where this information is being pulled from. So this is 435 00:21:13,260 --> 00:21:16,410 being pulled directly from their website, and I can see all my 436 00:21:16,530 --> 00:21:18,990 sources and everything sitting up here that I want to delve 437 00:21:19,020 --> 00:21:22,130 into deeper. Go and have a play perplexity is excellent, 438 00:21:22,550 --> 00:21:25,520 particularly for doing things like well, you've mentioned this 439 00:21:25,610 --> 00:21:27,950 thing here, and I want to go into some follow-up questions 440 00:21:28,100 --> 00:21:30,710 around the area, much more rapid, and the key thing for me 441 00:21:30,830 --> 00:21:34,850 here is this has searched for 20, gone through 20 sources in 442 00:21:34,880 --> 00:21:37,910 this instance and looked for that insight, I have that prompt 443 00:21:38,000 --> 00:21:40,750 saved up, I can just chuck that prompt in and start researching 444 00:21:40,780 --> 00:21:42,850 that prospect. Shane's asked the next question, which is 445 00:21:42,910 --> 00:21:46,420 pre-empting, so somewhat prophetic. There, Shane, and 446 00:21:46,480 --> 00:21:49,150 that was coming next. Perplexity has this built-in thing called 447 00:21:49,240 --> 00:21:53,140 spaces. This space has custom instructions. If I come up to my 448 00:21:53,230 --> 00:21:56,140 custom instructions, there's my prompt in here. I've actually 449 00:21:56,230 --> 00:21:59,890 given it the value proposition, so anytime I post a link into 450 00:22:00,160 --> 00:22:03,180 here, I'm going to be then generating account plans or 451 00:22:03,270 --> 00:22:06,780 research, we're going to call it with that same prompt, and I'm 452 00:22:06,870 --> 00:22:13,020 just sending the instructions into here, research https form 453 00:22:13,110 --> 00:22:16,020 performance, and it should just run. It goes for the same 454 00:22:16,110 --> 00:22:18,210 process, might be a slightly different output, because I'm 455 00:22:18,330 --> 00:22:20,840 going in for a second time and having a bit of a conversation 456 00:22:20,870 --> 00:22:23,270 with it, but same thing. Fact, it actually found more sources 457 00:22:23,300 --> 00:22:27,710 this time. So, the point is you can reuse it, and now all of 458 00:22:27,770 --> 00:22:30,290 these, all of these searches are saved, and it will appear here 459 00:22:30,350 --> 00:22:32,930 shortly when it's finished. But all of my account planning or 460 00:22:33,200 --> 00:22:35,750 research will be stored in this space. For anybody wanting to 461 00:22:35,810 --> 00:22:38,240 take this one step further, I've got a Google spreadsheet. This 462 00:22:38,300 --> 00:22:41,050 could be your CRM, like HubSpot. I mentioned about connecting to 463 00:22:41,080 --> 00:22:44,260 an API, and any tool can do it. A tool has an API, and all of 464 00:22:44,350 --> 00:22:46,630 the AI tools do it. You can connect that system without you 465 00:22:46,660 --> 00:22:48,610 guys ever having to lift a finger. This could be 1000 466 00:22:49,450 --> 00:22:52,180 records, it could be 10,000 records in your system. If we 467 00:22:52,330 --> 00:22:55,690 want to go and research them, I simply would allow an AI to go 468 00:22:55,780 --> 00:22:58,180 and access it. You know, I'm not putting any prompts, that's what 469 00:22:58,180 --> 00:23:00,990 we trained in the back end, and in a second, you'll suddenly see 470 00:23:01,350 --> 00:23:04,200 information just appearing in those cells for that AI research 471 00:23:04,320 --> 00:23:07,260 for those two organisations sitting in my sheet. The first 472 00:23:07,260 --> 00:23:10,770 step in this is AI is a research tool, get the information, it's 473 00:23:10,920 --> 00:23:13,800 massively powerful in terms of getting us insight, which we can 474 00:23:13,860 --> 00:23:15,720 then use in further steps, whether we want to do those 475 00:23:15,810 --> 00:23:17,970 manually or we want to do it with AI. As you can see here, 476 00:23:18,030 --> 00:23:20,100 it's pulled through that information directly into the 477 00:23:20,130 --> 00:23:23,180 into a spreadsheet, no effort required from the salesperson. 