Stephen Banbury:
I’m delighted to be hosting the webinar. And actually, today I’m being joined by former colleague and season marketing professional Ryan Jenson. So Ryan delight to do it with me for this. Perhaps you could just take a moment and and introduce yourself.

Ryan Jensen:
Sure. Thank you, Steven. Yeah. Steven and I had the opportunity to work together at reputation.com not too long ago. So my background has been in B2B marketing primarily in the areas of growth and operations. So understanding where that product market fit is how you come up with an appropriate strategy and message for that person, and then how to leverage certain pieces of technology and process to be able to do that at scale.

Ryan Jensen:
And so this is a wonderful topic for me, because AI certainly facilitates that kind of motion.

Stephen Banbury:
That’s great. Thank you. So let me dive into the agenda, so I’ll do a quick introduction around sort of AI and that marketplace and the synergies with marketing, and then we’ll go into the topics around data and automation and enhancing the customer experience.

Stephen Banbury:
Both Ryan and I will do. Look at a couple of used cases and a real world examples for that. And then hopefully, we’ll have time for QA. Or at least a couple of questions. So please send those in, and and Brian will actually capture those as we go through this presentation.

Stephen Banbury:
So let me start with the landscape. And really why this is so important. And since 2019 that there’s actually been wider public accessibility to Gen. AI tools and platforms, and with the success of models like open eyes. Dally I see the first dally in 20 and 20 generative AI models have become more refined, and we saw a massive increase in adoption with the release of Chat GPT. Back in less than a year ago, actually back in the end of November 2022. And, as you can see, the adoption.

Stephen Banbury:
Our strokes, any application before from TikTok to Instagram, Pinterest, Spotify, etc. So in less than 2 months they had over 100 million users and today that’s well over a hundred 70 million users. So the pace of change has been pretty substantial. Sonia hung from Sequoia capital posted this out on what formally known as Twitter X. 

Back in October last year, and as you can see, the landscape that she pulled together was pretty, I mean, not tiny, but small. And then, when you look at September of this year, you can see just the ex explosion in the amount of applications and tools in this space. And this doesn’t even include things like the infrastructure and some of the other tools that support it. So you know, I think you’re probably familiar with, like the Mar Tech loomscape, it’s getting that way and not surprising when you see the billions of dollars that are actually being invested in generative AI and the applications in that space.

Stephen Banbury:
So, Marketing and AI. So I think about it as like a dynamic duo in many ways, and the list here is a list that was compiled by the Marketing AI Institute, and they published last year the state of Marketing and sales. AI report. 

Stephen Banbury:
They asked a number of marketing people to essentially look at 50 different use cases and actually rank those in terms of importance. Now, to be fair, there’s obviously more than 50 use cases for marketers. In fact, there’s hundreds, probably thousands, of those. But of those these were the top 10 that they came back with and interesting. 4 of these, when you look through, these are actually classified as dealing with content marketing, and for actually as analytic cases. So marketing and AI, obviously a bunch of use cases. When when you look at that. So let’s set the scene a bit about marketing and the growth there. So let’s look at a data driven decision making. 

So simply put, I would say, AI unlocks invaluable insights from data that’s too large and complex for humans to easily analyze. And so this enables us to be more informed and and forward looking across industries and these are just some of the industry examples. That I thought of that I actually utilizing. Ai. So if we look at a couple of these, so if you look at the transportation industry, for example, you know Uber leverages AI to forecast writer, demand across locations. And you’ve probably seen this if you use Eva Uber, or even Lyft, until you see the surge pricing that incentivize drivers to go to locations where there’s going to be more demand and for healthcare AI tools to use to analyze medical records and diagnosis data to identify trends. Essentially so that they can, you know.

Stephen Banbury:
Provide better preventative care and resource planning when you think about this in just marketing terms. You know, you see, AI impacting in terms of predictive lead, scoring, ad targeting, dynamic pricing similar to the Uber example I just mentioned, customer satisfaction, campaign, optimization, and multi-touch attribution, all of these utilizing AI in the marketing function. So to go one step deeper into marketing. Let me hand it over to Ryan and he’s gonna talk about an example of identifying and how to essentially reach out to your ideal customer profile. So over to you, Ryan.

Ryan Jensen:
Sure. And what’s really exciting about this, when Stephen was going through the examples, I’m gonna just pause and talk about how it’s applicable for me. So some of the examples that I share today are gonna be examples of things that we’re currently doing within my team where I’m at, and others are examples of what we would like to be doing. Future state. These are things that would really drive value.

