Why Enterprise Site Search is Hard for IT Teams Let's face it, managing a large,…
In this episode Steve Zakur and I are curious about the ways AI can be used to drive greater value for your company. We have our opinions about our own software of course, but this is a bigger question: how can you use AI to make your entire team and business smarter?
What companies need to think about right now is AI augmentation — augmenting decision making. Sometimes we’re thinking way too big about AI, instead of in a targeted fashion about what it can do for us now. This is the importance of practical AI.
A ChiefMartec piece recently asked if martech stack utilization is a misguided metric. If your stack is disconnected from value, it might be. Make sure the value is measurable and make sure the data can integrate. Does that end result provide value?
When what you have is a hammer, everything looks like a nail. You can’t look to the stack to save you in every situation. Good stacks are important, but if you aren’t pointing your marketing stack in the right direction or thinking about what you need it to do for you, you’re going to struggle.
1:50 The rise of practical AI
12:35 Stack utilization is a misguided metric
21:05 The stack won’t save you
SearchChat is available on
Search Chat is SoloSegment’s podcast dedicated to all things search AI and content marketing related. Who is SoloSegment? We’re a technology company focused on site search analytics and AI driven content discovery to improve search results, increase customer satisfaction and unlock revenue for your company. If you think we might have the answer to your conversion problems, feel free to connect with us.
Tim: Hi, I’m Tim Peter and welcome to SearchChat. SoloSegments’ podcast dedicated to all things search, AI and content marketing related who is SoloSegment? Well, we’re a technology company focused on site search analytics and AI driven content discovery to improve search results, increase customer satisfaction and to unlock revenue for your company. SoloSegment, make your search smarter. You can learn more at solosegment.com. In this episode of search chat, SoloSegment CEO’s Steve Zakur and I talk about the value of artificial intelligence and how you can use AI to drive greater value for your company. We also talk about intelligence augmentation and how you can use artificial intelligence to make your team smarter too. All that and more coming at you on the latest episode of SoloSegment’s SearchChat right about now.
Tim: Well, hi Steve. How are you doing today?
Steve: I’m doing well, Tim. I got my coffee. Some morning recording. I know we’re not supposed to show people behind the curtain what’s going on, but we’re usually afternoon recorders and now we’re in the morning so it’s a little bit of an adjustment, but I think we’re going to survive with plenty of caffeine.
Tim: Absolutely. And I think it’s going to give us our voices that deeply resonant frequency. That radio vibe. It’s like the overnight DJ. Steve: That’s right. That’s right.
Tim: You’re listening to the Loveline. All right, well coffee in hand and love of great technology and digital and search discussions in front of us. Why don’t we just go ahead and dive in. You shared a fascinating link with me from our friends at Georgian Partners about how even with AI, great is the enemy of good enough. Really, really interesting podcast episode and I’d just love to get your take on it. Maybe you can recap what they talked about. Talk a little bit about what you took away from it. Steve: Yeah. So a first, the shameless plug for our pals at Georgia Partner, John Prial, who’s an advisor to SoloSegment does this podcast. And it is definitely one of those stealth podcasts. It’s really great cause John, not only does have a great interview style, but he does have a very interesting point of view, which is kind of Georgia Partner’s point of view as far as investment. But they’re heavy into AI. I think where, as most companies are these days, most investment right these days. But they’re very pragmatic, right? They’re really looking for practical and in practical applications, they’re doing a little like, guess what I would call basic research, right? There are funding some firms that are starting with a clean sheet of paper, but for the most part, it’s a very pragmatic investment approach.
Steve: And this, this podcast with Adam Drake, I mean I didn’t know Adam before the podcast, so it wasn’t a name that I was familiar with, but I really dug his point of view on practical AI. How do you get value out of this? And it was funny, he kind of turns the acronym around from AI to IA and he talks about what companies really should be thinking about today is intelligence augmentation, right? Which is, yeah, we’d love it if the machine were omniscient and able to understand and evaluate and respond in ways that were effective without humans having to be involved. But this notion of general intelligence, just general AI intelligence is not one, we’re years if not decades away probably from a technology like that. And so let’s think about where can we apply the technology in ways that can augment the decision making ability of humans, whether that’s augmenting, kind of inside the firewall, if you will, within the company or augmenting our customers’ abilities to make a decisions or prospects’ abilities to make decisions.