478 00:23:23,330 --> 00:23:23,390 Richard Smith: Wow, 479 00:23:23,780 --> 00:23:25,640 Ollie Whitfield: things you like to see, huh? Personalization. 480 00:23:25,850 --> 00:23:26,810 Let's go rich. 481 00:23:27,080 --> 00:23:28,460 Richard Smith: For a lot of people, if they're honest to 482 00:23:28,490 --> 00:23:30,680 themselves, they don't personalise, right, because 483 00:23:31,190 --> 00:23:34,820 personalization is timely. But again, we're kind of going 484 00:23:34,910 --> 00:23:37,490 through the same exercise as before, right? Like for 485 00:23:37,550 --> 00:23:40,040 research, we're probably clicking into prospects' 486 00:23:40,130 --> 00:23:42,670 LinkedIn profiles, we're probably clicking on the button 487 00:23:42,700 --> 00:23:46,000 that says recent posts. We're probably scrolling through posts 488 00:23:46,090 --> 00:23:49,090 and looking at what they've posted about. Again, we're maybe 489 00:23:49,180 --> 00:23:52,390 looking at things like, oh, we're clicking on their jobs, 490 00:23:52,570 --> 00:23:54,940 clicking, seeing if there's a, there's a, there's a jobs board 491 00:23:55,030 --> 00:23:57,820 for them, looking at, are they hiring right now. And then, for 492 00:23:57,820 --> 00:23:59,950 a lot of people, they might access things like, you know, 493 00:24:00,160 --> 00:24:03,240 earnings reports, financial reports, and kind of scrolling 494 00:24:03,330 --> 00:24:05,640 through those things to identify, here's there's 495 00:24:05,670 --> 00:24:08,730 something in here that I can pull out to kind of personalise 496 00:24:08,880 --> 00:24:12,390 my approach to this prospect. Again, this stuff is like we're 497 00:24:12,450 --> 00:24:16,320 all doing it today, but we're probably not aware of how much 498 00:24:16,500 --> 00:24:19,620 time we're sinking and doing this for every single prospect 499 00:24:19,620 --> 00:24:22,460 we're engaging with, and yeah, like, for me, this is kind of 500 00:24:22,580 --> 00:24:26,510 how I, how I do it today, right? Well, before I used AI, this is 501 00:24:26,600 --> 00:24:29,960 exactly how I, how I was doing it. It might take me sometimes 502 00:24:30,500 --> 00:24:32,690 10 minutes just to find something relevant that the 503 00:24:32,780 --> 00:24:35,540 prospects posted about on LinkedIn in the past three 504 00:24:35,630 --> 00:24:38,900 months, to so that I can, I can reference something when I, when 505 00:24:38,930 --> 00:24:39,500 I contact them. 506 00:24:39,740 --> 00:24:40,850 Ollie Whitfield: All right, Tom, should we show them how it's 507 00:24:40,910 --> 00:24:41,000 done? 508 00:24:41,360 --> 00:24:42,940 Tom Ridley: Show them how it's done. Is what they are one way 509 00:24:43,000 --> 00:24:44,530 it could be done, because there's always more than one 510 00:24:44,560 --> 00:24:44,620 way. 511 00:24:44,769 --> 00:24:45,279 Ollie Whitfield: Some of the ways, 512 00:24:45,700 --> 00:24:47,560 Tom Ridley: so two tools here, very different ends of the 513 00:24:47,590 --> 00:24:50,740 spectrum. And actually, it was a great example of how fast the AI 514 00:24:50,920 --> 00:24:53,740 space moves. When I started presenting these slides, 515 00:24:54,010 --> 00:25:00,810 reggie.ai was a browser plugin, and now it is a full AI. I layer 516 00:25:01,140 --> 00:25:04,590 that sits for the most part in enterprise grade software, so 517 00:25:05,370 --> 00:25:08,100 it's crazy how fast the space moves. Tuesday is a slightly 518 00:25:08,100 --> 