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"We've seen companies locked into vendors for a decade with no way out." – Juan
Jacqueline and Juan kick off 2026 with a quick reality check: stepping away from screens feels great, but the Martech stack doesn't magically get simpler while you're gone. They get brutally practical, drawing on conversations with 300+ brand-side marketers to map the six biggest pain points emerging across enterprise teams right now.
They dig into why "Customer 360" is still mostly a fantasy, how integration complexity turns stacks into brittle Jenga towers, and why AI pressure is creating more chaos than value. From auto-renewal horror stories to redundant CDPs and initiatives chasing optics instead of ROI, the message is consistent: confidence comes from evidence, not experience bias — and the cost of getting it wrong has never been higher.
Sponsor
Brought to you by Hightouch — Went all-in on a big marketing suite but still struggling to get value? You're not alone. Our sponsor, Hightouch, spoke with 50+ enterprise teams and found 79% are frustrated by high costs, slow innovation, and rising complexity, often needing specialized teams just to keep things running. They'll share the full findings in a live webinar on February 12, plus what they're seeing from organizations updating their Martech stacks. Get the report and register!
Timestamps
02:10 — An exclusive announcement for listeners
03:50 — Why experience-based advice keeps failing enterprise teams
07:45 — Six themes from 300+ marketer conversations: what's breaking in enterprise
10:50 — Data fragmentation and the myth of Customer 360
15:00 — Why evidence-based decisions are the only way forward
18:20 — Integration complexity, legacy sprawl, and cross-team coordination failures
26:15 — AI pressure without value: herd mentality of GenAI, risk, and bad customer experiences
31:00 — Adoption and operating model problems: utilization dropping, skills gaps growing
36:00 — Measurement, attribution, and ROI proof gaps: why nobody trusts the numbers
41:30 — Scaling personalization and execution speed: the bottlenecks no tool can fix
Connect & Subscribe
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Creators and Guests
What is Making Sense of Martech?
Unfiltered takes on the biggest shifts in marketing technology. We spotlight what matters, who's leading (or lagging), and what's next. In Martech, clarity is power — and we're here to deliver it.
00;00;04;58 - 00;00;08;05
Speaker 1
Welcome to Making Sense of MarTech podcast. I'm Jaclyn Friedman.
00;00;08;05 - 00;00;09;10
Speaker 2
And I am one Mendoza.
00;00;09;15 - 00;00;18;43
Speaker 1
And this is Office Hours, and we cut through the noise and discuss the latest and greatest in the martech landscape. So happy New year. Juan, how are you doing?
00;00;18;52 - 00;00;37;33
Speaker 2
Happy new year. I'm doing well, thank you. I'm well rested. I took two weeks to go camping in here in Victoria, in Australia, right at the southern part of Victoria, where it was half beach and half bay. Absolutely spectacular. Beautiful beach area. It was wonderful. I didn't think about work once. How about you?
00;00;37;39 - 00;00;54;04
Speaker 1
It sounds lovely. Yeah, I didn't think about work too, too much, but that's mainly because I was also in a very remote place with minimal Wi-Fi and self-service. My husband and his family didn't really have much of a chance to think about anything really, other than maybe Stranger Things, but I digress.
00;00;54;09 - 00;00;58;46
Speaker 2
Oh yes, please don't give me any teasers. I have not finished. Stranger things has.
00;00;58;52 - 00;01;03;18
Speaker 1
One more episode to go. Let's go. It's about to go.
00;01;03;23 - 00;01;25;50
Speaker 2
I know I'm going to it. I actually spent a bit of my time cleaning my house and it sounds extremely boring, but it's so nice. Like looking at all the things you neglect from the year at, like fixing up your house and just going and doing them for like two weeks. Very good. I highly recommend it. It's, you know, we deal with a lot of complexity in marketing, technology teams and stacks and challenges.
00;01;25;50 - 00;01;40;10
Speaker 2
But you know, when you take it, take yourself away from it and do something simple like paint your fence or fix your air conditioning or, you know, like throw out all of the mountain of toys that your kids have. It's a quite nice experience. It's good. I think it's refreshing. Just as good as a holiday.
00;01;40;15 - 00;01;46;43
Speaker 1
You're making a good argument to become a Luddite and just get rid of old technology.
00;01;46;48 - 00;02;07;30
Speaker 2
Oh, I love it. Yes, 100%. The less I'm on my screen, the better. But we should probably get into the office hours. I'm excited for the new year. We've got a whole new swath of content for you guys. We're really excited to kick off the year. But before we get into our new content plan for making cinematic jokes, tell us a bit about a sneak peek.
00;02;07;30 - 00;02;09;47
Speaker 2
Something a bit sneaky, a bit something a bit special that's coming up.
00;02;09;48 - 00;02;37;53
Speaker 1
Yeah. Yeah, we are exclusive announcing a sneak peek here, and a week from today it will be shared more publicly. So you'll be in the know first. But we are announcing something formally, and it's going to be a different way of thinking about the martech weekly. And so we are launching Twitter rRNA, which is our research and advisory component, an arm of the MarTech weekly.
00;02;37;53 - 00;02;49;00
Speaker 1
And I would love to hear your perspective on as to why we're building this and maybe how it is different and just completely a different way of thinking about what the TMW represent.
00;02;49;02 - 00;03;10;16
Speaker 2
It's great. We're really excited. We're only a few weeks away. It's been a bit of a labor of love. Almost six months actually developing this, but more than 18 months thinking about this direction. So Jacqueline has been a massive part of this process. But basically, I guess the MarTech weekly is started as a weekly newsletter. I started it on a Friday text.
00;03;10;16 - 00;03;28;24
Speaker 2
My manager at the time, I was working for an enterprise marketing technology consulting company. So I text my manager and I just said, hey, I think there's a gap here. I think that a lot of the senior leaders in marketing technology just have a real lack of knowledge, a real lack of insight from what's going around the market.
00;03;28;29 - 00;03;51;32
Speaker 2
And at the same time, if you look at the chief martech martech tribe landscape around marketing technology, it's growing a thousand technologies a year that's been consistent over the past 5 or 6 years now. And as MarTech weekly has evolved, obviously we do so many things now in the marketplace, support marketing technology teams thing that we've sort of looked at was going back to our roots a little bit and thinking about that initial newsletter and why it was done.
00;03;51;32 - 00;04;14;44
Speaker 2
And the main reason was to supply leaders, busy people, managing dozens of people, tens of millions of dollars in budget, you know, huge marketing complex marketing, technology stacks, helping them have the right level of information, evidence to make decisions around the technology stack, big, consequential decisions that would last for years and cost millions of dollars. Very hard to reverse and unwind.
00;04;14;46 - 00;04;40;08
Speaker 2
You know, you need really high quality information, but the newsletter was really just one small part of that. And so it really extending into RNA with this whole new approach where we, we call it evidence based decision making around marketing technology, not experienced, biased, which is often what you get with other consulting firms or you get with analyst firms, is you're getting an opinion based on their immediate experience with different technologies or their existing partnerships with different technology platforms.
00;04;40;13 - 00;05;00;46
Speaker 2
But for us, well, we're collecting data and we're going to talk about this in a minute. We've been collecting data across hundreds of enterprise marketing technology, stacks and teams. So we have all this incredible data and, well, we're actually rolling out the utilization of that data to support things like choosing a new technology platform. You know, that's not easy in this world.
