Data Analytics Chat

The Power of Personalisation: How AI Influences What We Buy

• Ben Parker • Episode 65

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In this episode of Data Analytics Chat, we sit down with Allison Olson, Senior Vice President of Analytics Solutions at Merkle. Allison shares her inspiring career journey, filled with proud moments, challenges, and valuable leadership insights. She talks about the importance of following your gut, taking risks, and how COVID-19 reshaped leadership attitudes.

 

We then discuss how AI is transforming personalisation and, ultimately, buying behaviour. Allison breaks down the shift from static to dynamic personalisation, exploring how adaptive experiences powered by real-time data guide customer decisions. She also covers the ethical use of AI, strong data foundations, and the transformative role of generative AI in creating truly tailored customer experiences that influence what we buy and why.



00:00 Introduction to Leadership and Personal Growth
00:21 The Role of Gut Instinct in Decision Making
00:52 Challenges and Ethical Concerns in Data Analytics
01:34 Welcome to Data Analytics Chat
02:12 Alison Olson's Career Journey
04:46 The Evolution of Leadership
07:11 Impact of COVID on Leadership
08:37 Learning from Failures and Taking Risks
10:37 Balancing Management and Leadership
13:45 Skills and Mindsets for Leadership
16:32 Advice for Aspiring Leaders
21:01 Introduction to Dynamic Personalisation
21:59 The Concept of Dynamic Personalisation
23:23 Static vs. Dynamic Personalisation
25:34 Real-World Examples of Personalisation
27:22 Data Types for Adaptive Experiences
29:27 Predictive Signals for User Needs
30:42 Balancing Personalisation and Privacy
35:12 Challenges in Real-Time Personalisation
38:16 Generative AI and Future Possibilities
40:05 The Future of Jobs in Data and Analytics
43:57 Conclusion and Final Thoughts

Thank you for listening!

allison olson:

my most proud moments are different employees that I have had that have gotten promoted or have moved on to other jobs and and are extremely successful. That is my, that's what fills me at the end of the day. And so if you ask me now about leadership, that's why I enjoy it. What I have found is your gut knows best, right? Your gut knows best, what's right for you. And then for me, anytime I have taken that nervous jump, it has been worth it. Lead volunteers, go and, get involved in some nonprofit and then, raise your hand to be the chairman of some committee and lead a team of people that could stand up and walk out at any moment. I have a big problem with using this data to manipulate people. I could go to one particular sporting website and I could just use their AI driven software and type in with agen ai. I have a 10-year-old, like a 10-year-old that is, wants to start lacrosse, what do I need to buy? And it could find it for me and put it in the cart already, and then I just have to look in the cart and see if it makes sense.

ben parker:

Welcome to Data Analytics Chat. The podcast where we discuss the world of data, ai, and the careers shaping it. My guest today is Alison Olson, who is the Senior Vice President of Analytics Solutions at Merkel Densu In today's In today's episode, we will explore her career journey, the challenges, the insights she's learned during her career, and the data topic will look at the impact of personalization in ai. Alison, welcome to the podcast.

allison olson:

Thanks for having me, Ben.

ben parker:

I am looking forward to this discussion. So let's let's dive straight in. Do you wanna just begin by sharing your career journey?

allison olson:

Sure. I have, let's see here. I'll start with kind of high level. I have over 25 years of experience and two degrees specifically within statistics. In marketing. And honestly I did not know that was gonna be my interest until I started college and I was getting closer to the point where you have to declare a major and I took a stats class and I fell in love. So the rest is history and then obviously. Statistics and what it was, called earlier on in my career. Predictive modeling has really changed over time in a sense of now it's more in the forefront with ai and machine learning and all of that. But it's, it is just been it's been exciting. So yeah, I'm not sure where you want me to focus on specifically in my

ben parker:

Yeah. And how did you, how did you fall into, obviously now you are in the SVP, how did you progress?

allison olson:

Ooh, that's a good question. Progression is never perfectly linear, right? There were different points in my career where I felt. Stuck and that I maybe wasn't moving, moving forward or utilizing my strengths as best as possible. But I would say when I look back now, every single place that I worked at and every single different, like industry and vertical that I helped to measure whether I worked in IT directly or whether they were my clients. It has all helped to shape who I am today and the knowledge that I can bring to the table to help solve solve different business related problems today. And so I would say, if I would always ask myself at a company, am I getting everything I need from this company and am I giving everything I can give? And when you get to the point where there's nothing left for you to learn and you feel like you've given everything that you've given, that's when I would consider moving on. But it's been. It's been a fun journey just getting to learn new things and, when you switch companies and meet new people and you get to learn new processes and then as technology changes you can see different companies and how quickly some will adapt and how slowly others will. So that's, I would say that's some of the interesting pieces with the career progression.