00:25:11,040 different tool, so we'll jump into both those tools in a.. I 519 00:25:11,070 --> 00:25:12,990 think the next slide shows it, and in the interest of time, we 520 00:25:13,050 --> 00:25:15,720 can probably just jump to it. So, both of these tools, it can 521 00:25:15,750 --> 00:25:18,000 be used to create personalised messaging. All personalised 522 00:25:18,030 --> 00:25:20,870 messaging comes from the kind of same concept, which is to my 523 00:25:20,930 --> 00:25:23,750 perplexity point earlier, the more context you can feed an AI, 524 00:25:24,410 --> 00:25:26,450 the more personalised you can make the message. So that 525 00:25:26,570 --> 00:25:28,970 research that we did in perplexity a moment ago, that 526 00:25:29,090 --> 00:25:33,500 would be context and information we would feed into a - I'll give 527 00:25:33,560 --> 00:25:37,580 it a quote - personalization engine. Okay, but also prospects 528 00:25:37,640 --> 00:25:41,170 websites, broader Google searches, you can scrape 529 00:25:41,440 --> 00:25:44,230 people's LinkedIn pages, I'm sure she won't mind me saying 530 00:25:44,350 --> 00:25:47,590 it, but Nia, my sales coach, and I were working on a project for 531 00:25:47,590 --> 00:25:51,820 the last few weeks on scraping insights out of the My Sales 532 00:25:51,910 --> 00:25:54,310 Coach posts that they're making in the business and 533 00:25:54,310 --> 00:25:57,280 understanding the engagement on those, that's all context, so 534 00:25:57,820 --> 00:26:00,240 both of these tools operate in a similar way in the sense that 535 00:26:00,270 --> 00:26:03,960 they harness multiple data sources, and then they use that 536 00:26:04,020 --> 00:26:07,890 to start writing emails or writing communications in your 537 00:26:08,220 --> 00:26:11,460 tone of voice with your value proposition in mind, and with 538 00:26:11,460 --> 00:26:14,280 your target, and specifically with your target prospect. So, 539 00:26:14,550 --> 00:26:16,740 on the left-hand side, we've got Reggie, so it's an 540 00:26:16,830 --> 00:26:20,190 enterprise-grade AI enrichment tool designed to work around 541 00:26:20,310 --> 00:26:24,320 multiple areas of knowledge, CRMs, SharePoints, all this 542 00:26:24,350 --> 00:26:26,450 stuff, it can pull that together. Tuesday is a bit more 543 00:26:26,540 --> 00:26:29,330 light touch, and it's a tool that you can force a load of 544 00:26:29,510 --> 00:26:32,780 data into in one go, 1000s of contacts, and it will go and 545 00:26:32,900 --> 00:26:35,450 directly work with what's on LinkedIn and start creating 546 00:26:35,480 --> 00:26:38,180 using content based on what's on their profile. So, both really 547 00:26:38,210 --> 00:26:41,260 nice tools, but if you want to start doing this with Chat GPT 548 00:26:41,410 --> 00:26:44,080 or an equivalent today, then you can. What you need is that 549 00:26:44,170 --> 00:26:49,450 context. So the research from Segaplexity put into a folder on 550 00:26:49,960 --> 00:26:55,120 or a project in say Chat GPT or the same equivalent in Claude or 551 00:26:55,240 --> 00:26:57,730 Gemini. If you did that documentation around what your 552 00:26:57,760 --> 00:27:02,010 value proposition is, what your standard sales emails look like 553 00:27:02,070 --> 00:27:04,110 in terms of the ones that are good that get good response 554 00:27:04,230 --> 00:27:06,390 rates, so it gives it an idea of what good looks like for the 555 00:27:06,450 --> 00:27:09,600 business. Put all of that in a project and then start giving it 556 00:27:09,690 --> 00:27:13,170 some specific context on on chats that you have around, I 557 00:27:13,260 --> 00:27:15,540 want to write an email for this customer, and this is the 558 00:27:15,540 --> 00:27:17,670 information I'm going to, this is the information