Join Clarasys Associate Director Tom Carpenter and marketing expert Phil Boyden of Sojourn Solutions as they explore the complexities of the MarTech landscape, from automation platforms to AI, to Customer Data Platforms (CDP), and offer practical advice on selecting the right tools for your requirements.
Tom Carpenter: Hello, listeners, and welcome to another podcast with myself, Tom Carpenter, and I'm joined again by Phil Boyden, a marketing expert from Sojourn Solutions.
Hello, Phil. Great to have you back.
Phil Boyden: Hi, Tom. Great to be here again.
Tom Carpenter: Today, we are going to be talking to you all about a theme we spoke about last time, which is how do you navigate the tech landscape, particularly discussing MarTech and things that are out there and available to you.
There's probably quite a lot of confusion with some of our listeners about when a marketing automation platform is the right platform, when some really specific Marketing technologies are the right platform. CDPs are also very current and popular at the moment. So hopefully Phil can help us dispel some myths about what those platforms do and don't do and where some of the decision points will come.
So I guess, Phil, let's start with some of the basics. So what are some of the core kind of capabilities that organizations will have today and what would be the difference between some of those and going for a full fledged marketing automation platform?
Phil Boyden: Sure. So I suppose, really, if you kind of work from the ground up, your first need might be to message people that you know, and it's easier to message the one you do know, because we've got opt in and stuff like that.
So at that point, you might just need to send some emails out. If it's fairly simple stuff, if you're sending a message every so often, then, just a platform that basically sends out an email is enough, and you can do the occasional blast. We don't necessarily advise that, but you have to start somewhere.
Moving on from that, we can have automated journeys. So you can have always on campaigns for nurturing people, welcome campaigns, win back campaigns, that sort of thing. So the moment you're actually automating orchestration, like that, then you need to look at your marketing automation platforms. So that would allow you to drop people in based on certain criteria.
So, you know, you're pulling in information, maybe from post-sales. So, you know, they had a contract it's run out, or they've got a contract, there's only a month left on it and there's no new paperwork running through. You can pull that information in, drop them into a campaign to automatically say, “Hey, time to sign up again with us.”
And then you can track that. You can see if they're opening it. You can see whether they have been doing anything based on that and it limits the stuff that other teams in the company have to be doing, basically.
Marketing automation vs Customer Data Platforms
Tom Carpenter: Is there a breadth between marketing automation platforms of which channels you can do that through? Are there some which are much more specific to, let's say, your email scenario there and some which are truly omni-channel capabilities?
Phil Boyden: So that's a kind of a tricky one to answer really, I suppose. Omni channel for me, you need to have a real good understanding of what's happening across all of your channels.
So a market automation platform could send out emails, send out SMS, some can do app push or web push. Others can maybe stick a bit of WhatsApp on and you can get bolt-ons for all these as well, so you can still push out to all those channels. Where you really need to get to Omnichannel though for me is where you need to have an understanding of people across all the different platforms, all of your own data, but for example, it's in a CDP, that CDP would pull all the data in, make sense of it and allow you to activate.
And when I say make sense of it, it's not just seeing what they've done, but it’s actually tying those identifiers together. So I've been liking say something that Clarasys has been up to on LinkedIn and I've made some comments. That might, that's going to be on a completely different email identifier to when you're actually sending me messaging about what you're doing, or when we're collaborating and working together.
So CDP would actually be able to recognize those identifiers and pull it into a single profile. And then, With a lot of the platforms you pay per kind of known profile within there, so.
Tom Carpenter: So it is linking different customer identities together, something which marketing automation platforms can do, but they're just not as robust as say a CDP or will you, do you think you would always need a CDP to be able to do omni-channel effectively?
Phil Boyden: So different marketing automation platforms have different capabilities. Obviously, a lot of them, the main identifier is email address. So my Gmail address wouldn't equate to my Sojourn Solutions email address. Wouldn't equate to some NTL world that is in some systems. Cause I went back so long when I was signing up to them.
So a marketing automation platform wouldn't actually marry those together. You might be able to get bolt-ons. So you might get some social media platforms, Hootsuite, Octopost, where they will do those identifying matching processes before pushing data in, but it's not really the right place for pulling all those IDs in, in one way. But it depends how you want to be using your information, I suppose, but a CDP definitely does all those identifiers there.
Tom Carpenter: Yeah. Okay, fine. So for those who are trying to work out, do I need a CDP as well as a marketing automation platform? If you're going to be pushing towards market leading marketing technologies, then you probably would need both, but you'd need to be investing in full omnichannel experiences to get the most out of those tools?
Phil Boyden: Say so, yes. So the orchestrations you can get within CDP are brilliant for next best action, that sort of thing. So you can react to exactly what's going on then and you can serve adverts up on different channels. You can make sure you're reaching out to people in that way.