00;05;00;46 - 00;05;23;18
Speaker 2
You know, you're looking at dozens, often of different, different vendors with different approaches, different strategies, different pricing. That's really tough using the technology, how to implement it well, how to report on its value, renewing the technology when a renewal license comes down. Actually, Jacqueline, you and I talked about this with our CMO recently where he said that it was like a $5 million renewal from a Salesforce contract and no one knew about it.
00;05;23;22 - 00;05;50;46
Speaker 2
You know, it was just like it just rolled over. Yeah. Without any strategy around how they're going to continue to leverage this platform with that renewal. And I think it was pretty significant also like a three year renewal. So renewals is a massive pace, like setting yourself up for success when you go to negotiate, for that renewal process and then also, retire, like letting go of technology where it's actually being not utilized enough and saying sayonara and actually saying goodbye to technologies that you no longer need.
00;05;50;51 - 00;06;17;02
Speaker 2
And so those sort of four areas choose use, renew and retire. That's sort of our strategy there. But it's all evidence backed. So we look out to the market. We've got data on the vendors in the marketplace. We've got data on the brands and how successful they are, the use cases that they're employing. And we're starting to really build this momentum around this idea of when you come to your next major, consequential martech decision, you really should have the highest quality evidence from the marketplace to make those decisions.
00;06;17;12 - 00;06;33;51
Speaker 2
And so that's kind of the big thing to reveal soon and how it all works. But it's really, really exciting. And, you know, Jacqueline, you and I kind of met around this idea, I think initially on LinkedIn, as I often do on LinkedIn, I post like a random clue to like what, we're working on at the MarTech weekly.
00;06;33;56 - 00;06;51;17
Speaker 2
And, you commented, you said I'm interested. And I said, hey, this will blow your mind. I had no idea who you were at that point, but I think I commented in that said, this will blow your mind. And so that was gosh, back in, I think November or December 2020 for a little while ago now. And so that's how we met, right?
00;06;51;17 - 00;07;12;16
Speaker 2
And you've been doing that work yourself. You've been working as a practitioner at some major enterprise companies, dealing in first hand with a lot of these problems, buying, choosing marketing technology. So, yeah, it's really exciting. And, you know, as a team, we're really excited to bring this out to market. And more importantly, it's for the marketing technology off, you know, only for those folks.
00;07;12;30 - 00;07;19;46
Speaker 2
Really, we're not servicing anyone else except for that marketing technology practitioner that laid off making those big choices. So yeah, we're really excited.
00;07;19;47 - 00;07;46;57
Speaker 1
I'm really excited for us to take on this next frontier of not just helping folks navigate martech, but also deciding with confidence. And it's not just deciding what to keep, what to use, but how they should be thinking about their strategy with their tech. Because oftentimes you get stuck and that's usually a symptom of a greater issue. And so we can really bring all of our understanding and evidence based content data, you name it into the fold.
00;07;46;57 - 00;08;12;25
Speaker 1
And it's going to be extremely interesting because as we expand upon this launch and our research component, we already have been collecting data, as you've mentioned, and we actually have a sample size of over 300 brand side marketers in terms of folks we've been talking to in the market and just trying to get understanding of what brand side practitioners are dealing with.
00;08;12;25 - 00;08;35;05
Speaker 1
And there's been six key themes that we see as really beneficial to kind of highlight and talk about together. And if we deem it worthy or if you deem it worthy, more like we could potentially do a segment or two on these specific topics as their own standalone conversation, just because there's a lot of meatiness to each and everyone.
00;08;35;05 - 00;08;41;23
Speaker 1
But it's it's exciting that we we already have these results and we haven't formally launched yet.
00;08;41;28 - 00;09;04;45
Speaker 2
Yeah. And and it's interesting the challenges that are coming out. I mean, you know, we're we're seeing from the data challenges, but then hearing it, hearing the frustration or the challenges or someone looking to leave their job because of some of these problems, you know, is makes them very real as well. So you're seeing from both talking actually conversing with with folks that are leading a lot of these areas, then also collecting the data to sort of back up with evidence.
00;09;04;45 - 00;09;27;16
Speaker 2
It's really interesting to see, you know, we've seen some absolute horror stories. Jacqueline, you and I, over the past 12 months, we say companies being locked in for more than a decade, and they have no way out from a vendor, and they want to get out from that vendor, but they can't. We've seen companies, as I just said, a, being put into renewal cycles where they're dumping millions of millions of dollars, but they have no idea what's going on.
00;09;27;21 - 00;09;27;40
Speaker 2
We've seen.
00;09;27;40 - 00;09;40;29
Speaker 1
And we've also seen companies where they have one of every platform and the redundancy is wild. And, yes, of just thinking through the procurement contractual negotiation process. It's a bit nightmarish.
00;09;40;34 - 00;09;46;09
Speaker 2
It's unbelievable. So a lot of enterprise companies have to have everything right. You know, two CDPs.
00;09;46;14 - 00;09;47;26
Speaker 1
If not all three.
00;09;47;28 - 00;10;08;45
Speaker 2
Data analytic or or all the technology scattered among product teams and different business units. You see that a lot as well, where, you know, nothing talks to each other. You see that? That's pretty consistent. We see among some of the challenges, but we also see some great stuff. We had some great conversations last year with folks where a lot of the technology that they had, they made it basically deprecated.
00;10;08;45 - 00;10;35;09
Speaker 2
So they let go of a lot of technology because I didn't really need it. So they're saving a lot of money as well, but also getting smart around that technology stack. You know, we've had some fantastic outcomes and wins where companies are driving millions, tens of millions of dollars in revenue from new use cases, from technology. We've seen the, you know, the adoption of AI agents, AI decisioning, generative AI content, and a lot of really interesting results around how those technologies are being utilized.
00;10;35;20 - 00;10;51;00
Speaker 2
So there's a lot of exciting stuff. It's not just challenges, but maybe Jaclyn, you can give us a roll call. What are these six key challenges that have come out? Our data repository of enterprise brands. What are they. And then maybe we can circle around a little bit what they what they actually mean.
00;10;51;04 - 00;11;17;39
Speaker 1
Theme number one data fragmentation and a lack of a single source of truth definitely tracks. Number two integration complexity across the martech stack. Three AI pressure without a clear value realization that one resonates with me a lot. Number four operating model and adoption challenges. Five measurement, attribution and ROI proof gaps. And lastly, scaling, personalization and execution speed. All right let's dive in.
00;11;17;39 - 00;11;44;30
Speaker 1
Because these six are meaty. And I think it's worth us kind of not just seeing what are talking through what we've seen, but also what else other industry and research firms are acknowledging and seeing within this space. And so starting with data fragmentation and a lack of single source of truth, I mean, that rings true in terms of just siloed data and consistent identities, poor data hygiene and these ever pie in the sky.
00;11;44;30 - 00;12;12;54
Speaker 1
Customer 360 it's never existed. I don't care who says they have it as part of their platform. It doesn't exist. And this is backed up by the one and only the Gartner Research. And they're saying only 14% of organizations say they've achieved a 360 degree view of the customer. I would argue the 0% of organizations have, but 14 is pretty close in terms of actually wanting or actually proving that, and 82% still aspire to it.