Steve: So anyway, I really liked his thesis and it’s funny, everything which is old is new again, right? So great be the enemy of the good. I mean, we’ve heard that for, for eons and KISS, right. Keep It Simple Stupid is a philosophy, so he bring these theories to his work. But it’s absolutely right. I think we get really wrapped up in the complexity of the data and the gee whiz nature of the technology that often we’re thinking way too big about what AI can do and instead should be thinking in a relatively targeted way about what AI can do for us.
Tim: Yeah, absolutely. I think that’s really smart and a really fascinating way to think about it. I’m going to do a shameless plug for one second for a podcast episode I recorded for my other podcast a little over a year ago, about a year and a half ago that was called, “AI won’t steal your job. Smart people who put AI to work will.” And the reason I’m bringing it up, as you know, there’s actually a series of fields in chess, oddly enough, in high stakes competitive chess, they actually pay attention to what they call centaurs, which are great chess players who are using AI. They’re sort of riding on top of AI and that’s where you get the half man, half horse. Steve: Okay. I was wondering where centaur is going to come into it. Okay. Got it.
Tim: To help guide their moves and by the rules of the high stakes chess stuff, cheat. But they’re a better player than the just the AI would be because they’re bringing their human insights and their human creativity to it. But the AI is bringing insights to it that the person couldn’t. And so the two together so much more powerful and, and I think this is exactly what John and Adam were talking about on the podcast episode. So just out of curiosity, I know you’ve been having some conversations with a number of folks about how they’re thinking about AI to do the, or more more importantly, thinking about IA, this intelligence augmentation component to be more effective. Maybe you talk about that a little bit.
Steve: Yeah, it’s interesting. I actually try not to talk about the technology when I’m talking to people. It’s more about the value, right? So I try to focus on the business side of it and not sprinkle the pixie dust in the conversation. But I mean everybody likes the pixie dust, so it’s kind of unavoidable. But one of the things that has been interesting and I have conversations literally every day. I think since the beginning of the year I’ve had 116 non-sales, non-investment discussions with digital marketing. I keep tracking them, right? I’m kind of one of these anal people and it’s very interesting. What I’m trying to discover is what’s top of mind, what are the themes that digital marketers are really interested in? And when you talk about AI, machine learning, text analytics and LP, any of those buzzwords, there’s kind of three camps, right?
Steve: There’s the, we want to get started. We know it has value, but we haven’t yet gotten started. And a lot of that has to do with the fact that they haven’t figured out what the problem is, right? And by the way, it’s a great place to start, right? So because it shouldn’t be technology in search of a problem, it should be a problem in search of a way to solve that. Right. But I think often it gets a little, kind of do loopish because they are trying to think of the big problem and often it’s a very targeted problem and that’s kind of the third class of person.
Steve: I think there’s a second class that has gone and bought the technology and they bought the technology because often they are, and you see this in search a lot, search engine providers a lot, where there’s not a lot new in search, right? There’s not a lot new in how search engine technologies work. Most of them are [unintelligible] based. Most of them are elastic or solar based and people are kind of bolting on augmentation to them and so they’ll buy kind of this traditional technology that by the way, if you know how to manage it works pretty well. I mean there’s… Tim: Right, right.
Steve: I mean cause great search is actually driven more by content than by search platform. Oh by the way, when they bought the technology and they’re making use of it, there were some, AI slash machine learning text analytics features and functions in it. So they hope to take advantage of that. So it’s kind of more technology based thought. And by the way, when you quiz people on, oh, well great, how are you taking advantage of that? Often the answer is not so much, and we’ll talk about that a little bit more in a in a minute. And then there’s kind of the third one, and I had this very interesting conversation with this Fortune 500 scientific equipment manufacturer, I think it was earlier this week. And they’re very interesting.
Steve: First of all, their AI leader is not a data scientist. Their AI leader is this kind of technology savvy, marketing savvy, almost like project management program management guy, right? And what’s really interesting about that is he sees the business and the technical landscape and he’s thinking about interesting business problems that are kind of intractable. And one of the interesting business problems that’s intractable is, how do you price in a way that you can kind of find the right intersection point between conversion rates and profitability. And what they’re doing is they’re just using these, they take all this data they have about visitor behavior on the web, about purchase price, about pricing that they get from, because they have a field sales force in addition to kind of the website.
Steve: You’re taking all this and just kind of laser focused on this one problem of, again, how can we do better at pricing? Yeah. Make ourselves more profit, close more business, et cetera. And what’s the right balance? And I think that’s a great example of where the business problem was clearly defined and the value proposition was well understood. And yet traditional methods made it difficult to operationally solve this problem, right? Everybody’s had pricing models since the beginning of time. But what they were supposed to do was kind of in runtime gather data about what is Tim doing and what should we be offering them at this moment based upon not only what the model says is right, but what I’ve learned about Tim in his interactions. And so, that’s just kind of one example of where I think accompanies this kind of third approach, which is the very tactical approach is the approach that Adam talks about in the podcast, which is, how do you target a specific business problem?