ben parker:

Okay. Brilliant. And then did, so you mentioned you fell into the love for statistics. Did you, early in your days, did you feel that you were gonna become a leader? Or how did that sort of turn around?

allison olson:

That's a good question. I, nobody I don't know. I think that you, people might think they're leaders, but it takes. Being one to really realize what's involved is what I would say. So I, so if you had asked me let's say right out of college, I would've said, yes, I wanna be a leader. I want to, lead large teams, I wanna climb the ladder, all of that stuff. But that's more ambition talking. So if you talk to me now about leading teams, my main focus with leading teams is around. Like the kind of the story that I say, the is that I like to be on the side of the stage. I like to be on the side of the stage and I like to. Be the one that's directing the lighting to say, Hey, put the spotlight on that individual on the stage. I like to be opening up the curtain. So it's like removing any roadblocks for the team, making sure that they are fully empowered to do the amazing work that they can do. Helping to mentor them. Everybody needs to learn and grow, right? Like I think that's the biggest thing too with leadership is not that. You know exactly what's right. It's more and more willingness to accept feedback and change based on feedback. And so I think that's a big thing with leading teams is like helping to give feedback in a constructive manner that. Doesn't feel harmful or hurtful, and then work with them to grow and uplevel the parts that need to, need to just be tweaked a little bit and then help them shine. Help, like my most proud moments are different employees that I have had that have gotten promoted or have moved on to other jobs and and are extremely successful. That is my, that's what fills me at the end of the day. And so if you ask me now about leadership, that's why I enjoy it.

ben parker:

Okay. Brilliant. And would you say there's sort of a defining moment that's changed your career?

allison olson:

Ooh. There a couple defining moments. I would say the more recent one was COVID, I think it changed a lot of people. But during COVID, I would say. I softened a lot more. I don't know if that's like a thing to say, but I softened a lot more, I care way more about people's mental health than I ever did, so I do more like mental health checks. With employees, how are you doing? How are you holding up from this week? I know it was a busy, stressful week. What can we take off your plate? How can we further train your team to take that load off of you? Is there anyone on your team you're worried about? Have you taken enough days off? That's a big, that's a big problem in America, right? So we have global teams, but in America we have a lot of i, it's like a pride in not using all of our PTO for some reason. And so I definitely work with the teams to. To help break that cycle, to actually use the benefits that the company gives and to take the PTO when needed because we are all our best selves when we get the rest and relaxation that, that we need. And so I would say COVID was a big one. Some other ones. I think whenever whenever things happen and you feel like. You know what, how do I say this? Like failures and failure. That sound, that sounds so negative. I learned the most from failures. And so anytime there is something where I feel like, Ooh, that did not go as well as I wanted, I take a moment to process it and all the feelings around it, right? Disappointment and all of the things. And then once I've processed it, I'm like, okay, now I need to learn from it. Now I need to grow from it. And so I would say various different failures that has helped. And then the other big turning point I would say is risk. There will be points in your career where either an amazing opportunity comes up. Or you have this great idea like, like you did for a podcast and there's this risk, this big leap, and then the decision when you're, at the top of, think about like a, a cliff thing where people jump off and they jump into the water and everybody's having a lot of fun. You're on the top of that cliff. Many other people, you've seen them jump off and they're, they've, they're swimming and they're doing just fine. But that moment where you have to tell yourself, am I gonna do this or am I not? There's risk involved. I'm a little scared. Everyone that's done it looks like they're having fun. Should I do it or not? What I have found is your gut knows best, right? Your gut knows best, what's right for you. And then for me, anytime I have taken that nervous jump, it has been worth it.

ben parker:

Yeah, no agree. I think as you make some valid points definitely like COVID, it's, it impacted a lot of people in ways obviously. I think a lot more people wanna become more purposeful. Obviously, like you, like yourself, you are more, obviously more pe people oriented. I think I, that's definitely more commonplace now, isn't it? See, we're in. I think this, it was a wake up call for a lot of people, I think. So yeah. And some good points you made. So in terms of obviously your progression then you've must have come across some sort of challenges along the way. Has there been any sort of standout challenges that you feel have shaped you or taught you real leadership?

allison olson:

I would say anytime you have a situation, like when I look back. I am the manager that I am because of all of my former managers. And some, because they did a great job. Some because may maybe not. I know they're gonna listen to this and be like, is it me? It's not you if you took the time to listen. But. When you see things that you don't want to emulate, sometimes that has even a bigger impact, right? So we'll go with an easy one, micromanaging. No. I have yet to meet a human that says yes. I love it when someone's just over my shoulder watching what I do and nope. Do that different. So whenever you come across like a manager, that I feel like that helps even more for you to be like, I need to step back, give empowerment to my people, let them do what they're gonna do, and let them also experience failure, but mitigated failure, right? Trying to guide them through different components, helping them out. But honestly, most people. They're hired because they know how to do their job or they have excellent potential. And so these are the reasons where it's like, why can't we just trust that people are adults and nobody has time either to micromanage. So I would say learning from all of that and all of, my past managers, and that goes back to even, I started working. I started working when I was young. I was babysitting when I was really young, and then I worked at like a pizza place and some other restaurants. It's 15 up through college and different internships and so this includes all of those. I think that when you watch how people treat other people, it's, it really helps to shape your leadership. And then the biggest thing, if you're not sure how to lead. Lead volunteers, go and, get involved in some nonprofit and then, raise your hand to be the chairman of some committee and lead a team of people that could stand up and walk out at any moment. And that's gonna change your leadership style pretty quickly.

ben parker:

Yeah, you made some good points there. And I think just going back to your previous point, I think we're gonna time with the next question is like you mentioned about just go for it. Really being fearless and don't worry about risks. I think that's, you should just push, go for it. Really. Like in terms of just. I think people worry too much about what's gonna happen when really look, just go for it, push yourself, and you never know what will happen. So then obviously that sounds like one of your sort of skills, like you quite fearless. So is there any other like skills or mindsets that have helped you progress into leadership?

allison olson:

Oh, that's a good point. So I will go back just real quick as a natural like statistician, data analytics person. I am riddled with fear. So I'm, so that is, that's great that you said I was fearless, but it is, I'm on top of that cliff for a long time making those decisions. But the thing that I would say there is more like trust your gut. If your gut says, this is wrong, this isn't my passion. I don't know if I wanna do this opportunity, then don't. But if your gut says, man. I really want to do X, Y, and Z and I'll just, quit my daytime job. Start a podcast or what, whatever it is. But you get that strong feeling in your gut. Then I say, go ahead and take that leap. I had an opportunity where for. A group of us were approached by an investor and it was like the opposite of Shark Tank, where they said, Hey, we've got this amount of money, we want this amount of stake. Do you guys want to leave your company and start a company? And that was a big decision for me and I took the leap and I loved every minute of it. And they were wonderful to work with. We were able to build the company up, get a whole bunch of clients. It was a great opportunity. So that's, that's what I'm, thinking around that piece. Oh my God.

ben parker:

No,

allison olson:

still there?

ben parker:

many people like, I mean it's with so many people, they even wanna like move into leadership, but they feel like they don't dunno enough. They've got the fear. It's fear and everything. Even when you're younger, like even a bar gonna chat to a girl, boy, whatever. He's just you have the fear, don't you? It's that what if, but I think you just gotta go through it like so up to a girl. Like just what if it's so much that goes on in obviously even your life and I seen work. So is there any other

allison olson:

and I apologize. I apologize. Did I cut out at all? So my, my whole computer went to a a blue screen, but then it just came back on.

ben parker:

No, that's fine. It all, it was fine.

allison olson:

Okay. Okay. We, okay. Good.

ben parker:

So was there any other, skills or mindsets that have helped you progress?

allison olson:

Skills and mindset. Okay. The skills st I would say stay stay up to date on whatever skills are happening right now in, in the industry and, and we all know it's ai and then of course, machine learning on the background to to handle that as well as making sure the data's set up right. AI cannot work with real time transfers without the data set up in such a way where it can quickly, seamlessly feed in through all of the AI to do what is needed. So I would say that piece, and then the mindset is curiosity, be curious, have fun with every question that comes up. And yeah.

ben parker:

Okay, good. And then what advice would you give someone that's looking to become a leader?

allison olson:

I would say, that's a good question. So someone early on in their career

ben parker:

Yeah, yeah.