But maybe, and there are orchestration capabilities within CDPs as well, but if you're really looking for a long term nurture with a long term interest and you've got an email address, there may be pushing that out to an audience in the marketing automation platform and following it through from there might be a better way of doing things.
Tom Carpenter: And I guess CDPs are great at segmenting customers into more complicated segments and routes, but ideally you're marketing based on actions and behavioral data, which is a little bit more complicated to interpret. Is there a kind of right place to be doing that? Or could you do that across either technology?
Phil Boyden: You can do it across either, I would say.
So there's some companies that are looking at CDPs and they're tempted to tear out marketing automation platforms because they feel the CDP can actually track all this information and then just serve up single emails. You'd actually just push a blast out, audience goes in, creates an email, sends out a MailChimp, and you don't need those orchestration capabilities within your marketing automation platform.
However, if you imagine the complexity of the data you're looking at within a CDP and you're trying to track. There's so many points of interest you're trying to track to really run that journey, then it could in fact be simpler to say, right, here's the audience that we really need to nurture, they're not reacting to anything else. So let's drop them in and put them into a long term campaign. And you can still check against CDP, whether they've hit another audience or the CDP can push a shared list of people to remove from those campaigns again. Yeah. Some of the orchestration, it depends what you're trying to achieve and where those orchestrations should sit.
As for me, it's a lot of it is to do with maturity, I suppose, maturity of the organization. So if you're running things, if you can pull some information about social advocacy and intent into your marketing automation platform, and maybe you've also got another intent platform, like demand based sixth sense, that sort of thing, which is pulling that information in and you can centralize that and get your messaging going out.
From market to automation. If you're not managing to really automate all those kind of messaging sequences, it's highly unlikely you're really ready to get the best out of a CDP. Yeah. I think you really need to have an idea of how you're nurturing, how those journeys look and stuff before you move on.
Otherwise, if you can't get your data settled within a simpler platform, if you just go for something bigger and pull even more stuff in, you're not going to see the wood for the trees and it's possibly even going to be detrimental to your marketing. You might even dip as opposed to even stay at the same point.
Tom Carpenter: Yeah. Okay. That's almost like you can have too much information that you're not sure what to do with kind of.
Phil Boyden: Yeah. And if it's low quality, so if you're not really putting things out so that the systems are capable of matching the different things that your customers are interacting with, then you're not really going to get that big picture.
Gen AI in content creation and personalization
Tom Carpenter: So we're in a world now where it's not just about digitalization, it's about automation and trying to reduce the manual efforts and also like be able to more dynamically personalize and adapt. So many of these capabilities and toolings will talk about their application of AI. Are there things that you've seen already which are more effective and easier for organizations to implement that help them to move towards a more automated world?
And what kind of capabilities some of these tools do you think can help people make the most of AI?
Phil Boyden: We're seeing a lot of generative AI coming in at the moment. I think that's one of the good ones that's really got a grip going on. I mean, I think we've all kind of done it. We've all put some details in so that Chat GPT, for example, it can spit something out that we can then start playing with because it's, it kind of helps you, it can really help you formulate your ideas if you're trying to tie some stuff together, the right prompt can really help with that.
And we're seeing that coming into our marketing platforms for, Content, we're seeing it coming in to marketing for subject lines. I saw a brilliant thing the other day from service that you can actually, it can create the content of an email to your customer, who's having an issue with sort of X, Y, and Z, which wouldn't necessarily be things tied together in a knowledge base.
So it's, it really helps enhance how we're dealing with the customers and speeding up that time as well. People can create content so much quicker now than they could in the past. I suppose we'll have to just watch over time to see if everything becomes really generic as the best message surfaces. And maybe we'll go straight back to humans writing everything again at that point.
Tom Carpenter: Are you seeing with some of the technology providers that they're building Gen AI based capabilities into the tech? So like you mentioned the subject line point, so that it's almost providing you different alternatives, or do you think that's something that marketers should be considering using as an aside?
Let's say I've got Chat GPT open when I'm creating my content and I'm trying to think of a Think about what different ways can resonate. How mature is Gen AI being integrated into these technologies at the moment, do you think?
Phil Boyden: So we're actually seeing different big vendors on the technologies buying and pulling in, or partnering with AI capability companies so that it is servicing within the platforms now.
It takes a little while for the product development teams to actually get these really working well together. But there's some great roadmaps out there coming for the future. One that I'm really excited to see coming into the platforms is, natural language requests. So I need a segment for this, messaging that does this, and you literally just chat through your criteria and it builds that segment and reporting has got some of the same capabilities coming as well.