Steve: And it was really interesting to hear, talking to this gentleman, it was, he was at that intersection of business and technology. So it wasn’t a data science led project. It wasn’t a technology led product project. It wasn’t a vendor led project, right? But it was somebody at that intersection of business and technology finding a relevant and important problem and then creating a platform or they bought a platform. But using the platform then to solve a very specific problem. So that a, they create value from the exercise and b, they stretch that muscle, right? They, they build muscle in understanding how to use AI, how to use it in very practical ways to create value in the business.
Tim: Well and it’s interesting you bring this up because, it’s funny you say everything old is new again and you referenced something you said we’d talked about in a minute and I think the minute has arrived, which one of my favorite quotes is when people say, when all you have is a hammer, everything looks like a nail. And what’s really fascinating to me about this discussion is these aren’t folks who are saying, great, where can we use AI? Or let’s go find a nail to hit with our AI hammer. They’re actually saying, hey, where are the big problems that we have not been able to solve? And is that something that AI can actually help us, that machine learning can actually help us, right? Which I think is really, really fascinating and excellent, excellent transition to this article you shared from Chief MarTech by Scott Brinker who talks about MarTech’s stack utilization being a misguided metric. And I think this ties in really directly with what you were just talking about. So again, I’d love to hear you kind of make that logical leap for us and talk through that a little bit. Steve: Yeah, you bet. So I was on a sales call, I don’t know, three months ago talking to a digital marketing exec that it was one of…
Tim: The other day. The other day, three months ago.
Steve: They all blur together. It was a really fascinating call because one of the things, one of kind of the objections that you get in sales calls is, and anybody who’s done sales kind of can list off their favorite objections. But one of the more common ones you get, especially these days when companies are struggling between an integrated stack approach to MarTech. So we’re an Adobe Shop, we’re an Oracle Shop, we’re a Salesforce Shop, whatever, right? Or the best in breed approach where, which is, yeah, we might have integrated stack or might not, but we also look for technologies that have very specific value propositions that help us solve a specific challenge.
Steve: Anyway, he said, they have that latter approach, right? They were both an Adobe Shop and best of breed. But the problem is they had like 30 technologies in their MarTech stack and a lot of those had new measures of value. And he owned up to it. He said, shame on us. We kind of went in and bought these things and these guys had an interesting technology but there was no way we or they could demonstrate the value. And so they were going through a whole rationalization process. And basically his objection was, call me in three months when we’ve completed a rationalization and then we can talk about your technology and, oh by the way, be ready to talk about value and how you’re going to measure because I’m really interested in that. And so I think the reason it’s top of mind is because Monday was the three month point.
Steve: So I sent him, sent them the reminder email. So we’ll see what happens. But it really is this, there’s a lot of this going on. You hear all about it a lot. This rationalization of the tech platform. And Scott has a really, I mean as Scott does almost anything he says, but he has a really interesting point of view and that is to say that the value to the enterprise is really at the intersection of three things. What’s the features that a technology brings to the table? What are the skills that the organization has to take advantage of those technology features. And then finally, what is the value that that technology then creates? And it’s really, I love the model because as a software vendor, right, I like to talk about features all the time and how our features differentiate from the market and how it creates value that’s different from the market.
Steve: But I don’t often talk about the skills piece, although I do implicitly, but I never thought about it this way. A lot of our clients need consulting help. So when we sell software, we often sell consulting with it and part of that startup, right? That goes beyond say training, they really need, hey, can you upscale us so we really know how to take advantage of us, of our technology and we like that because well, a, we get paid to do it but b, we like people to be able to know how to use our technology to create the most advantage for them. So I think it’s very good from a retention perspective because if you have value, you’re going to renew. But it really is this value piece that that I think is often missed during these purges of technology, is that really understanding what is the value of the feature that you have installed.
Steve: And I can, it’s countless, countless times I’ve heard the following. That’s a really interesting feature that your product has, Steve. By the way, our stack already has that feature. And by the way, our feature isn’t unique. How we do it is unique. But you know the thing we do, we have behavior based personalization or some sort of personalization technology is not unique. And then I ask, oh great, how’s that going for you? It’s kind of my next question. And often, and by often I mean 95% of the time the response is, oh well we haven’t enabled that yet. Okay, so you’ve been, …
Tim: We already have that. We just don’t use it.