00;12;12;54 - 00;12;18;53
Speaker 1
I would say 100% of every company aspires to it. But what are your thoughts on on that stat? Does that sound about right to you?
00;12;19;00 - 00;12;40;01
Speaker 2
I think it's true. I think the numbers are much lower. I think it's quite 40% is a quite optimistic number. 82% still aspire to it, but it is kind of like self-driving cars in a way. You know, it's always two years away. You know, the amount of sort of heads of data, chief data officers that I've spoken to in the past that have they're gunning for this, like, single source of truth data that's centralized.
00;12;40;01 - 00;12;58;00
Speaker 2
Every business is tapping into it. You know, this whole philosophy that, you know, even snowflake talks about, which is bring your apps to the data, not your data to the apps, you know. So bring your apps to a central source or a golden record or 360 view. It's interesting because, it does definitely feel like it's always two years away in these organizations.
00;12;58;00 - 00;13;18;25
Speaker 2
But at the same time, I think there have been some really successful, views of this. I think one of the smart ways which companies try to tackle this problem is to get very, very practical about where the data is currently sitting. What's the practical commercial value realization of that data? You don't need everything you know. And the future use case that's five years away.
00;13;18;30 - 00;13;35;19
Speaker 2
You can solve for that later. But what's the core customer profile that you're really looking to build? What's the identity challenges that you're trying to overcome and then focus on building against that? I think that's where a lot of success comes from, is you don't need a single source of truth. You need probably 2 or 3 sources of truth.
00;13;35;19 - 00;13;59;14
Speaker 2
What are those and what is really true in the sense of commercial value and also practical customer experience value. Focus on those things because like every other investment in a company, there needs to be an ROI on pursuing a source of truth. You can't be philosophical about it. You can't be like, like often a vendor would come into a company and say, you can pull up a profile of your customer and you can see everything they've done or contact said.
00;13;59;14 - 00;14;26;07
Speaker 2
A person could pull up the profile and see everything that sounds familiar. It's a very familiar talk track that you see with the vendors. However, that's a philosophical proof point. It's not a commercial one. It's not saying. Right. If we actually look at the data that we're collecting, and we are saying that there is more value by by focusing on these specific variables or these specific data points, for these reasons, we're going to invest in collecting or and centralizing those areas.
00;14;26;07 - 00;14;45;25
Speaker 2
Then we're going to see a commercial outcome because we're going to run better email personalization or web personalization or the contact center is going to be more optimized, more efficient. You know, all of those things are true. But like everything else in business at least needs to lead to an ROI. So I think a big problem with this is, a lot of chief data offices, a lot of marketing technology heads.
00;14;45;25 - 00;15;04;38
Speaker 2
They think about this as a philosophical concept that's always two years ahead, like, self-driving cars, you know, and not actually thinking about the commercial value. That's where you're going to get the runs on the board. That's when the executives are going to start turning heads and saying, yes, we're so happy we consolidated two systems or three systems or 20 systems, because that's led to a greater outcome for our business.
00;15;04;38 - 00;15;30;36
Speaker 1
Yeah. And I think to that point, there is a statistic that nearly $13 million per year on average are wasted on poor data quality. And so philosophically, yes, it is a pie in the sky ideal to have a single source of truth, but at the same time, you should still try to as simplify your data sources as much as possible so that you can at least clarify and align on where things are and where things live.
00;15;30;41 - 00;15;43;04
Speaker 1
That's half the battle. Is achieving that alignment on where we trust the data, because otherwise it is just a cesspool of data which we don't want that abyss anymore because it's the cost.
00;15;43;06 - 00;15;58;41
Speaker 2
The other thing that I often see is companies suffer from data silos because people come into the business, they set something up and they leave. And one one later, I spoke to many years ago, 3 or 4 years ago. This is a problem that's been, I think, for many for probably 25 years now. I think this is a problem that's constant.
00;15;58;41 - 00;16;14;16
Speaker 2
But about five years ago I spoke to I laid out he recommended to building a Jenga tower. So if you're familiar with the game, you got these blocks that you build up and then you take them out. The first one, they say the Jenga pile implode. Basically, the first time you say that, do that, then that person loses.
00;16;14;16 - 00;16;39;36
Speaker 2
A Jenga tower is very similar in the marketing technology. Well, I mean that like a lot of people come in, they put another block in, they take a block out, they create separations for certain reasons at the time, and they're doing it for growth opportunities. And because an executive wants something or, you know, there's a blocker and it's all reactive to the business situation in the specific context that they're in, not proactive, which is what we're kind of getting at here, is thinking commercially, strategically about where that strategy is going.
00;16;39;50 - 00;16;57;39
Speaker 2
And so, you know, people coming in and out of the business, different consultancies coming in and building things. And then you've got this maelstrom of like, right, we've got this Jenga tower, seven pieces of being left out. It's about to implode because it's so complex and heavy with all the different things. Those are a lot of the forces that I think enterprises are up against.
00;16;57;44 - 00;16;58;37
Speaker 2
In big companies.
00;16;58;48 - 00;17;27;44
Speaker 1
Yeah, without a doubt. And to add to the reason for the difficulties here is also there's a lack of documentation when someone leaves a company, if they take that institutional knowledge away and it's not shared, where are you going to get that? And I do think this is actually where AI is extremely valuable between your company wide note takers and just being able to generate notes and documentation based off of existing conversations, that is making it a lot easier for those who are maybe allergic.
00;17;27;49 - 00;17;51;17
Speaker 1
So documentation, I would say those in our martech space and roles need to be anything but allergic. You need to be getting your vaccine every couple months because otherwise you're setting yourself up for lack of scale, and also you're setting up for future successors for failure, because there's nothing worse than always having to come in to a new role.
00;17;51;17 - 00;18;16;39
Speaker 1
And you have to audit what exists today, what existed previously, and if you're unable to find it. I mean, I've had to interview previous employees many times in my roles because I wanted to fully understand the decision making along the way, because there's usually really important and valuable lessons that were learned to achieve where you are today. But if you don't know the whys, you kind of start from zero and not a helpful way.
00;18;16;39 - 00;18;58;09
Speaker 1
But moving on. Number two integration complexity across the martech stack. So tools not speaking the same language. Oh, legacy tech and the M&A sprawl that slows everyone and everything down. And then of course just dependencies like it or data engineering or engineering in general. So this whole concept of complexity sprawl is definitely something others noticed. And so Gartner in 2023 kind of survey where the complexity and sprawl of the martech stack was 41% and a lack of strong customer data foundation led to 40% of impediments and so that is inevitable.
00;18;58;10 - 00;19;33;16
Speaker 1
Fan. But then as the added layer of inflexible governance. So if that's also a part of the mix, you're kind of setting yourself up for disaster when you have complex systems because you're scaling and you have a lot of data, it's both a positive and negative at the same time. And it's this privilege and disadvantage. And similarly, force are also found that 28% of B2C marketers agree that their tech portfolio is too complex or redundant, and they would much rather, nearly 50% would much rather reduce the number of platforms they're using.