I've got, and 559 00:27:17,700 --> 00:27:20,600 some chucking some specific documentation into there, so you 560 00:27:20,690 --> 00:27:23,480 can create your own simpler versions of these tools, which I 561 00:27:23,510 --> 00:27:26,270 said are a bit more manual, but would deliver huge amounts of 562 00:27:26,300 --> 00:27:29,720 value, and when you start to see that they are generating you 563 00:27:29,780 --> 00:27:32,390 benefits in terms of the quality output that you get to, the 564 00:27:32,390 --> 00:27:34,400 better, and you can start to scale those to give you an 565 00:27:34,400 --> 00:27:36,440 example of some of the things that I would prompt for in 566 00:27:36,470 --> 00:27:39,680 these, I would be looking for where prospects are using 567 00:27:39,770 --> 00:27:41,890 language that would align directly with my value 568 00:27:41,920 --> 00:27:46,330 proposition, so if I - I'm an AI company, right? So if I - if I'm 569 00:27:46,450 --> 00:27:49,060 looking at an organisation, thinking, are they wired the way 570 00:27:49,300 --> 00:27:51,760 I am, it's like things that they say, where they say, where they 571 00:27:51,880 --> 00:27:54,220 mention things like we're at the cutting edge of something, and 572 00:27:54,490 --> 00:27:57,700 or we're entrepreneurial stuff like that, they're perfect terms 573 00:27:57,790 --> 00:27:59,830 for me, because I'd latch on to those. 574 00:28:00,040 --> 00:28:03,420 If someone's, if an organisation has traditional, that's not 575 00:28:03,600 --> 00:28:06,390 necessarily the best language that I would want to be writing 576 00:28:06,480 --> 00:28:08,520 to. So, if I've got to change the way that I might read my 577 00:28:08,550 --> 00:28:10,860 communication, or maybe actually don't even send an email them at 578 00:28:10,920 --> 00:28:13,560 all, you get the idea about it's trying to get to that nuanced 579 00:28:13,710 --> 00:28:16,110 level with all the information we can feed into it, and then 580 00:28:16,230 --> 00:28:19,350 using that information to then create truly personalised emails 581 00:28:19,380 --> 00:28:21,950 that you would write if you had 30 minutes per email, 582 00:28:22,220 --> 00:28:25,370 Richard Smith: yeah, I think an example for our company is like 583 00:28:25,610 --> 00:28:29,060 in looking for people's on their LinkedIn profiles where they're 584 00:28:29,210 --> 00:28:32,000 referencing things like coaching or development of people is 585 00:28:32,060 --> 00:28:34,520 important to them, they're the people that are gonna most 586 00:28:34,640 --> 00:28:37,550 resonate with our proposition, they're the people that we want 587 00:28:37,550 --> 00:28:40,810 to profile as like higher priority, higher priority 588 00:28:41,290 --> 00:28:43,870 prospects beyond just what a lot of people are searching for, 589 00:28:43,870 --> 00:28:47,470 which is, you know, hey, I'm looking for these accounts or 590 00:28:47,560 --> 00:28:51,250 companies of this size or this job title, like, which is great, 591 00:28:51,310 --> 00:28:53,440 right? That's a good starting point, but how do you actually 592 00:28:53,710 --> 00:28:56,920 become more focused on the people who I think you use the 593 00:28:56,920 --> 00:29:00,160 phrase wired the same way as you, wired the same way as you, 594 00:29:00,340 --> 00:29:02,580 they're going to be easier to get on your side when it comes 595 00:29:02,640 --> 00:29:03,360 to approaching them, 596 00:29:03,540 --> 00:29:05,490 Ollie Whitfield: right, chaps. I'll move us on then. So, last 597 00:29:05,490 --> 00:29:07,740 thing here, I think this one maybe, maybe you disagree, Tom. 598 00:29:08,190 --> 00:29:10,470 Does this play a little bit more toward the sales leader point of 599 00:29:10,470 --> 00:29:12,690 view? I get it, could well be both, but is this not that 600 00:29:12,720 --> 00:29:12,990 country? 