Steve: We already got one. So, I’m sorry. Cheap Monty Python reference for those who…
Tim: And yet it will get a laugh every time, Steve. Every time. Steve: I know you appreciate it. No one else.
Tim: Absolutely right. Steve: It’s, yeah, we haven’t enabled it because it’s not a priority for our IT team because often these integrated stacks requires some configuration that’s a lot more complex than say user configuration, right? It requires some IT lift. And so they don’t enable it. And you know one of Scott’s points is, if you can’t extract the value from the thing you already have, and by the way, often it’s, we’re an Adobe Shop and it’s one of 40 things the Adobe stack does and we can’t do this one thing, he goes, but if you can find something that actually creates the value, so if it creates net positive value to the business, then buy the best of breed thing that’s going to plug in. Now I will say personally, if I were a buyer, I’d want to make sure that, a, that value was measurable and not just promised, because a lot of software vendors promise stuff and it’s hard often to to figure out if they’re actually delivering on it.
Steve: And I’d also want to make sure the new technology integrates with your stack because often that unique feature is valuable not only when the feature can be delivered to your customer, but when the feature, the data derived or developed or thrown off by the feature can be integrated with other pieces of your stack. , right? So I think those from my perspective are: make sure that the value’s measurable and make sure the data can integrate. And if those two things are true and it has net positive value for the business, then go for it.
Tim: Absolutely. No, it makes a lot of sense. And again, we’re talking about this idea of, everything old is new again, we’re going back to this idea of ” what’s the problem you’re trying to solve and how are you using this to deliver on value?” You and I talk about this all the time. Obviously you focus a lot on the sales side. I focus a lot on the marketing side. We try with marketing, this is a marketing 101 thing. You don’t talk about features, you talk benefits, you talk about what is the benefit that people receive, the value that people receive. And it’s great to hear that when we’re talking to the customers who kind of get it, that’s what they’re looking for. Whether or not they’re actually executing in practice every single day, prior to working with us, of course.
Tim: Is a different matter. But at least they understand that’s what they’re trying to get to. And I think that’s, what’s the old, do you remember Syms Department Stores, they always used to say, an educated consumer is our best customer.
Steve: Back when we watched TV.
Tim: And it’s kind of that same idea.
Steve: Yes, I remember those commercials.
Tim: Back when we watched TV that’s right. I’m Sy-zing.
Steve: Because it’s Sy, I thought his name was Sy. Yeah, there we go.
Tim: Sy Syms. Yeah. But maybe dating ourselves just a little bit but the thing that I’d love to hear you kind of talk about just a little bit more is this idea that, I kind of want to go back to this idea of when all you have is a hammer, everything looks like a nail and how people seem to be looking to the stack, just save them. Right. And this idea of yeah, you need a good stack, but if you are not pointing your marketing stack in the right direction or you’re not thinking about what you need your marketing stack to do for you, what’s going to happen there. So if you could just talk about that for a minute, that’d be great.
Steve: Yeah. You know, it’s very timely. I’m crafting an email right now. We work with a number of consulting partners to help them with their clients and I got asked this last night, hey, could you craft an email for me that talks about basically the benefits of marketing strategy, which is kind of a weird question to get, but okay. I could, because everything starts with what are you trying to accomplish in the market. So, but I do think that a lot of technology buys are driven by not only what the thing is going to do for you and that’s often the problem that is well understood that you need to do better email marketing so you buy a technology that helps you with that or you need to do better personalization.
Steve: And so a lot of technology is purchased at least initially to solve the problem you understand. But I do think some of the shiny objects that end hand-waving that sales people do is try to get you onto the thing for the future. And that circles back to that common comment that I often hear, which is, we already got one, because they were sold this thing and I think somewhere in there is this behavior-based personalization object. And yeah, we’ve never used it. So I think that, when you think about Scott’s model, Scott Brinker’s model, which is this notion of skills, I think that’s where there’s a huge gap and this is a huge gap in technology acquisition and by technology value extraction. I think is a huge gap in marketing strategy execution.
Steve: We get enamored with these best of breed practices, these best of breed technologies, these best of breed approaches to extracting usefulness from data, but often the skills of the team and by the team. It could be the marketing team, it could be, especially in large enterprise, the broader team or all the business units, teams, brand units are coming together. You bring the IT team into that and it’s the skills of the process as well. I can’t tell you how many times–you and I were actually in a meeting yesterday where we heard this–which was yeah, we’d like to take advantage of that but getting the IT people together with us to get this thing going, right, might be horribly difficult.