00;19;33;21 - 00;19;57;36
Speaker 1
And that's something we keep seeing continually. Why are we spending this much money? Also, why did that auto renew? Because no one was paying attention or no one was owning that relationship. And it shouldn't be in the hands of procurement only because martech in particular is so specific. It's not your run of the mill, your data warehouse, your CRM, all of these tools that are just automatic that we know we're not changing from marketing.
00;19;57;36 - 00;20;14;26
Speaker 1
You can be more modular. You can be a little bit more like a Jenga or a Tetris situation, where you can make it work for yourself better. There's a lot of opportunity to fix this. I think collectively as as a general just martech industry and community.
00;20;14;32 - 00;20;36;55
Speaker 2
Yeah. Integrations has always been such a cross-functional problem and cross-functional. What I mean by that is coordinating across many different teams with different incentives. Typically product IT and marketing, those three domains coordinating together. That's where the integrations often break. We don't see a lot of companies complaining about the integrations themselves. Often that's quite straightforward. It's a rest API.
00;20;37;04 - 00;21;10;19
Speaker 2
Yeah, sometimes. Often there has to be a custom API. Often. Well, in the enterprise, not really. So native, native APIs are very much a small business type thing where you can go into a, I don't know, a braise or something. And as a native connector, you know, it's interesting. The integration is both coordination and also customization, like customization in the sense that you can go to a large customer engagement platform or a CRM, CDP, and they'll say they have connectors, but often what they mean is that we've designed the connectors over the majority use cases that people want, not necessarily the thing that you need.
00;21;10;19 - 00;21;29;07
Speaker 2
And so that can slow things down because you go, right, we bought this platform because it's got this native connector into our CDP as an example. That's a really good value add. Or you look at say, for example, sales, Salesforce Appexchange. They have a big sprawling marketplace of different apps, and you automatically assume that they're all going to integrate very well.
00;21;29;11 - 00;21;48;47
Speaker 2
Turns out no, often it isn't that case. It's very much contrary where there's three specific things that that those native connectors do and then everything else. You're an API documentation. So you know, but there is ways around this, actually, we had a great insight from one of our speakers at AWS London actually last year. This person can't name who they were because they were a mystery speaker.
00;21;48;47 - 00;22;08;06
Speaker 2
But I can share kind of what they did. They were advised against using one trust compliance consent type platform because of its lack of integrations. When this person actually sat down over a weekend, yes, a weekend Saturday and Sunday, and then read all of the API documentation from top to bottom. Monday morning he went back to his agency, went back to his team.
00;22;08;06 - 00;22;26;15
Speaker 2
He said, you're lying to me because actually this integrates with everything. You just have to build your own APIs, a certain infrastructure you need to use. But this would actually work great for us. How many martech leaders actually do that on a regular basis? I would say not many. I think part of the problem with integration is this abstraction of oh yeah, it integrates with this other platform.
00;22;26;20 - 00;22;43;53
Speaker 2
Right. But exactly how have you read the documentation? Have you actually gone through it with your IT team or with your data team? That is a big part of this problem as well. But as I said, complexity and customization is one piece, but the coordination is the other piece, which really makes it challenging to make sure that everyone's aligned.
00;22;43;58 - 00;23;16;30
Speaker 1
Agreed. And I think double clicking to if you're thinking through requirements of integrations, it's really thinking through interoperability to it. Yes, it integrates and what integrates which fields integrate, because a lot of the existing platforms do integrate easily. However, it might not send every detail that matters to you. And so I would get extremely granular. And one of my favorite cheat codes here is actually looking at the connectors, the like Fivetran is a great example with really excellent documentation of what data fields will be sent.
00;23;16;32 - 00;23;36;49
Speaker 1
And you can just kind of look can appear beyond the curtain and see what they would be able to send. Because if it's available to them, that is what's accessible. And you'll be surprised by the number of data points that you would think would be extremely valuable that don't get sent. And so that's where do we need to customize?
00;23;36;49 - 00;23;52;31
Speaker 1
Do we trust this vendor? Have we talked to customers who say, yes, we were able to make this work because we did this. And so yes, I think it's more of just doubling down on the research component and the evidence more than the feelings facts over feelings every day.
00;23;52;37 - 00;24;10;20
Speaker 2
Oh yeah. Can I, I want to tell a story here that puts some meat on the bones with this integration complexity particularly touching on coordination with other teams. A few years ago, I was working on a project where we were about to launch our first personalization use case, and a lot of the data that we were using was sitting upstream in a SAP data silo.
00;24;10;20 - 00;24;28;49
Speaker 2
So the team that was very ambiguous, it was kind of like they were in the distance. You didn't know who they were. They were kind of mysterious. Anyway, we were days from launching our first use case and really hoping that it would be quite successful. And we did a lot of work. It was 4 or 5 weeks of, you know, data strategy, content creation to get this going.
00;24;28;51 - 00;24;43;18
Speaker 2
And this poor company the day a few days before launching this, that shadowy, mysterious team that we don't know about made some change to a variable in that SAP database, and then everything down flowed downstream of that to the CDP became garbage.
00;24;43;18 - 00;24;44;23
Speaker 1
Oh, no.
00;24;44;23 - 00;25;03;36
Speaker 2
And so the CDP was collecting and this is a large scale company. Right? So you're talking hundreds of thousands of records being updated every couple of hours. And then to unwind, it was even more difficult because that IT team had the incentive. They had to fix this thing, but they had no cognizance, no recognition that we actually were relying on this on a revenue generating activity.
00;25;03;36 - 00;25;23;06
Speaker 2
And that's a like a painful story. But, you know, it took another 4 or 5 weeks to even just get that conversation going of how do we fix this? Data engineering teams are going nuts because we just cleaned all the data. We just got it all organized very painful. But that's where a coordination becomes really challenging because you don't have to like marketing.
00;25;23;06 - 00;25;37;17
Speaker 2
Tech teams can't think about their own marketing needs in that situation. They have to bring it in. They have to bring data. They have to bring product. They have to often bring in legal and compliance. Those coordination conversations will help you avoid those kinds of landmines.
00;25;37;24 - 00;25;56;30
Speaker 1
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00;25;56;35 - 00;26;22;42
Speaker 1
That's why companies choose high touch as the clear choice to personalize every interaction. See what high touch can do for you at high touch.com forms. Om. And now back to office hours. All right. Moving on to number three I pressure without clear value realization. And certainly around use cases scalability governance and data readiness responsible adoption cost consumption credit you name it.
00;26;22;47 - 00;26;43;53
Speaker 1
I think we beat a dead horse on this specific topic just because it's so relevant to what we do, and it's going to be interesting to see if some of the predictions come true, both the AI bubble popping, but also even Gartner's predicted that 30% of gen AI projects will be abandoned. That was by the end of last year AKA you know, just two weeks ago.
00;26;43;53 - 00;26;57;47
Speaker 1
However, I will be curious to see if they follow up on that and and share more because I know we've talked about it many times, but every AI platform is in there. One year POC got to prove it or you lose it and we'll see how that goes.
00;26;58;00 - 00;27;14;36
Speaker 2
There's a great game, a board game. We love to play it with our family. We actually just bought as a Christmas present for one of our neighbors called Herd mentality. Herd mentality. It's a game that you play where, you go around the table and you write on a card, not what you get asked a question.
