Ben Kruger 0:21

Hey, thanks for having me. Excited to be here.

Ben Kruger 0:41

Yeah, absolutely. So it wasn't by design, but my background brought me through a lot of the marketing funnel. I started in attribution trying to analyze the impact of online engagements to offline sales at a company called RevTrax. I then went over to retention at a company called Bluecore who handled email triggers and became a full-blown email service provider. So I got you know really sticky with LTV and retention there. And then I joined Google as an e-commerce account strategist. That's where I met Event Tickets Center. They were one of my clients and during our time working together while I was at Google I helped them lean way more into Google's AI and the marketing tactics and strategies that were coming out you know this was coming out of COVID so 2021, 2022 things were changing a lot at Google and the team at Event Tickets Center ate it up really adopted things super thoroughly and strongly and you know I had worked with hundreds of clients and at Google and I had never seen someone dive so deep and it work as well as it was promised.

So with that I you know I left Google and joined ETC to just continue that sort of rocket ship and our adoption and it's been awesome ever since.

Ben Kruger 2:14

Yeah. Coming out of it, I think, you know, people were eager to get out and experience things live and artists were, you know, starved from their touring revenues. So, perfect storm. Plus, you know, the AI changes. I think we were one of the first to adopt and go like full throttle into it. So, it was really a perfect storm like 2022, 23, 24, and today.

Ben Kruger 2:52

For sure. So, it's probably not affecting our IT infrastructure as deeply just because you know that's our baby and we have like highly qualified engineers and developers working on that. I they are obviously using AI maybe as a co-pilot but you know they're approaching that with like precision and quality. So I think using their expertise there is really strong. However it has helped our marketing organization and at the surface, we are truly just a marketing company. We're you know trying to connect fans with ticket inventory to shows. And it's completely transformed our marketing org.

We're a lot leaner. People are doing a lot more. I think one of the biggest shifts we've seen is instead of people on our team like pitching a new tool or a new strategy on paper, right? Like writing a business case or like trying to pitch it with slide decks, they're coming with a full-blown prototype. So I can click, you know, our team can click through it. We can play with it. We can envision it either if it's an internal tool, how our team's going to use it or how our customers are going to experience this new feature that someone's adding.

And these are non-technical people being able to you know, come with like I don't know something that's like 80% there. When you can see the full-blown concept and we're so there's that and then how quickly we're able to iterate and move on these things. It's really transformed the way that we go to market improve our experience with our customers, but also internally like there's a lot of production and labor that goes on in building out our ad campaigns and our landing pages and it's all just really accelerated both the quality and the experience that it delivers.

Ben Kruger 5:08

Totally so we you know we rely a lot on our CRO the conversion rate optimization team so it's helped them immensely with prototyping and coming up with new concepts to test to implement on our site to improve conversion rate. In two ways, right? Like one building out the actual feature or update or new funnel step that they want to add into the funnel, but also being able to analyze our session data and our funnels and our heat maps to understand where there's drop off or where there's potential gaps to fill in where people maybe hitting the back button or rage clicking or getting confused, right?

We can analyze so much more data now by leveraging AI. And of course it's fact checked and verified, but we're able to find a lot more gaps and opportunities and there are things that we, you know, there could be very granular things like I'd say pre-AI we were focusing on more macro like let's improve the funnel across all of our events where now we could do like oh minor league baseball has this pocket of opportunity or country music has this pocket of opportunity. So we can go a lot deeper and a lot more granular now with the amount of data that we can capture and analyze and then build against as well.

So it's we're able to do things now that we always knew we wanted to do but we didn't have the resources and the bandwidth to do it and AI has definitely enabled us to do that now.

Ben Kruger 6:59

Yeah, totally. I mean the models are only so good, right? They're only trained on what's available to them. So all the proprietary information you have is super valuable and you know it's going to help you get better outputs from the models but also it's things that your competitors or others can't mirror or can't model. Yes we have s like there are other ticket platforms that are similar to us but you know we do very well in one type of show where others don't. So we have a we attract a very different audience and very different types of customers.

So, we could, you know, really lean into that and leverage that to our advantage. So, you know, we've got like you said, 15 years, I think it's even a little bit more of data and obviously purchase data. So, what someone bought, what show they went to, what venue, where they lived versus where the show was, like are these people traveling to shows, are they not, are they buying the cheap seats or the premium seats? All of this is plus all of our website session data, our customer service, inquiries, tickets, customer reviews, right?