Tom Carpenter: Yeah, I think that's great. I mean, across the lead to cash ecosystem and in many other use cases as well, we're seeing that being kind of two, maybe even three sides to the benefits of generative AI.
One, productivity, reducing the time to do things, like maybe you're spending lots of time trying to work out how do we position our content to different audiences? What's the right phrasing to use? Like how many different use cases can we adapt to? We don't have that much time to create different versions of the same thing, for example.
And Generative AI, I can speed that up drastically. So some great productivity gains internally, the ability to create more diversity and richness from maybe what you start with one piece of content and now becomes 10, 20, 30 pieces because Gen AI can reduce that. So I think some great productivity gains, which I'm mentioning there.
The other one for me being a customer experience expert is I think it also enables you to offer much more personalized experiences without as much effort on your side. So for example, like a lot of the marketing automation platforms will allow you to be like, well, if they did this, give them this content or if they do provide this, but the content that then needs to be provided means that you're having to create so many different versions of the same thing that you can't personalize, because you just don't have the time, capacity, resource to be able to do it.
So I think Gen AI also, because of the productivity gains, opens up this possibility to offer really personalized experiences and messaging to the point of it can be infinite personalization depending on what you know about the users. So I think there's so much power and I can touch optimize better customer experience from using Gen AI.
As with lots of automation, I guess the risks are; you've got to know about the customer to be able to personalize. You've got to have some idea of whether what Gen AI produces is going to work and is right. I think we've all of us have probably put things into Chat GPT or other AI tools and what's popped out doesn't make that much sense or it's a little bit wordy.
Like it's not perfect, right? So we're still learning from that because I think at the moment I agree that we're seeing the introduction of these tools and it's important for organizations to be ready. But there's still probably some risks in using that information initially. So it's great that you can start applying it.
It's not going to suddenly solve our problems and being able to personalize hugely to start with though.
Phil Boyden: Yeah, I'd agree with that. Some of those points hadn't even had to think about to be honest, but I suppose if you're using generative AI and you're creating all these really fundamental different pieces of content at the moment, you still have to build your rules into dynamic content and serve that up in a certain way.
And that could actually take more time and be less, less efficient than you just putting one generic email out in the first place. But wouldn’t it be great if in the future, AI could actually read that and build that email on the fly based on how neat and clean would your data need to be for that to genuinely work? It is so easy now for people to have a quick moment on social media, and that can kill anything you've done that I think we'd have to be really careful as to…
Tom Carpenter: It needs some external inputs into whether it's working or not. Yeah, absolutely. And I think at the moment that's why it's great if it can be used as a tool for productivity. It's great if it can be used as a tool to create more personalized content, but at the moment it's going to need some interpretation and decision making on how you expose that to customers. We're not quite at the stage, obviously embedded within the tooling or otherwise, that you can just kind of let it go.
Phil Boyden: Yeah. And I think Some of these platforms that talk about AI and stuff like that, in a way, not all of them are. So I think we need to be really careful on that as well. So you've got some that are genuinely AI, you've got some that are machine learning, and some are actually programmatic. So take a chatbot on a website, some of them will actually be talking to you and reacting to what you're doing.
Some are waiting for some keywords and we, I'm sure we've all had some proper nonsense come out when we're having issues with this. Cause my car keys aren't working. Have you thought about buying a house? Cause it's picked up on the word keys or something like that. You know, so, you know, if we are really looking forward to progressing our marketing and helping us, we really need to make sure that we're buying the right platform for our needs.
Tom Carpenter: Yeah, absolutely. And I guess that's where it comes into, where do you apply the AI in some of these situations as well? Like, are we applying that logic within to the CDP, are we, are we using it just ourselves at our desks? And I would say the answer to that currently needs to be, it could be all of those things.
There's not a one size fits all, as we've discussed with some of the capabilities. But is there anything where you're like, you know, you're, you're really cutting edge, if you're applying this kind of Gen AI or AI to certain elements of your marketing, or do you think we're still in a sort of experimentation phase at the moment?
Phil Boyden: I think in a way we're still experimenting. I've not seen anything particularly come right to the forefront in that, you know, all the companies that are doing this are benefiting a certain way. And I think a lot of this stuff is so new that there's lots of early adopters. Then they don't quite know what to do with the technology.
So it dips off and then there's less adopters than there were to even at the very start. And then people get to grips to how it works in the real world. And then it starts to adopt at a much slower pace than it did in the first place. And I think AI and these new platforms are definitely going through this kind of pure excitement didn't quite work out and through that kind of cycle.
So I think we need to wait for a lot of these technology to settle, see how they work in the real world. And then I think we'll see the big vendors picking up these technologies and tying them into the platforms as they actually become more mainstream.