00;27;14;36 - 00;27;32;03
Speaker 2
For example, what's your favorite color? And in the card you have to write not what your favorite color is, but what you think that group's favorite color is. Herd mentality. Fantastic game. Gets you thinking very differently about how to answer questions. There's a lot of herd mentality going on here. With AI pressure, we see it as a constant point of frustration.
00;27;32;03 - 00;27;55;03
Speaker 2
We've had several people call me up last year saying my executive is really putting pressure on us to deliver AI value in these areas. I completely disagree, or I'm not certain I even even know I haven't dived into it. But there's budget and there's pressure to show, particularly the public companies, to show those markets that we are investing in AI.
00;27;55;07 - 00;28;22;30
Speaker 2
But what you get out of that is you get a lot of slop and a lot of nothing where like stuff that's just totally unusable stuff that you never will actually use in your everyday work or as a consumer. And then often ways that are that comical and funny and kind of stupid, right. And so like I did a keynote, last year in Denver around this topic of particularly with generative AI, these platforms hallucinate.
00;28;22;35 - 00;28;43;43
Speaker 2
And if you're putting a platform that hallucinates and gives false answers or false information, there's been a litany of so many high profile things from Canadian airlines giving sort of recommendations around fares and refunds. That was totally false through to local car dealers. GM, you know, doing maths homework in a customer facing chatbot on their dealer website for cars.
00;28;43;46 - 00;29;14;55
Speaker 2
Those examples, one of millions when you take this generative AI platform work and then put it out in the wild. But the question I asked that keynote was, how did we get so far away from our sense of excellence in this industry? I remember back in the day when I built personalization use cases that every single piece of copy they needed to be triple checked, that everything need to go through compliance, that even the idea of, a customer receiving a communications, even if it's not very consequential at all, was very scary.
00;29;14;57 - 00;29;35;38
Speaker 2
You know, we did not want to do that. We wanted to be accurate. We wanted to have high quality content and information for our customers. We wanted to deliver an exceptional experience. Now, how is it that generative AI is now allowing us to deliver subpar experiences that can be often factually wrong? In fact, we don't even have control over whether or not what that customer is getting as an experience.
00;29;35;38 - 00;29;55;30
Speaker 2
You know, how is it that we're allowing that to happen? And, you know, the reason why is because the executives see the pressure from the market and the herd mentality driving this. So if you're a leader right now dealing with executive put pressure on you to do AI adoption, go back to your values. You know, one of the core values and any marketing technology team is accuracy.
00;29;55;42 - 00;30;14;49
Speaker 2
It's the veracity of the data. Having high quality data, having great experience as your customers and but also, most importantly, having control, control over the risk, control over the value. What if I take that away and but falling over to pressure from the executive that will never get you a seat at the executive table eventually either.
00;30;14;53 - 00;30;20;12
Speaker 2
So I'm going on a bit of a screed here, Jacqueline, because I think that this is real.
00;30;20;12 - 00;30;21;17
Speaker 1
You back in.
00;30;21;22 - 00;30;39;33
Speaker 2
This is I am back at work now. Okay. So but it is it is such a big problem herd mentality and really contaminate the program, the excellent program of work that a lot of our customers, a lot of our members are working on every single day to advance AI pressure can contaminate that. I think it's a huge risk point.
00;30;39;33 - 00;31;17;19
Speaker 1
Sidebar could also be an excellent piece of swag, martech, herd mentality, and something along those lines. All right. Number four operating model and adoption changes. Shelf wear undertrained teams, misaligned governance, lack of ownership and insufficient internal capabilities. Oh man. We're not up to date on the latest survey. As in, I'm waiting for Gartner to share theirs. However, in 2022 42% of respondents said that their more tech stack capabilities were down 58% in terms of utilization.
00;31;17;30 - 00;31;39;45
Speaker 1
Then in 2023, one year later, it dropped down to 33%. And the last this was three years ago. So if there was a 55% difference in just three years, I'm scared to know where we're at three years after that. And so it's really problematic to see just how under adopted and under utilized all of these platforms tend to be.
00;31;39;50 - 00;31;56;00
Speaker 1
And granted, of course, we need to think through tenure, churn all the different things from an employment and people component that impact the tools and ultimately the processes. But I'd be curious what your thoughts are on those just kind of mind boggling numbers. Yeah.
00;31;56;04 - 00;32;09;14
Speaker 2
My question to you, Jacqueline, is, is utilization more about feature bloat from vendors or skills and capacity for team? If you could pick one, which one would you pick? Vendor bloat or skills and capacity.
00;32;09;21 - 00;32;11;53
Speaker 1
Skills and capacity always. Every day.
00;32;12;05 - 00;32;12;31
Speaker 2
Was a.
00;32;12;36 - 00;32;41;56
Speaker 1
With skills and time. You can be unstoppable. You can build things, you can get the right tools and tech stack. But if you're just solely focused on what exists within your marketing suite solely, yeah, you can get there. But it might not be the best solution. So it's really the question of like best of breed. And that is people in terms of their skill sets and the tools, but also trying things out, do small tests.
00;32;41;56 - 00;33;02;59
Speaker 1
If you do a small test to be like, I want to personalize X, Y and Z, or I want to see if I can build an AI agent to help with this specific component of our process. See if that works before you actually invest and I'm always about micro wind micro tests before anything's actually proven. And I think that it gets difficult if you're losing talent.
00;33;02;59 - 00;33;06;08
Speaker 1
But also there's clearly something else systemic happening if that's happening too.
00;33;06;11 - 00;33;22;56
Speaker 2
Yeah, I agree with you. So this is not an enterprise situation, but as a company for us, we were utilizing a CRM and we renewed our CRM earlier this year, our contract for the next year. And for the first time, we actually sat down with one of the sales reps, and we looked at the entire feature list that this CRM provides.
00;33;22;56 - 00;33;38;42
Speaker 2
And then I chucked it into XL, and then I called out the ones that we or we actually reliably using, and it was less than 20%. And we're not by no means, you know, there's so many features that we will never use, but the CRM will then point to look at all the value getting, you know, look at all the features you get.
00;33;38;42 - 00;34;04;26
Speaker 2
Look at all the stuff we're delivering for you. Look at stuff we continue to deliver for you that you don't ask for. I would say that feature bloat is part of the problem here, because really, some of the data that's coming out of Gartner and what we're seeing and so challenges is utilization of the stack. Now, I would actually say that utilization of your marketing technology is probably not the best goal or the best metric, because you can use 100% of your CRM or your customer data platform, but then you are generating revenue.
00;34;04;26 - 00;34;22;42
Speaker 2
Are you getting ROI? You know, would you want to be in that camp, or would you want to be in the camp that says, we use this one thing in the CDP and we're driving to revenue each year, you know, on the specific use case, which one would you choose? I'd rather choose the latter, often. Right. And so I think the more interesting piece here is operating model.
00;34;22;42 - 00;34;32;50
Speaker 2
And for sure you've worked in some pretty fast growth companies. Jacqueline, let me put a word out for you. Agile coach, have you ever worked with any agile coaches? In the past.
00;34;32;50 - 00;34;37;12
Speaker 1
I've worked in agile, but not agile coaches.