This all just sort of gets modeled together. And luckily we had been building a data warehouse alongside in parallel and now like you know all of the data is clean and organized and now we could just add AI layers into it to analyze it and action on it. So yes, like the boilerplate models are great, but the more that the more context we can provide about our business and super specifically with lots of scale, it's way better and more powerful and impactful than just using it off the shelf.

Ben Kruger 9:01

Yeah, absolutely. I think a really good example of that is an email campaign we recently rolled out where we know the past events that someone has either browsed or purchased and we know obviously like very precisely the artist, the venue, the category of the show, etc. Etc. And then we have our catalog of either soon to launch events or events that are currently live. We can match all that up to give people highly personalized recommendations of what shows they should be looking to attend next. And it's more than just matching on like you've seen country before, here's country.

You know, we can go really granular and leverage Spotify data and other data sources to know a lot more about the artist to make these matches really high quality. And then within that we have personalized content about, you know, referencing the shows that they've seen before and why we think this is a match. You know, sometimes I'll see the emails that'll be like, oh, like these are this artist's top three songs. They sound like these from this person's catalog. You're like, you're going to love it. And then we have tons of venue information like the best place to grab a beer at the show or like what you can expect with parking, etc. Etc. So, we can really get really deep and give like high quality recommendations and help people have the best experience possible.

Ben Kruger 11:09

That's exactly right and yeah and trust is a really big factor in this business. You know essentially the same tickets are available across a variety of different platforms. So to help us differentiate and stand out and become the trusted platform, these things really help us. And we do leverage a lot of our reviews and our customer service tickets to create that content or proactively try to guess what someone may be unsure about or may have questions about. So yeah, it helps us there tremendously as well.

Ben Kruger 12:42

Yeah, absolutely. So, we have a really heavy emphasis on quality and QA. So any work that is either done by hand or by AI is getting reviewed by humans that are looking for you know quality and making sure that the output is intended is matching the criteria that we intended for when we were building out the automation or the manual work. So that has always been something that we are really strong in and now I think we just have more people leaning into the QA side of things. Like we've taken people who were doing things by hand and now they can move over to more QA and analyze the outputs that are going back into the system.

Which is really important. So I think we're able to do a lot more now and at higher quality. So that's been an awesome shift that we've made. And then I think where you know myself I definitely got caught up in this and where I think the organization has learned over the past two years is we were very quick to automate things right like a lot of these tools came out and we're like oh I could just have AI do this and just throw it in and it did a pretty good job.

It probably did 70 or 80% of the work. But what we try to really preach, and I think everyone has organically just learned this themselves, is like before you automate something, you have to really go in and do it like click by click extremely manually and really understand the nuances of this workflow before you even think about automating it because it'll, you know, the AI output may seem good on surface, but it's missing a lot of things and if unless you know exactly what to look for or what to expect, it's going to miss it.

And you know that just compounds the more that's done the worse and worse the output gets. And then I think when we were like just quickly automating things and throwing things at a wall, we would like set up a process, never think to check back on it, never look at how it's doing over time. What are the outputs? Like you know the quality degrades if you just keep letting it run and you forget about these processes and then other things depend on that process and it all really breaks down. I think I attribute a lot of that to being like these are very normal I think processes for engineers and developers but all of us nontechnical folks like don't think about didn't think about these things.

So we've kind of learned that more of an engineering mindset I think like breaking things down into small problems and into procedures and we're now applying that to our marketing expertise which I think is which is awesome. But it we had to go through that learning curve but that's it was an important one.

Ben Kruger 16:02

Sure. Yeah, I don't think it like the use of it needs to be that fancy. Like I think you really just need to get a light bulb. Like every individual needs to get that light bulb moment of seeing how it actually works and how practical it is and that it doesn't need to be this whole overblown like fancy design like it doesn't need to be this whole thing like it could be very simple a good example of that is a lot of my work that I'm doing is with CSVs right I'm downloading data from Google ads or meta or from wherever it may be GA4 or whatever pulling it into Claude.

I use Claude Cowork a lot and it's just I'm working with that CSV and manipulating the data and asking it questions and then it's either rewriting something, restructuring something and giving me a CSV back and I'm just importing that back into the platform like no APIs, no MCPs, nothing fancy. It's highly controlled. I know what I'm giving it. So it's like you know I'm very much in I have a lot of visibility and but it's really like 10x my ability to do things right. I can create campaigns at scale. I can get a lot of work done.