Steve: So again, I think that there’s a lot of technology out there and even the technology that is in pursuit of a very valuable problem to solve. It gets stopped up by either the skills and the functional skills of the humans involved or the functional process skill maturity of the overall organization. And I’m a former IT guy so I don’t want to cast CIO types so I don’t want to cast too many stones there, but I do think there is a huge bottleneck in the traditional model, which is IT CIO controls the entire technology platform for the enterprise. I think that there’s an emerging CIL model where the functional areas are getting responsibility for managing their own tech stack.
Steve: And I know CIO’s is everywhere will wave their hands and light their hair on fire because now technology spending is out of control and that’s what leads to rationalization efforts because people bought too much tech, right. But I think the closer you move the tech purchase decision and quite frankly the tech enablement decision to the business function, the more likely value is to be extracted. Because I got to tell you, marketing technology people, if they had a marketing technology development team or at least enablement team, they’re not going to make the decision to allocate all the resources this next quarter to making sure the ERP system works better. No, they’re going to make sure that that personalization feature that’s in their Adobe stack that they haven’t used for the past 24 months finally gets enabled. So there’s a maturity and a business model line within organizations I think is a huge inhibitor.
Steve: And I, as a CIO guy back in when I worked for IBM, I flinched when people talked about this sort of model because I did worry that integration was going to be a problem, spending was going to be a problem, et cetera, et cetera. But now that I’m kind of on the business side, I really do understand and appreciate why they might want to put the, the technology decisions in the hands of the functional leaders because they’re closest to where value is being created. And I think that is something that CIO people talk about a lot, but their processes, their skills and their metrics aren’t really aligned towards that reality. And so I think bad decisions are made.
Tim: Well, and I think it goes back to, you told the story a little earlier about, the individual you spoke with who was not an ML guy, was not an AI guy, but what he did know how to do was ask the right question. And I think that’s really the skill that we want to see people, every company should want to see their folks learn because, bringing this full circle to talk about where AI helps and helps make intelligence augmentation. It can only augment when you’re actually asking intelligent questions. Steve: Excellent. Excellent. I like that.
Tim: You don’t want to augment the stupid questions. Steve: Absolutely not.
Tim: All right, Steve. With that, any last words you want to leave folks with before we wrap up for the day?
Steve: No. Yeah, more coffee I think. But this has been a really interesting discussion and you know, it’s one that I think everybody who talks to a vendor or everybody who is working on their strategy, right? So in a couple of months we’re going to start working on our 2020 strategy for success or roadmap to success. Really has to think about, and again, I’m sure we’ll put it in the show notes, but really go back to that Scott Brinker article. I think it’s an excellent read. I think his kind of mental model for thinking about how to make sure you’re getting value out of the technology platform, whether that’s your search platform or your marketing platform or, we’ve done all this, doesn’t matter even if you’re not in marketing, even if you’re head of payroll. But I really think it makes a lot of sense in thinking about what capabilities do we need? What’s the value of solving that business problem?
Steve: And then looking hard in the mirror and saying, does my team have the skills, the functional skills? Does our technical team have the bandwidth and process maturity to make the right decisions and prioritize this stuff? And how do we make sure that all that organizational capability, and maybe that’s the better way to look at Scott’s skills bubble is really that organizational capability because it crosses skills across this process. It crosses bureaucracy within the organization. Does the organization have that organizational effectiveness? I think it’s a fantastic model. I encourage everybody to read that.
Tim: Fantastic words to live by Steve as ever. Thank you so much once again for another great chat and look forward to speaking with you next time.
Steve: You bet. Have a great day.
Tim: Take care now.
Tim: SearchChat is brought to you by SoloSegment. SoloSegment is a technology company focused on site search analytics and AI driven content discovery to improve search results, increase customer satisfaction and unlock revenue for your company. SoloSegment. Make your search smarter and learn more at solosegment.com. If you like what you’ve heard today, click on the subscribe links. You can find at solosegment.com/podcast. On iTunes, Google Podcasts, Stitcher Radio, Spotify or wherever fine podcasts can be found. You can also find us on LinkedIn at linkedin.com/company/solosegment. On Facebook at facebook.com/solosegment. On Twitter using the Twitter handle @solosegment. Or you can drop us an email at email@example.com. Again, that’s firstname.lastname@example.org. For SearchChat, I’m Tim Peter. I hope you have a great rest of the week. Thanks so much for joining us and we’ll look forward to chatting with you next time here on SearchChat. Until then, take care everybody.