00;34;37;16 - 00;34;57;27
Speaker 2
Tell me, let me let me tell you about this magical role. Are you ready? So an agile coach, coaches the agile team. So what they do is I sit above all the different agile things. Guys, you got scrum and you got Kanban. You got all of those different agile tools that are working in the business. And then they are they're really just to say, good job, you know, and to make sure things are progressing ahead.
00;34;57;28 - 00;35;16;09
Speaker 2
Operating model is tough. It's like the agile coach. I ask that because there's this role, and all they're really doing is making sure that people are doing doing the model that they've already been trained to do. But that's how much enterprise companies invest in to operations. You know, they've got people that are training people that have already been trained.
00;35;16;22 - 00;35;35;13
Speaker 2
And then they they spend their time just making sure things don't fall over. Operations is brittle. Operations can change quickly, even in large companies. But operations as diverse as well. It goes back to our previous one of these previous points about different coordination problems within different teams. Operating model feeds right into that. You know, it also slows down the utilization of technology as well.
00;35;35;15 - 00;35;57;58
Speaker 2
But I saw the world of like scaled agile frameworks and, you know, agile coaches and this whole concept of agile Spotify model was really famous for a while there about ten years ago. Since then, that's all fizzled out. And I feel like, you know, in terms of operating models at the moment, there hasn't really been a dominating concept to replace a lot of that, but I definitely feel as are they should be, because a lot of this is ideas.
00;35;58;08 - 00;36;20;36
Speaker 2
You know, agile is not is a it's a manifesto. It's a list of beliefs. It's not a recipe for how to deliver stuff in your business. You know, it really is that it's philosophies and beliefs about how you operate a company. I haven't really seen a prevailing like a new thing, which is kind of unusual. I'd say. You would think that there would be more operation methodologies coming to the fore, but really, I haven't seen anything.
00;36;20;39 - 00;36;50;12
Speaker 1
Well, I think there's a couple reasons. Agile is only so good in certain respects. And also the frameworks that do exist don't work for every company's needs and their own complexities and interdependencies, interdepartmental dependencies. So I hear you, but also I don't care. I think every I think every company has to figure it out for themselves because everyone operates slightly differently and every team has a different cycle for it.
00;36;50;12 - 00;37;15;36
Speaker 1
As long as you can ladder up to having the same goals, OKRs and vision. And that's really where I see like program management, where it is the greater component, whether it's a, you know, technical program manager for all of marketing, and it's very different than a project manager who is very much in the weeds. The program manager can be in the weeds, but their job is to make sure the system is coming along.
00;37;15;36 - 00;37;38;04
Speaker 1
And to your point, I think this is where a lot of platforms are failing because they are wanting to deliver quickly, because we're in this rapid environment that you have to get ahead. And as a result, we are diluting product vision in favor of future vision. And that's not what people actually need. We need to think through what product will help this.
00;37;38;04 - 00;38;09;31
Speaker 1
What within our existing scope of our platform. And I mean this from a vendor side. What works? What could we make better. Because you can roll out so many different things relatively quickly, but building things with no technical debt, building things that work and work for, you know, we'll say 90% of your customers use cases. That's much harder to build, and it's much harder to get that loyalty and retention based off that easy to it's like acquisition versus retention strategies.
00;38;09;31 - 00;38;17;35
Speaker 1
It's easy to acquire based off a fancy new feature, but it's actual maintenance and improvement over time that matters far more.
00;38;17;35 - 00;38;35;14
Speaker 2
And I agree with you there. It is interesting. So one of our constant collaborators, his name is Jonathan Go. He's the head of Medibank, which is a $13 billion, health insurance company. So he heads up martech there and he has this fabulous concept. You can check it on the martech weekly.com. I read an article for it about us called Leadership Debt.
00;38;35;14 - 00;38;54;10
Speaker 2
And this idea that like, it's not just technical debt, it really is leadership debt. When you have bad leadership operations fall over, when you don't have someone really making sure people are focused on getting things done quickly and things can actually, accumulate over time. It leads to bad culture, bad hiring practices, and then things just move slower and slower.
00;38;54;21 - 00;39;16;32
Speaker 2
It's like the virtuous cycle, you know, it's a spiral. You can go up to ever greater heights of, unbelievable outcomes. Or you can go cycle right down into that, the depths of hell, in terms of lack of leadership, lack of accountability, lack of structure, all those things. But that all of that contributes to operations, marketing operations is a growing, burgeoning area, particularly in the B2B world.
00;39;16;36 - 00;39;21;02
Speaker 2
I see that happening in B2C as well, because we need a there's a lot to operate, there's a lot to get right.
00;39;21;03 - 00;39;22;52
Speaker 1
It's so needed.
00;39;22;57 - 00;39;26;22
Speaker 2
Yeah, very much needed. But let's talk about scale.
00;39;26;22 - 00;39;26;48
Speaker 1
Without.
00;39;26;49 - 00;39;29;07
Speaker 2
It. Let's talk about one of my favorites. Go for it.
00;39;29;09 - 00;40;05;32
Speaker 1
Oh, it's a favorite to say words upon. Let's just say that. All right. Measurement attribution ROI proof gaps. There's difficulty measuring incrementality brand impact cross-channel attribution and justifying investments. So anecdotally, I don't believe in attribution. It doesn't work. There is no current infrastructure platform recipe formula that is true for not only everyone, but that can be agreed upon because there's data driven models, there's multi-touch model, there's first touch, last touch, even touch.
00;40;05;45 - 00;40;34;58
Speaker 1
You name it. There's one of everything. This is B2B and B2C. Nothing works. Just like lifetime value is not really going to tell you much. Average order value that's very different. And average. You know, purchase value all you name it, all the different components that are related to conversion that are far more important. And you have so many teams that are all dealing with the same pie, and everyone wants to slice it up so they have more pieces of the pie and are attributed to this than the other.
00;40;34;58 - 00;40;45;26
Speaker 1
It's a constant battle over the exact same thing. Hey, we have one singular goal if we're all contributing, great, but I would love to hear what your thoughts are before I dive into some metrics.
00;40;45;26 - 00;41;03;41
Speaker 2
Yeah, and we did an episode recently on one of these areas around attribution. I'm actually reminded of, a person that approached us. What was it about three months ago? Maybe they came to us, and they said they're building a tech platform to, quote, solve lost click attribution once and for all. I almost lost the guy out of the zoom meeting.
00;41;03;41 - 00;41;19;11
Speaker 2
I think at that point, that person's point was that, no, no, it's not that last click is bad. It's just that every other vendor except for me is doing it wrong. I said, oh, come on, you can you really say that? I mean, we've been working at attribution for a long time here, and there are so many gray areas, as you point out.
00;41;19;11 - 00;41;27;33
Speaker 2
Jaclyn attribution Incrementality, you know, experimentation around these areas. It's been alive and well since the dawn of marketing. And yet.
00;41;27;42 - 00;41;32;54
Speaker 1
Yeah, marketers originally were sifting through data like that. That was what you did.