Ryan Jensen:
But at, you know, at the end of the day, you know, it’s machine learning. You know, you need to have the data. And then once you train the data. You’ve got algorithms that are able to detect patterns make predictions and that that’s really cool for people that have had a data science background. You understand that it could be really difficult to structure your data, get it to a point where you can actually do an analysis. 

So if you’re marketing, and you want to do a conjoined analysis to understand what characteristics your product should be. Highlighting back in the day. That was very difficult. Time consuming arduous required a lot of different people. And what’s really exciting now is, if you can get the data, the AI is able to train on that data and give you insights that otherwise would have taken a long time and a lot of effort.

Ryan Jensen:
And for me, in the world of growth, the first thing that you always wanna do is understand how big is that market that you’re trying to reach based on what your specialty or niche is? 

How many more of those types of customers based on your best customers? Can you identify? And in the past, you know, like I said, you’re having to call through bounds of data in, let’s say, salesforce to look at things like deal sizes, close rates having to deal with customer success to get things like Nps, scores or customer sentiment and financial data, and then having to bring together all those disparate groups together to say, What does our ideal customer profile look like. And then. Now, taking that information, how do we come up with a program to reach more of those type of people?

Ryan Jensen:
But what’s cool with tools like 6 cents. And this is the example that I’m gonna use. You’re able to do that in such an accelerated, automated fashion because you’re able to bring in a lot of those data points. What are the characteristics of your ideal customer? Whether that’s you know, your typical, you know, demographic or psychographic information or even financial data and brute. 

Put that into the solution and then create segments that will now alert you to when somebody that fits that similar profile is showing intent whether it’s by visiting your website or by searching for keywords associated with your category. And now what’s really cool is not only can you alert your sales team in real time. But you can also automate campaigns to do some nice marketing air cover in the form of ads, within LinkedIn within Google and other platforms, and really start to get to the ahead of the curve and it enables you to dial in your dollars. So instead of just spending your money nondescriptly on a bunch of different things, you’re able to get more laser focus, because ultimately these types of efforts are enabling you to dial in on exactly who is the right party? And is that right party showing intent?

Ryan Jensen:
And so for me, that’s a gold mine, because marketing dollars are limited. And in today’s environment, that’s even more so the case. And so this tool enables me to spend the right dollars on the right kind of activities with the right people. So that is a really great case study that I’m excited about. Back to you, Stephen.

Stephen Banbury:
Yeah, that’s great. That’s super insight. Tools, like 6 sense, have done a really good job of incorporating AI into its platform. And I think for for marketing people. When you look at your Martic stag. Many of those are actually utilizing AI already. And so you know, how do you get more familiar with that? To to maximize your investment. I’ve certainly found that. There’s a lot of Motec in the companies that you work for. Not all of them are being used to their fullest. So super insightful!

Stephen Banbury:
Let me talk dive into with right now about automating some of the routine tasks. So again, going back to the state of marketing and sales. I report 74% of respondents said, that you know more of a quarter of their tasks are going to be intelligently automated. Over the next 5 years. And this is actually quite an increase from what they’re actually like, how they using it today.

Stephen Banbury:
And actually, 41% of the marketers anticipate over half of their tasks are going to be automated. In the next 5 years. So a big increase there. And I’m gonna give a an example around zoom. And then I know Ryan’s gonna talk about a a couple more real life examples. So zoom released. And I know whether you’re using team or Google chat or huddle, or we’re using zoom today. So all pretty familiar with this tool, certainly.

Stephen Banbury:
During the pandemic and post pandemic. They’ve released new functionality with their AI companion release. and it’s pretty interesting. And if you don’t have access to this is probably because your it system and the Administrator hasn’t actually like released it yet. But that’s something they could do. So you could play around with it, but you can jump in if you joined a meeting late. So, for example, this webinar, you could ask it to catch me up on things that I’ve missed.

Stephen Banbury:
You could say, Hey, did they mention? My name? Was Steven mentioned? In what context was I mentioned, and that would keep you up to date. In addition to that, it actually helps you compose chats within the meeting. It actually composes and replies to emails as well as recapping and identifying action items during the meeting which is pretty cool. So you know, as you think about I had a meeting with Brand in anticipation of this webinar and post webinar, it actually generated a summary of what we discussed and action items, and emailed that to me with little to no interaction from Brian. So I definitely recommend you play with this if you haven’t got this switched on, maybe. 