601 00:29:13,290 --> 00:29:15,210 Tom Ridley: No, I actually think, and I'm not even gonna.. 602 00:29:15,660 --> 00:29:18,090 this isn't.. I don't think it's a hyperbole, so it's an opinion 603 00:29:18,150 --> 00:29:22,010 status of fact. I think call analysis, whether that's video 604 00:29:22,130 --> 00:29:25,640 or just the audio transcript, is probably the most valuable thing 605 00:29:25,790 --> 00:29:28,760 in the sales or the piece of data you can have in the sales 606 00:29:28,820 --> 00:29:32,030 function and customer success, and the reason is it contains a 607 00:29:32,150 --> 00:29:35,660 wealth of data that up until AI was really difficult to get, so 608 00:29:36,110 --> 00:29:36,800 not just for leaders. 609 00:29:37,130 --> 00:29:38,360 Ollie Whitfield: All right, well, Rich, talk to us about 610 00:29:38,420 --> 00:29:40,340 what it's like today, and we'll get, we'll crack on to do. 611 00:29:40,760 --> 00:29:41,680 Richard Smith: Yeah, well, I think the thing, what's 612 00:29:41,740 --> 00:29:44,380 interesting is that probably most people on here are probably 613 00:29:44,470 --> 00:29:47,110 using some kind of like call transcription, call 614 00:29:47,590 --> 00:29:51,190 summarization type technology. Think for me that the challenge 615 00:29:51,220 --> 00:29:53,920 is that they're probably not capitalising on what they could 616 00:29:53,950 --> 00:29:56,980 actually do with that technology, and for a lot of 617 00:29:57,070 --> 00:29:59,740 people, they, they may still be watching about their calls one 618 00:29:59,770 --> 00:30:03,090 by. On in full, they may be missing some key context. They 619 00:30:03,180 --> 00:30:05,730 may be, they may still be making notes from their calls. They may 620 00:30:05,880 --> 00:30:09,090 still be trying to self-identify mistakes within the calls, but 621 00:30:09,090 --> 00:30:11,070 actually, from experience, most people aren't even doing that. 622 00:30:11,310 --> 00:30:13,860 Most people aren't reflecting back on, "Hey, where did I go 623 00:30:14,130 --> 00:30:16,860 wrong in my last call? They're also doing, like, follow-ups to 624 00:30:16,950 --> 00:30:19,530 calls, and some people still aren't even using kind of these 625 00:30:19,650 --> 00:30:23,570 tools to create great summary emails. I'm actually excited on 626 00:30:23,840 --> 00:30:26,090 the next slide to share some of the ways that I'm actually using 627 00:30:26,450 --> 00:30:30,770 call analysis, and some share some examples of where perhaps 628 00:30:30,830 --> 00:30:32,870 what you're not doing today, which you could be doing, but 629 00:30:32,900 --> 00:30:35,150 for again, for a lot of people that probably they have access 630 00:30:35,210 --> 00:30:37,190 to this, they're just probably not doing a lot with it, and 631 00:30:37,190 --> 00:30:40,630 it's kind of probably harming their effectiveness and 632 00:30:40,690 --> 00:30:41,770 productivity, Tom. 633 00:30:41,980 --> 00:30:42,490 Ollie Whitfield: Over to you, mate. 634 00:30:42,700 --> 00:30:43,870 Richard Smith: Yeah, I'll go, go, go for Tom. 635 00:30:44,230 --> 00:30:46,990 Tom Ridley: So we can probably rattle through sides, because I 636 00:30:47,080 --> 00:30:49,660 think we're just right. Most of us will probably have some level 637 00:30:49,660 --> 00:30:52,270 of cool note taker now. If you don't, sometimes I turn up to 638 00:30:52,330 --> 00:30:54,160 things I'm testing them, and I've got five, and it's me 639 00:30:54,310 --> 00:30:56,410 joining, so it's a bit outnumbering for me, or 640 00:30:56,440 --> 00:30:59,890 whoever's joining my calls. Gong and sales loft, and I want 641 00:30:59,920 --> 00:31:02,820 labour on these. I think the big thing across the spectrum