00;41;33;03 - 00;42;11;42
Speaker 2
Yeah. And I think maybe in the new frontier of, AI, there could be some really interesting opportunities there. But yet again, you know, attribution is a messy, messy concept. It takes some seriously big leaps of faith to trust in a certain methodology. I think, whether it be. For measurement or it'd be last click, you have to have a philosophy that aligns with that, and you have to explain that philosophy that the rest of the business understands, especially your CFO, because if you're going back to your CFO and you're saying right now, attribution model tells us that this channel is driving the highest value, highest profitability, and now you, CFO is going to
00;42;11;42 - 00;42;29;37
Speaker 2
say, well, how did you attribute that exactly? Oh, well, this, that and the other thing, and then get lost in translation. And then in the end of the day, a very poorly used methodology or very misunderstood methodologies used to to give truth to something that isn't true, but that's the problems. I think the beauty of attribution is the search for truth.
00;42;29;37 - 00;42;57;29
Speaker 2
It's a search for what is real. Which of the 50 am I wasting? That's the goal is, you know, that classic attribution quote that says you're going to waste 50% of your marketing budget problem is figuring out which one are you wasting? I think a lot of that feeds into, yeah, into this search for truth. I wish we would do away with the word attribution and talk more about truth, about reality, because I think that helps to frame a conversation about, well, what is measurement actually here about?
00;42;57;35 - 00;43;20;30
Speaker 2
What is it for? It's to help us find truths about our customers, how they're engaging, how they're not engaging, how they're driving, how they're converting, how they're not converting all those things. But honestly, I just attribution is about as complex as a human spirit. Humans do things for all kinds of random reasons. They go down channels and they come off that channel and they come back again, and then they search something, and then they put it in their browser.
00;43;20;34 - 00;43;46;53
Speaker 2
You know, you have that happening at a scale of billions and billions of people every single day. There's no clear way to attribute all of that. It's too complex. It's too heavy. I kind of agree with you, Jacqueline, but at the same time, you need to show return on investment. You need to. But I think the goal here is to, as I said, get back to reality and then think deeply about your philosophy of what's true and what's real, and then which methodology will help you get there the best.
00;43;46;53 - 00;43;59;02
Speaker 2
Instead of just picking something up that your manager told you to do, or something that you know a boss told you to do, or a vendor, worst of all, will tell you to do, you know, think deeply about your philosophy of attribution first before you dive into it.
00;43;59;02 - 00;44;25;12
Speaker 1
For sure. And what's interesting is in a 2022 survey by Gartner, only 53% said that marketing analytics influenced their actual marketing decisions. And that is terrifying considering every person I know is coming on board being like, I need a dashboard to see this, I need to see that. And there's nothing wrong with wanting those things. However, there are things wrong if either you don't trust the data or you're not actioning based off of your data.
00;44;25;17 - 00;44;51;28
Speaker 1
So as much as we care about this, it's fascinating. And also according to for sure, only 76% of companies are dealing with other attribution models. They're just doing single touch attribution. That's terrifying. And if you're doing first, you're wrong. If you're using less, you're wrong. They're both non consequential. They're helpful and directional. It's kind of like the concept of vanity metrics.
00;44;51;32 - 00;45;11;03
Speaker 1
They're signals but they're not going to tell you much. And hearkening back to the very first point that there is no such thing as a real customer. 360 there is no real way to attribute correctly you can do specific experiments on specific things and get some information, but hard to do it at scale and for an entire business.
00;45;11;03 - 00;45;11;38
Speaker 1
That's it.
00;45;11;43 - 00;45;28;59
Speaker 2
It doesn't stop you trying. It's kind of one of those things. It's like Sisyphus rock, you know, the philosophy of physics pushing a rock up the hill, only for it to roll down again. That's very much the journey of attribution. Do you stop pushing the rock up the hill? No, don't stop it. Keep going. Keep trying to find your source of truth.
00;45;29;10 - 00;45;38;23
Speaker 2
You need that. Because if you don't have a good sense, even though imperfect, even though not 100% accurate, it's still better than nothing. Keep pushing the rock up the hill.
00;45;38;29 - 00;46;04;19
Speaker 1
I hear you. All right, well, last but not least, scaling personalization in executions speed. So both balancing the real time personalization campaign volume, global complexity and just the pace of cultural change. And I'm glad this one is the last one that we're talking about, because I feel like it's the most overstated, overused one in general because personalization can mean so many different things.
00;46;04;19 - 00;46;12;47
Speaker 1
But I'm curious to hear your thoughts. If there's something new that you want to add to the specific component.
00;46;12;52 - 00;46;41;13
Speaker 2
Scaling. Personalization I actually don't really have a whole take on this one. I would say that personalization is always about scale. It is personalized. Customer experience is not the customer talking to someone at the retail store front. It's actually getting an email that's super relevant to them, or a website experience that's super relevant to them. Or more importantly, these days, a chat experience or an experience with an AI agent or LLM that's delivering something very, very personal and exceptional for them.
00;46;41;16 - 00;47;15;30
Speaker 2
So honestly, I think that the balancing your real time personalization, volume, complexity, pace of cultural change, all those things are real. They're always going to be real. They're always going to be there because personalization is about the customer's experience. It's about finding those things that the customer really values and gravitating towards those. So maybe I'll give you an example of lazy personalization and then smart personalization, lazy personalization of things like product recommenders that come straight out of a vendor toolbox where you're putting it in an email and it's recommending based on what the customer has previously purchased, that kind of stuff.
00;47;15;30 - 00;47;40;48
Speaker 2
Obviously, today, even ten years ago, was table stakes. Anyone could do that. You can put an email. It's fine. Nothing. Nothing wrong with that at all. But it is very table stakes. It is quite lazy because really getting to personalization means like okay, we do this product recommendation module. However, I'll give you an example with a beauty brand I worked with many years ago where we layered those product recommendations on the content they were consuming, particularly around this skin concerns.
00;47;40;55 - 00;47;59;41
Speaker 2
Right? So that the content they were consuming around specific skin conditions like for example, blackheads or, different types of shades of mascara, things like that. We use our CDP to tally up the data there so that it would directly inform the products that the customer would be, served up in those email campaigns and then a website as well.
00;47;59;46 - 00;48;18;16
Speaker 2
And personalization campaign went through the roof. It turned it totally transformed how we did product recommendations. And really, that's just one example for a retailer. But that's where I think the crux of it is personalization. Scaling crap is still crap, you know, think through, how can you actually well.
00;48;18;16 - 00;48;20;35
Speaker 1
It's eloquently it is it is true.
00;48;20;40 - 00;48;40;53
Speaker 2
It is true. And if a lot about what it's like, yeah, we're doing the best personalization. We're getting amazing conversion. We're getting this incredible customer experience, great scaling it. And volume is is not the challenge. It's the idea. That's the challenge. Yes. And there's no technology that can help you do that. You need smart ideas. You need really good data to analyze what your customer's doing.
00;48;40;57 - 00;48;54;39
Speaker 2
You need to think outside the box to do personalization so well. But I guess coming back to scaling, you've seen this yourself firsthand in so many brands. Jacqueline, what do you think is some of the bigger blockers here? What's holding companies back from actually scaling those really good ideas?
00;48;54;39 - 00;49;20;19
Speaker 1
I think it's having the good ideas in the first place, but also I would say first and foremost is data accessibility and data silos. It's just not getting the access you need. That said, I think really what bubbles up the most is having appropriate use cases. So to your point, table stakes is different than real personalization. First name, last name or most recent X, Y, and z product recommendations.