Try and get your administrator to give you access. But again, you know the days of note taking and putting action items, I think, for something like Zoom are probably long gone, but you know, I’m a terrible multitasker. So actually, I can just focus on the meeting in hand. Which is a way. Better use of my time. So that’s a very recent release. Actually, last month.

Ryan Jensen:
and there’s gonna be, you know, across all these tools, there’s gonna be more and more functionality built in to these applications. So, Rob, perhaps you can talk to the 6 cents email example. Yeah, so this is something that we’re investigating right now, and you know other tools like Saleslav do something very similar.

Ryan Jensen:
But you know, at its heart is it’s automating a lot of the work that goes into some of these outbound cadences that we’re all familiar with that are enabled through sales, log outreach, salesforce cadences, etc. So when you think about the typical outbound sequence that you have to build one. There’s a lot of work upfront to figure out.

Ryan Jensen:
How do we segment the data to be able to trigger the right responses. So an example that could be somebody that’s been in a lead status have attempted to contact for more than 14 days, and then it could trigger, maybe some spear messaging to be able to wake that person up to get a demo booked.

Ryan Jensen:
or there’s people, you know. Segment might be a lost opportunity based on certain criteria. So you’ve got the work that you know goes upfront there. Then you’ve also got to connect with hopefully marketing to get you some nice, impactful messaging that’s on point that can prompt a response. And then you’ve got to be able to be situationally aware to know if this response happens. Based on, you know, response, I get from a person maybe follow up with this and you know that takes a lot of time. And this, what you’re able to do is it automates a bunch of that so that you can input what your goals are? 

Who your audience is. And then it’s able to be contextually aware to where you’re able to see if this person responds this way, we can send a response automated. So instead of having to build kind of that hard and fast logic, you’re you’re able to be a little more flexible and responsive. And so this is something that we’re currently, you know, in the process of trying to better understand.

But the promise of that is great, because I can’t tell you how much time. My team my content team has to spend on leveraging things like the Sas Academy materials to come up with really good, impactful messaging when something like this, in concert with maybe a little bit of chat, Gtp. Can help really take a lot of time and effort out of their day to be able to do this at scale and speed.

Ryan Jensen:
And then another routine task is SEO. So you know the website. You know, II speak from experience, and most of you probably agree. But organic searches to your website typically are your best converting leads. Those are the ones that have the highest likelihood to turn into an opportunity and close because they’re looking for you, and they’re demonstrating intent.

Ryan Jensen:
So you need to spend a lot of time to make sure that you are getting top of full first page present on Google being or whatever search engine you’re you’re targeting and a very competitive depending on what space you’re in and what keywords you’re going after. And

Ryan Jensen:
so a lot of time, traditionally is spent on developing things like meta descriptions, meta tags, and other things, because those still are important facets to your SEO strategy. And here’s an example that our team does where you know just a a typical page where we say, Hey.You can give it broad guidance, and in this case we’re asking chat should be to give us a meta description, and it responds great.

Ryan Jensen:
And we give in some information of what we’re trying to accomplish and what that page is focused on. And within seconds we get a very nice, impactful meta description that we could drop right into the HTML that otherwise probably would have taken, you know, even a seasoned, you know, marketing content writer, probably 2030 min to come up with something that would work. And so great, you know, the examples I’ve shared are data leveraging data for insights. And then the other great thing is tasks. I mean, both of these examples are very time intensive tasks that AI really speeds up and does so typically in a very good manner that requires very little editing after the fact.

Stephen Banbury:
Thanks, Ryan. That’s it’s just a great tool the let me forward to Cx. So enhancing the the customer experience. So you know, AI aims to make custom interactions with brands smoother, you know, more intuitive and certainly more tailored to the individual experiences and needs. And so here are some very well known brand, so they’re utilizing AIin slightly different ways, but all using them. So let me pick on dominoes. Pizza, for example. So Domino’s pizza has an AI powered chatbot. That’s actually called Dom. So some very creative thinking about the naming there. But Dom less customers order pieces directly from Facebook Messenger, or through voice commands.

Stephen Banbury:
Brands like Netflix and Amazon. clearly using recommendation engines to drive sales and engagement. What I actually didn’t realize in the case of Netflix is. It’s estimated that 80% of the content watched on Netflix actually comes from its recommendation system. Which which I found pretty stunning when you look at spotify. And Airbnb, for example. You know, they’re leveraging personalization algorithms. An example. 