of 642 00:31:02,910 --> 00:31:05,910 note takers is that when they first came to the market, they 643 00:31:06,000 --> 00:31:07,890 were good, but people didn't necessarily know how to use 644 00:31:08,070 --> 00:31:11,160 them. We have seen an abundance of these things pop up in other 645 00:31:11,220 --> 00:31:14,730 technology, like for example, Apollo added a note taker some 646 00:31:14,790 --> 00:31:17,490 time ago now, but they added a note taker because they 647 00:31:17,910 --> 00:31:20,870 recognised that a lot of SDRs were wanting that kind of 648 00:31:20,990 --> 00:31:23,660 functionality at their end of the sales cycle, it wasn't just 649 00:31:23,780 --> 00:31:26,180 probably where I've been focused a little bit more towards the 650 00:31:26,510 --> 00:31:28,850 in-flight deals and account management type stuff. 651 00:31:29,000 --> 00:31:31,250 Historically, we have tools now that can actually give you 652 00:31:31,760 --> 00:31:35,600 real-time guidance and playbook information, if you want to have 653 00:31:35,690 --> 00:31:38,000 it. They're more expensive, but you can get them. The point is, 654 00:31:38,150 --> 00:31:40,240 it doesn't matter what AI tool that you're using or 655 00:31:40,300 --> 00:31:42,580 transcribing with even if you don't get access to that 656 00:31:42,640 --> 00:31:45,130 transcription until after the call, what matters is that 657 00:31:45,220 --> 00:31:48,910 you've got now a huge amount of data that you can use for a 658 00:31:48,940 --> 00:31:51,430 variety of purposes. The key thing for me is thinking about 659 00:31:51,550 --> 00:31:54,190 how you want to leverage those tools in your workflow. Let's 660 00:31:54,220 --> 00:31:57,040 say you're an SDR using these tools, or someone that focuses 661 00:31:57,040 --> 00:31:59,410 on the qualification, the early stage of the sales cycle, then, 662 00:31:59,800 --> 00:32:02,490 like Rich was saying, you want to be using those calls to 663 00:32:02,610 --> 00:32:05,130 analyse scale what you're doing, you want to be looking for 664 00:32:05,220 --> 00:32:08,100 trends in the way that you're doing things, possibly not an 665 00:32:08,250 --> 00:32:11,550 individual call to call situation, but what are you 666 00:32:11,580 --> 00:32:14,040 doing over a period of time. So you need to take all those 667 00:32:14,100 --> 00:32:17,670 transcripts and feed that into a project within Chat GPT or some 668 00:32:17,790 --> 00:32:20,930 form of AI tool to analyse what's going on inside of your 669 00:32:20,990 --> 00:32:25,370 calls at large, counter to that, if I was, say, you know, working 670 00:32:25,460 --> 00:32:29,120 on enterprise level deals of six to 12 month sales cycles, I've 671 00:32:29,180 --> 00:32:31,520 probably got lots of long meetings in there, which could 672 00:32:31,550 --> 00:32:34,310 be hour, hour and a half, even two hours at times. There's 673 00:32:34,460 --> 00:32:37,370 loads of subtlety and nuance. There's multiple stakeholders 674 00:32:37,430 --> 00:32:39,830 that I'm dealing with. I need to use that tool in a very 675 00:32:39,920 --> 00:32:42,700 different way. So, yes, the meeting minutes are great, and 676 00:32:42,730 --> 00:32:45,250 understanding what I said is great, but actually what's 677 00:32:45,310 --> 00:32:48,760 better is maybe to use that tool to do a stakeholder profiling 678 00:32:48,790 --> 00:32:52,030 all the time to say, well, what was head of procurement saying 679 00:32:52,090 --> 00:32:55,030 and doing whilst I was talking about the topic, oh, and also 680 00:32:55,120 --> 00:32:58,540 head of HR or head of sales, whoever we're selling to, what 681 00:32:58,570 --> 00:33:00,660 were they doing, and use the calls in a much more 682 00:33:00,720 --> 00:33:03,450 sophisticated way, beyond just I've got some notes and some 683 00:33:03,540 --> 00:33:06,870 actions, it's how can I use the information or the knowledge I 684 00:33:06,960 --> 00:33:09,720 gathered during that, that time where I was on a call, the most 685 00:33:09,810 --> 00:33:12,840 valuable time we have with prospects and customers to my 686 00:33:12,900 --> 00:33:15,300 advantage, and use it in multiple different ways across 687 00:33:15,630 --> 00:33:17,490 my sales cycle or across my business. 