There's a guy, Scott Brinker, and he basically does a map of the MarTech that's available out there. And, going back kind of 12 years, you could actually see all the logos on the screen and now it's literally just a series of dots. I'm getting older, but pretty sure it is just a set of dots we're looking at these days.
And AI is the biggest growing facet there. But just because a company has created something that has AI capabilities doesn't mean it necessarily slots in correctly and can build your business the way you need to and match those use cases and requirements that we've been talking about a lot.
Tom Carpenter: Yeah. So as we were talking about in some of the earlier podcasts, I guess, again, the important things here is AI is a bit like saying we need something digital.
Like we passed that horizon, right? Digital is now a must. So we're getting to the point where AI is now a must, but there are multiple ways in which you could implement AI based solutions, just as there were multiple ways to implement digital, moving from manual to digital. So I guess the main thing to do is work out like, what are some of the key metrics or business objectives that you're looking to apply or move the dial on?
And then what do you need as a kind of platform as a basis to be able to build on those objectives. And that's where you get to like, what are your key requirements? So there you're right. There are lots of elements you could apply AI. Maybe it's things like at the moment, it's about consolidation and therefore you'd want to use AI to be more productive, but maybe it's about breaking into new markets and new industries.
And you need some level of automation to do that. That's a different use case, isn't it? Because the important thing of AI is, everyone gets very excited that it's a thing that can be applied and can really optimize their business. But in anything that's kind of a bit overwhelming, like that it's easy to distill it to a few use cases, apply it to those use cases.
Phil Boyden: Once you've worked through that, what are the business requirements? What are your end goals? What are you looking to achieve in the next three to five years? What are the use cases for your customers in order to support that? And then what do you need to do?
And if there's some AI out there that helps that, great, definitely pull it on board.But if you're just going with AI for the sake of it, so you're keeping up with the Joneses, then that's not the way to actually drive your business.
The future of MarTech platforms
Tom Carpenter: So in a ideal marketing capability in the future, you would be seeing that they would be marketing automation platforms and CDP platforms. So I guess we might be seeing a convergence of those technologies in the future.
Is that something we're seeing already?
Phil Boyden: To an extent that they talk about orchestration within the CDPs, but if you take, your top class marketing automation platform. I don't think that's matched currently within CDPs, but there's so many out there, I can't know about all of them, obviously, but I really think we will see more convergence of the two platforms. And that this thing is kind of on the horizon where companies are bringing everything into one place, and it'll be modular, so you can still pick and choose, but it's, um, it will be centralized, built on one infrastructure, and it will really simplify everything you're trying to do, and the reporting that proves that you're doing it well. So, I think CDPs will very much have their own capabilities to send out email, and then the orchestrations will do that. They'll cover the SMS and things like that. I mean, there's some channels where you still actually need external providers in order to be able to do these things.
Tom Carpenter: Like a text message, for example.
Phil Boyden: Yeah, but the in general, I think it would all be centered in, in one platform.
Tom Carpenter: Okay, so you shouldn't be too concerned of an organization where you think just a CDP or just a marketing automation platform can solve your problems.
At the moment, that's probably unlikely to be true. You're going to need to combine some different technologies together.
Phil Boyden: Yeah, completely. And I've seen and also different sides of the business will see different things as well. There's a large company we're working with and I've been watching the same battle for years over everything we can do can be done out of here.
And the other side of the business is saying, no, everything we can do can be done out of here. And the truth is…
Tom Carpenter: Is someone right or wrong there, Phil?
Phil Boyden: No, they're not. So it is, you know, next best action isn't necessarily what you need served up if you're spending 18 months thinking about putting a whole new software or computer infrastructure in your 30 floor building. There's different approaches need doing for different sides of the business.
Tom Carpenter: I'm sure some of our customers hate me saying this, but it really does depend, right? Like if it was an easy answer and it's just like, you should do X, you should do Y in certain scenarios, then everyone would be doing that. And like, there's loads of choice out there, which is great for us as consumers, right?
We’ve got a great breadth of technologies we can use. But it is so important that you understand what your business objectives are and then you make a choice that relates to that, right? So unfortunately we are going to have to go back to that same old point in this, like really understand what you're trying to achieve.
I'm not assuming that there are any organizations out there that are just buying technologies for the sake of it, but it's a complex market and the tech providers are great at selling the technologies they have. Just make sure, I guess, you think about that before making those choices and if you need external support, challenge the technology providers themselves or look to solution providers to support you.
So it's been great to have you here again, Phil. So Phil Boyden from Sojourn Solutions and myself, Tom Carpenter from Clarasys. It's been great talking to you through some of the complexities of the MarTech landscape today.
Thanks, Phil.
Phil Boyden: Thanks, Tom.