00;49;20;24 - 00;49;47;41
Speaker 1
Those are not personalization that is built in baked in requirements. And that's baseline. And similarly in this in this line of thinking. So Forrester did a survey last year commissioned by Adobe and stated only 12% of organizations are qualified as leaders in personalization and maturity that are actually doing it well at scale. So this is a problem that is and once again, that might be an overinflated number.
00;49;47;41 - 00;50;07;11
Speaker 1
So only one out of ten companies are doing this well. So it's no surprise it's not landing the way it should because there's opportunities you have to not only understand the context of where your customers want to see personalization, but have the appropriate use cases and also make sure it's not creepy. It's always a weird line that like, you really have to navigate.
00;50;07;11 - 00;50;31;41
Speaker 1
And so to that end, what matters to your customers and for example, conversion points aren't that it's what value, what impact. So one of my favorite things thinking through this, not just personalization only, but campaigns specifically, I always like to ask not just what is the company wide objective for this campaign, but what is the customer objective? What value are they receiving from this?
00;50;31;46 - 00;51;00;29
Speaker 1
So the easiest, most fun example we could use is Spotify Wrapped. Everyone wants to understand where they fit in and where they compare, and who's in the top 2% of listeners of a specific artist. That is intriguing. That is personal, and I know it's an easy example to use, but that's really creepy if it's other aspects. If you're a top 2% of, you know, PowerPoint users, like, okay, not quite as interesting, but that's a scale, you could see that.
00;51;00;29 - 00;51;29;06
Speaker 1
And I think similarly personalization is better off used. And what you mentioned, like in-store experiences shouldn't be what you think of. I think of out of a digital component is where personalization really comes to play. So sending those loyal customers individual like VIP boxes, it's actually things they're interested in and, you know, dedicated customer advocacy and communities and really investing in the people who are passionate.
00;51;29;06 - 00;51;51;17
Speaker 1
In my eyes, that's real personalization because you need to have those advocates that care. I mean, you really have to go far beyond what you can do in an email only. That's not to say you shouldn't try cool things out and do dynamic emails and bring in interesting stats every day, every week, every month, depending on what your business is.
00;51;51;17 - 00;52;11;11
Speaker 1
But it needs to have value for your customer. That is always a missing piece. And I think where most companies and strategic thinkers that are trying to plan for this fall flat. And so that's my personal opinion as to why scaling personalization never really comes to be, because sometimes it shouldn't scale, sometimes it should be a very small segment, but very true.
00;52;11;11 - 00;52;13;07
Speaker 1
It is a high priority segment.
00;52;13;12 - 00;52;32;23
Speaker 2
As a whole point of personalization. It's it's for you. It's not for everyone, you know. And ramping that up is another challenge. The execution space side of this problem that's come out of the data is also a very interesting one. You know, we all know that enterprise companies, they crawl at a very snail's pace. And it's interesting thinking about speed in the context of enterprise.
00;52;32;23 - 00;52;46;24
Speaker 2
My only recommendation for speed is simplify, simplify, simplify the problem of like Chinese whispers. The coordination challenges between people as information is relayed up the chain, down the chain, and then sideways to different teams.
00;52;46;24 - 00;52;51;03
Speaker 1
Let's use talent game of telephone. I don't know what Chinese whispers are.
00;52;51;08 - 00;53;09;18
Speaker 2
Oh, I go, so, you know the problem of a game of telephone where you call someone and then they call the next person, and then then they call the next person, and the information that's passed from telephone to telephone is a little bit more different. It's a changed over time. We see that a lot with execution and particularly speed.
00;53;09;18 - 00;53;28;53
Speaker 2
The more complex the ideas around personalization, the more multifaceted and dynamic and niched it is, the slower you're probably going to go, particularly with legal, but the simpler you can make the idea. If you can communicate it in one sentence to anyone in the business, then they can understand it. That's going to improve your speed because they can pick something up and go, cool.
00;53;28;53 - 00;53;48;47
Speaker 2
We get that, one thing we used to do when we were doing personalization strategies when I was working, my former consultancy, was that for internal alignment. And Buy-In, which is a big part of your speed, is getting everyone coordinated around. This is to write a very simple like I'm talking 50 words maximum and a lot of images to show exactly what I'm going to do.
00;53;48;52 - 00;54;11;02
Speaker 2
Hey, we're doing this specific use case and it's going to be this. But make it extremely simple so everyone gets it, everyone understands it, and everyone can pick that up and then start working on it. That's one thing that's not utilized often. Like we think of speed and things like what's going through JIRA or, you know, the technology integrations or the data or, you know, but actually it's the information passing between people.
00;54;11;07 - 00;54;22;07
Speaker 2
If you can play a role where you can simplify that and then make it very accessible and easy for everyone, understand what you're trying to do. I think that's going to increase the speed you'll see an increase, I guarantee it. Yeah.
00;54;22;07 - 00;54;40;22
Speaker 1
To that point, I think I need to share a resource that I've built called a campaign request form, where it can be big or small, but there is a question. There's what is the singular goal? And if it's email specific, it's like, what is the singular CTA? Because you already know the principle of if there's more than one CTA, you've already dropped the ball.
00;54;40;27 - 00;54;58;46
Speaker 1
You can have, you know, secondary and tertiary goals that might be cause and effect. However, that's not the point of said campaign, said greater concept of a campaign. So you really have to to your point, keep it simple, stupid. Otherwise it's not simple enough and it's not easy enough to.
00;54;58;46 - 00;55;24;54
Speaker 2
Track 100%. And that, Jacqueline, is the six major challenges of surveying 300 and surprise brands over 2025 and what they're focusing on, what they're worrying about. But they're keeping them up and not what they're frustrated about. You know, how awesome is it to have that kind of level of insight, but also hope for you as a listener? You've actually gotten a bit of value out of just how to tackle some of these challenges.
00;55;24;55 - 00;55;28;34
Speaker 2
But as Jacqueline said, we'll be doing deeper dives into these in the following episode.
00;55;28;43 - 00;55;33;11
Speaker 1
If it's of interest. So if it's of interest, we can do deeper dives.
00;55;33;11 - 00;55;50;33
Speaker 2
Oh yeah, oh yeah. But we really want to focus on making sure that you're most successful in the role as a marketing technology leader. And these six challenges really stand out to us as areas where a lot of enterprises need help. But Jacqueline, maybe we can roll it out. Let's see how we go for sure.
00;55;50;41 - 00;55;56;44
Speaker 1
Well, and with that, thank you so much. Happy New Year. And Juan, you can roll the credits essentially.
00;55;56;44 - 00;56;16;06
Speaker 2
Roll the credits. Well thank you, thank you for joining. Making sense of MarTech. I'd love to have you. Please join us on the MarTech weekly.com. You can subscribe there with your email address. We don't do a lot of personalization, but there'll be a little bit. Come join us on, the email. You get all the latest episodes and some bonus content as well.
00;56;16;06 - 00;56;28;27
Speaker 2
It's really fun. Join us on Reddit. We've got a great Reddit community of people chatting along the way. Follow us on Making Sense MarTech on LinkedIn we have a showcase page. And finally, stay curious. We'd love to see you next time!