688 00:33:17,760 --> 00:33:20,010 Richard Smith: Two valuable use cases that I find really 689 00:33:20,100 --> 00:33:24,440 powerful with this is using the cold transcripts to create, I 690 00:33:24,500 --> 00:33:27,170 call them like what I heard you say slides for my next meetings 691 00:33:27,230 --> 00:33:30,680 or demos. I kind of taught Chat GBT. This is the format I would 692 00:33:30,740 --> 00:33:33,410 like these slides to look, which is your situation, your 693 00:33:33,530 --> 00:33:37,610 challenges, the impact, so it understands the structure of the 694 00:33:37,700 --> 00:33:40,570 slide. I just take the transcript, put in a Chat GBT, 695 00:33:40,660 --> 00:33:44,080 and it will actually create me my slide into those different 696 00:33:44,170 --> 00:33:47,020 categories that I use to start off my next calls with my 697 00:33:47,110 --> 00:33:49,630 prospects, so it's got the structure that I like. That 698 00:33:49,810 --> 00:33:53,710 exercise used to take me in some cases 30 minutes, 45 minutes, 699 00:33:53,830 --> 00:33:56,320 essentially listening back to the entire call to build those 700 00:33:56,380 --> 00:33:58,960 slides. It now takes me literally less than a minute, 701 00:33:59,200 --> 00:34:02,250 again makes me look super diligent, super prepared for the 702 00:34:02,340 --> 00:34:05,610 meetings. The second one is I like to use this for messaging, 703 00:34:05,910 --> 00:34:08,130 so sales people were trying to constantly find what messaging 704 00:34:08,130 --> 00:34:10,140 is going to land best by prospects, maybe from a 705 00:34:10,200 --> 00:34:13,170 prospecting point of view. So, what I can do now is take my 706 00:34:13,410 --> 00:34:17,730 call transcripts and get AI to essentially analyse what were 707 00:34:17,760 --> 00:34:21,650 the biggest problems, the most common problems, the quotations 708 00:34:21,770 --> 00:34:24,530 of my prospects being used across these calls, where 709 00:34:24,560 --> 00:34:27,740 they're describing the problems that they're experiencing, and 710 00:34:27,740 --> 00:34:31,550 that messaging essentially becomes my best prospecting 711 00:34:31,610 --> 00:34:34,310 messaging, because it's coming from the voice of my prospect, 712 00:34:34,340 --> 00:34:37,040 and I'm able to kind of amalgamate that across multiple 713 00:34:37,130 --> 00:34:39,890 calls. So, yeah, there's two use cases that you can use for kind 714 00:34:39,920 --> 00:34:42,100 of making yourself look more better prepared for your, for 715 00:34:42,190 --> 00:34:44,350 your meetings with prospects, but also helping you with your 716 00:34:44,440 --> 00:34:45,070 messaging as well. 717 00:34:45,280 --> 00:34:46,600 Ollie Whitfield: All right, guys, I'm going to go for about 718 00:34:46,780 --> 00:34:49,180 half a minute. An answer, I got three or four to give you. Tom, 719 00:34:49,270 --> 00:34:52,120 first, is it fair to say Reggie and Tuesday are more designed 720 00:34:52,150 --> 00:34:54,460 for B2B? What if B2C is an option? 