And I can do deep analysis, but it's not technical. It's pretty straightforward but still very powerful. So I think that was a very good introduction to the possibilities and that's what I'd advise someone to play with just like put data in and get some data out and see what it can do.

Ben Kruger 17:37

Probably both. We're a heavy Google Ads shop. So, you know, a campaign needs keywords like what search terms are we going to bid on the ad creative you know, the headlines and the descriptions that you see in the text. So, yeah, it's using years of our performance data like we talked about to understand what types of ad creatives work and what doesn't and what types of keywords and audiences should we be targeting. But that's all baked in the context now. So, I can be like, you know, whip up a new campaign for Yankees tickets and it'll use all of its context and know like Google Ads needs headlines that are no more than 30 characters and it'll trim the content to meet that criteria, etc. Etc. So yeah, that's one like really strong use case that we have.

Ben Kruger 18:51

Yeah, absolutely. So, both of those organizations are trying to protect fans rights on the secondary ticket market. You know there is a lot of lobbying and movement to restrict fans abilities to sell or transfer tickets. You know the a lot of the industry wants to keep the entire ecosystem controlled in their own environment right but let's say you have a sick kid or you can't make a trip or your flight gets canceled like I think you should obviously have the right to transfer that ticket and be able to get money back on it and have the right to do so.

So those both of those organizations are standing up for consumer rights both in like ticket transferability. A lot of states are trying to implement resale caps on how much you could resell a ticket for which I think it's just like an asset like a house or a car. And I think once you go down that road of trying to limit resale value on those assets, you know, it's it turns, you know, a little bit against what I think the country stands for. So yeah, we're heavy supporters in protecting fans rights and broker rights as well to resell tickets.

And yeah, so we're heavily involved there and I think it's best for our fans and also for our inventory suppliers and our brokers and resellers.

Ben Kruger 21:02

Yeah, I think this like rapid pace continues. I you know with the shiny object syndrome like I continuously see these new like wwrappers come out of like you know ad creators or like CMO for your business or CFO for your business like these AI SaaS tools and then one you could build it yourself very quickly with any of the frontier models and two like Anthropic and ChatGPT and OpenAI like keep coming out with they just put these like these solutions to bed quickly. They build their own product in house and then release it to the public.

So like that's why I stop chasing a lot of these things. It's I'd rather just build it myself because I know the business needs and how it should work versus relying on another tool. So I think that could stop and you know people just start to hone in more on building tools for themselves. In terms of the marketing landscape in performance marketing like where we say I think the rich just continue to get richer. I think the more that enterprises and organizations adopt these tools from a marketing perspective specifically with Meta or Google Ads the more that they're going to be able to take more market share.

I think that's what helped us rocket ship coming out of COVID. And I think it will just continue and you know our ability to see the see like a year or two ahead and understand like Google's implementing these things now to set them up for this later like we do it and we it may not it might be a rocky start for the first couple months but then you start to see it really start to rise and improve and then you're set up for the next tranche of new updates that come.

So, you know, you kind of got to bite the bullet in the short term, but those that do, I think it pans out for, and the rich just continue getting richer and like the smaller players get squeezed out.

Ben Kruger 23:34

I mean, there's always a chance. I mean, I think I just think the window of opportunity like is smaller. Like someone will come out with something great, it will work where historically maybe they'd be able to milk it or continue growing on it. But now I think everyone can just catch up really quickly to it if that makes sense. Like I think you can just make like someone's feature just one of your own and gobble it up a lot quicker than you used to. So like you can exploit things for a little bit but then everyone catches up and you know if it's making money people are going to hop on it. I think it's just it's lowered that barrier a lot.

Ben Kruger 24:24

No I would just say like I don't know. I have some like friends or family here that are in jobs that I think are susceptible to getting automated or built out and I you know I would just I always try to encourage them to hone their skills, try to build something on the side, try to use it in their core job today. And I'm talking about just AI at a very basic level. Just yeah more encouragement for people who haven't adopted or have stayed away to dive in and you know have skepticism and you know and curiosity but I think the best way to learn something is to do it and I just hate to see people sitting on the sidelines where there's like a gold rush like this right now.

Ben Kruger 25:52

LinkedIn is probably best. I'm on there here and there. Yeah, just find me, Ben Kruger. Shoot me a DM.

Ben Kruger 26:02

Yeah, thanks for having me.