For me, at least for like Spotify is that it creates a weekly playlist where it’s offering me songs based on you know what I like? Am I listening? History? And Ikea, they’re actually using, not just AI, but using augmented reality. So with their app, you could actually look and when you look at your own home, you can see what the furniture actually looks like within your own space, which is which pretty amazing. So I know Macy’s uses. Ibm Watson. So all of these are using AI to create better customer experiences. Across the board.

Stephen Banbury:
Another AI tool that customers or brands are using is actually sentiment analysis. So let me talk a little bit more about this one. In this example. Health care providers, and it’s not just health care providers. It could be retailers. It could be car manufacturers and dealerships and property management companies, but providers such as banner, health and kindred, they use a platform reputation, Uhcom’s. They actually use that natural language processing platform to break down customer sentiment and then and analyze the feedback and social mentions to highlight trends and topics in real time.

Stephen Banbury:
So for a healthcare provider. They’re looking, not just for feedback. In one instance, which could be, you know, how was your doctor’s appointment? They’re actually looking across the whole patient experience. So you know, what was, could you find parking easily? What was that experience like? Was checking in easy? Was the waiting time easy? Maybe use. The restroom was a rest. Rooms clean. How was your interaction with the doctor? How was your check out?

Stephen Banbury:
How was that process? And then what was the post doctor follow up like. And so in real time, whether it’s through, you know, Twitter or Facebook or some type of survey, they can actually react to the customer sentiment around. Is this a good experience or bad experience? So you know very simply for me. Customer experiences, you know. Listen to your customer. hear what they have to say. understand it and take action on it. And you can see there’s actually like a sentiment map here where you can see, you know, feedback on customer service. This is actually around property management, this particular map. 

But I think it does a really good job of giving the brands the full customer journey and experience as they see it, and how they feel those interactions ago. I don’t know if you wanted to pile on to that because you obviously have experience with this platform. Ryan. Yes, what what I really like about it is the fact that it can leverage insights from unstructured data. So typically if you’re involved in trying to understand customer sentiment, you’re relying on an Nps score

Ryan Jensen:
or a survey through a tool like Waltrix, which is very formal, and requires a little bit of time and effort. But what’s cool about this? Is it grabs all of that, you know. Just random comments from, you know, Twitter, feed, or email conversations, and it gives you a more broad and a more depth depth in terms of understanding what sentiment is and how people are seeing your brand.

Ryan Jensen:
And I think that’s where tools like this and AI in general can really help out because it really expands your reach and being able to understand how customers feel about you. And I know that was a question that one may maybe get to a little more depth later about psychographics and sentiment and a tool like this, or certain chat bots are able to do that. They’re able to sense. If I make a snarky comment and treat it as such and be able to respond accordingly.

Stephen Banbury:
Yeah, that’s right. And actually, on the side of graphics. There’s tools like we mentioned Ibm. Watson, for example, in the in the case of Macy’s. There’s crystal Athenio brand watch and that I think a bunch of other tools, too. So you know, maybe we can package that up and send it to the personal offsite question Ryan. So maybe if you email me after the the webinar. So what’s the the future of for marketers? And a question might be, is there a future for marketers with AI? And and suddenly, Gen. AI. And so this quote I took from Paul Roots from the Marketing AI Institute, and actually everything. Originally it came from. 

A doctor from a hospital in Pennsylvania. and it’s AI won’t replace marketers, but marketers who use AI will replace marketers who don’t. which I thought was very prescient. and you could take that marketers function, and you could replace it with customer service manager sales. I think you could. In in fact, it was originally used for radiologists by this particular doctor. So there is no guide, and there is no manual for many of these tools like Chachi, Bt. And others, so I would strongly encourage you to if you haven’t already started to spend time experimenting with this technology and create your own use cases actually think it’s you know, we all will have will have our own use cases depending on what our you know.

Stephen Banbury:
A function is within marketing or outside marketing, and I think it’s an opportunity to become the the change agent within your business or your function to be the one that sort of drives the next frontier in digital transformation. So if you haven’t started, I would like dive into it. And I would also encourage you. If you have a team to get them to invest and spend time doing this as well.

Stephen Banbury:
Any thoughts there, Ryan.