721 00:34:54,729 --> 00:34:56,679 Tom Ridley: Oh, God, good question. In the B2B to B2C, I 722 00:34:56,799 --> 00:35:00,359 said caveat across all tech in this space is that you. To find 723 00:35:00,479 --> 00:35:03,119 the one that works best for the way that your business operates, 724 00:35:03,179 --> 00:35:05,519 and that's the great thing about AI, you can always find 725 00:35:05,549 --> 00:35:09,299 something that is that works for your specific business. I never 726 00:35:09,509 --> 00:35:11,549 recommend a tool and say you shouldn't look at others. Of 727 00:35:11,669 --> 00:35:15,269 those two, I wouldn't recommend Reggie, because it's just 728 00:35:15,269 --> 00:35:18,119 because it's an enterprise level tool. I think that's overkill, 729 00:35:18,179 --> 00:35:23,239 if you're, if you are B to C, probably Tuesday or although you 730 00:35:23,299 --> 00:35:25,579 might find that there's a custom solution or another solution out 731 00:35:25,609 --> 00:35:26,419 the marketplace. It's better. 732 00:35:26,600 --> 00:35:28,250 Ollie Whitfield: Very good. I'll go rich. Do you think that 733 00:35:28,250 --> 00:35:31,370 there'll be repercussions for using AI-created openers or 734 00:35:31,430 --> 00:35:34,550 content that are sensed by the receiver? How can we keep 735 00:35:34,640 --> 00:35:35,960 authenticity while using AI? 736 00:35:36,140 --> 00:35:38,090 Richard Smith: Yeah, absolutely. If you sound like everybody 737 00:35:38,210 --> 00:35:40,870 else, doesn't matter if it's AI-generated or it's, you know, 738 00:35:41,560 --> 00:35:44,830 something that's been recommended on LinkedIn. If it 739 00:35:44,830 --> 00:35:49,330 becomes the norm, then it starts to become recognised as the norm 740 00:35:49,390 --> 00:35:51,670 by our prospects. So, I think what you need to look at AI is 741 00:35:51,670 --> 00:35:55,300 it gives you the, it gives you a much quicker starting point. 742 00:35:55,330 --> 00:35:58,690 It's about how you layer on your human authenticity, your 743 00:35:58,840 --> 00:36:02,430 tonality, or your own spin on things, which will keep the 744 00:36:02,520 --> 00:36:07,890 human element to it, so don't just use AI output, use it as 745 00:36:08,010 --> 00:36:11,220 like the big structure of the house is already built, you just 746 00:36:11,250 --> 00:36:15,690 want to add in your adding your own flavour to it to ensure that 747 00:36:15,750 --> 00:36:18,210 you're remaining authentic and differentiated to your 748 00:36:18,270 --> 00:36:18,690 prospects. 749 00:36:18,930 --> 00:36:21,140 Tom Ridley: Can I just add to that as well, which is a common 750 00:36:21,230 --> 00:36:24,500 thing about AI in general. AI is not the issue if you're getting 751 00:36:24,650 --> 00:36:27,440 people reacting to what you're saying to them in a negative 752 00:36:27,530 --> 00:36:30,590 way. The AI isn't the problem the way you're prompting that AI 753 00:36:30,770 --> 00:36:34,160 is, and what you're asking it to do. If I remove the word AI, for 754 00:36:34,220 --> 00:36:38,240 example, and said junior salesperson is making these 755 00:36:38,330 --> 00:36:41,350 calls, like has told me to say this, or my assistant, or 756 00:36:41,410 --> 00:36:43,750 something like that, we wouldn't, we wouldn't label it 757 00:36:43,780 --> 00:36:46,330 that way, we just say our message isn't very good, and so 758 00:36:46,540 --> 00:36:48,460 there's an expectation, because it's an AI, it should be 759 00:36:48,550 --> 00:36:51,460 perfect, it's only as good as the information we give it and 760 00:36:51,580 --> 00:36:54,280 what we train on it and ask it to do, so if you're not getting 761 00:36:54,280 --> 00:36:57,430 good results, consider switching things up, because just like if 762 00:36:57,640 --> 00:36:59,980 I use the same sales script I used five years ago, that 763 00:37:00,070 --> 00:37:03,600 wouldn't resonate today. You have to evolve, and so therefore 764 00:37:03,600 --> 00:37:06,300 the way that we prompt and work with the AI has to evolve as 765 00:37:06,330 --> 00:37:06,420 well, 766 00:37:10,379 --> 00:37:10,439 Unknown: you.