Ryan Jensen:
No. And what’s cool about this is, you know, Stephen and I are by no means experts on this is this is all we’re in the early stages of how this is being applied in, you know, in mass. And so it’s gonna be really cool to see how the used cases expand. But they’re gonna be there. And so this is gonna be the reality of our lives as marketers. And so we’re coming up with new use cases hopefully, us and other practitioners, you know, day to day, week to week. So this is just the beginning of it all. Yeah, I think that’s

Stephen Banbury:
We obviously had the question of cycle graphics, and we threw out some names and we’ll we can respond to. Someone can email me afterwards, and we can put some more in. But we had a couple of questions before. Tie into that Ryan. The first one was.

Stephen Banbury:
What’s a cool? What’s the coolest thing that you’ve seen, so far as it relates to Gen. AI, or even just AI, generally.

Ryan Jensen:
Well like for me. I you know I like the the that’s the strict strategic side. And so the example that I gave with 6 cents or other tools is really cool. Because there’s so much data out there, and just having had to go through those go to market exercises that were really difficult, and to be able to leverage a tool like this instead of have to rely on. You know a, a say, a business analyst, and 3 other roles is just really cool. And then on the content side, it’s just really nice, because I’m not, especially when you’re writing marketing content.

Ryan Jensen:
That can be a bit of a challenge for somebody like myself. And just to be able to. Ops, you know. Send that over to, you know. Tool like chat is is really is really cool. But you know, tools like intercom or drift chat. You know something that we’re looking at right now, because you know in the in the past you’d have to rely on a lot of elaborate decision trees and having materials available. But this enables you to once again have more flexibility, and to have the AI understand somebody’s sentiment, and then be able to respond contextually as opposed to have to anticipate that and then build a rote response to it. 

So I think those are examples that for me, help me in my day to day. And you know, granted, those examples are limited to me as you guys do your own research, based on where where it is that you’re trying to accomplish you’re gonna find probably different examples that will have just as much impact.

Stephen Banbury:
Yeah, I mean, one of the other questions will ties into it. And I’ll tell about my coolest thing. But was recommendations on tools and platforms you should be experimenting with, and that, as you could see from that market map, there are lots of tools from chat. Gbt. Github, co-pilot, mid journey, Firefly, Jasper, for example. If I was to pick one it would be Chat GPT.

They have a free version, but I would recommend you spend the $20 a month, whether it’s for a month or 2, or 3, or forever for that chat, Gp. Plus. It’s got there all 4 and play around with that cause. It’s got functionality. So you can actually search through Bing, you can it has this image generation tool from OpenAI called and what was very cool for me is actually took a screen, grab a scroll screen, grab of a home page.

Stephen Banbury:
and I drop that into Chat Gpt. And I asked the question, how can you optimize this homepage for lead generation? And 30 s later I had about 12 bullet points run that actually told me and suggested ways in which I can improve it. So it read the image all the text and may suggestions not just on like subject lines, making them maybe more value and benefit orientated versus feature and function, but around, like the Ctas and placement of those utilization of chat bot. So you know.

Stephen Banbury:
If you are in the demand, gen, or website design, you would have got to those all those bullets, probably. But the fact that actually generated that in less than a minute actually blew my mind and and was quite, quite the experience for me. So beyond those new tools.

Stephen Banbury:
you’re probably using tools like HubSpot today that actually have AI built into them. So this is genii tools. And I think you should plan, experiment with. But actually look at the tools currently within your multi stack and get really savvy and smart with that AI that’s built into those. So anything to add, Ryan. No, and I and I would say, you know, we’re still in the early stages, so I’d still recommend that you do spend some time. And if you’re creating content, for example, just to review it, because one thing to keep in mind with these types of tools is they’re only good is the data that they’re reading. And so one of the early criticisms so far is that these types of tools will just re-inform existing biases.

Ryan Jensen:
So always, you know, on the what my team does is, you know, it’s great to be able to develop content, but always spend, you know, a couple of minutes just reading it, cause you ultimately own and understand the strategy, and just spend a few minutes shaping it a little further to make sure that it absolutely is on branding on point with what you’re trying to accomplish.

Stephen Banbury:
Yeah, that’s great point. So I know we are a couple of minutes over. If you would like and haven’t had the opportunity to ask questions to get this answers. Please email me Steven at expert marketingadvisors.com I will do my best to answer that. I will forward that to Ryan as well, and and we can get back to you on that. Thank you very much for joining us today. I know Brian will be following up and have fun and enjoy the the journey of of AI as that changes. And hopefully improves our lives as we move forward. So thank you very much indeed. And I appreciate you joining us today. Thank you.

Ryan Jensen:
Thank you.