allison olson:

or Okay. Or like mid-level that's trying to make a big jump. So I would say one of the biggest things two, actually, two, two big things. One is everyone always thinks about managing up when you're trying to get promoted and to move into leadership. But remember, you need to balance managing up and managing down. And what that means is. You need to make sure that your team has everything that they need to be successful. That is what your leader is looking at. Just focusing on, Hey, leader, what do you need? And I'm gonna address all of your needs, but not addressing the needs of your team that the leader is looking at that as part of that decision on promotion. So I would say keep an eye for both of those. That's the first thing. And then the second one, I don't know, maybe it goes with the curiosity, but there, what I find is there's like a step function in leadership. And it tends to be at the director level for some reason, but some places it's a little different since titles are different everywhere. But there is a point where being a really good practitioner only gets you so far. Then the expectation from the people above you and around you is that you're gonna start doing more leadership like things. What does lead, what are leadership like things? Honestly, more boring stuff like more menial stuff. So to someone who's a practitioner and is coding like crazy and doing all of these amazing technical things, they will view what everyone else views as leadership. Rudimentary. And so I usually spend a lot of time mentoring people at that phase where they're like I wanna take this in this course and I wanna keep learning all these new codes. And I'm like, that is wonderful. But I, myself, my, my pie chart of time, I actually spend zero time now coding. Because of my level. I spent a lot of times looking at the financials. How are we forecasting? What are we selling in compared to those forecasts? I'm spending time looking at, are we being innovative? What's happening in the marketplace? I'm looking at what are clients' needs? Are we meeting those needs? Like those are the things. So it's like organizational kind of things, like taking the time to slow down and be organized about things. That, that a leader does. And I find that there's a struggle usually at that step function for people in data and analytics to make that jump. And I use it as like a. I don't know, like an area chart where one one side of it goes up and up and up while the other gets smaller and smaller. And so the practitioner part should get smaller and smaller as you move up in your career and the like administrative stuff goes up as you move up and sometimes that is difficult for folks.

ben parker:

Yeah, and I think it is being self aware of. Your, what's your key, what's your key skills as well? What abilities do you have? Because I mean it lead this, you can be like a senior leader where you completely move away from the, like the hands-on. But I mean you can be like tech leader where you still hands up, data roles again, so diverse now, so there's so much opportunity. You don't have to be like a full manager. You can be more of a tech lead, don't you?

allison olson:

But even in that case, so even let's say like a CTO who I talk to our CTO all the time, he's amazing. He is still spending, even though he is building out tools, he's he is very hands-on technical. He is still spending a good amount of time working with other teams, checking to make sure we have the right amount of licenses per our different departments. Like these are administrative things and you just always do more of'em. The more you move up in leadership. So it may not get to the point where the practitioner piece is zero, but that admin piece will always be more as you move up in leadership.

ben parker:

Brilliant. Okay, so let's move on to the data topic and so we can look at the impact of personalization in ai. So I guess from your perspective, what does dynamic personalization mean?

allison olson:

Ah, so this is what I have been talking about lately to all of our clients. I would say, I don't know, in the last several decades there have been like these slides that companies have shown clients where it's like the fuzzy consumer and then the consumer comes in view and then you know that consumer. What I'm here to say is that. Is not reality. So that, that static view of the individual. So yes, maybe that person was unknown before and yes, now we know them and it's, I'll just use, I'll just use woman in the suburbs, late forties, right? Yes. You know that about the person you might even know interests. Sorry. Interests and hobbies and all of those kind of things about that individual, but what I want to add in here is that we are dynamic humans. We are not static. So that description I just gave. Does not tell you how I'm thinking and feeling throughout the day. And we all know within our own selves that we change as different things change throughout the day. And so when I say the dynamic consumer, this is very cutting edge. This is very, right now we actually finally have the technology through AI to fully cater. To our consumers ever-changing dynamic needs. It starts to rain. We have weather data. We get that information, they get a different message. Or when they come to the website, they get a totally different experience. There is a national crisis that happens. We can immediately. Send out softened softened messages. We're, we are here for you or, snuggle up with your family and enjoy time at home or whatever. You know what, whatever the message is, we can immediately be changing those based on the data we receive on what is happening in the world today. So that's what I mean by dynamic personalization.

ben parker:

Okay. And so how would the, how is it different from static personalization that we've seen in the past decade?

allison olson:

Yeah, so the static is just the basic stuff. Like I said, like all you're knowing about me is that I live in the suburbs. I'm a female in my late forties. I like golf and I like to read like that. Doesn't mean that different things have been happening in our world and that, I'm a different person and need different interactions throughout, throughout the day and throughout the week. So that's the difference. Like that's, it's just. It's the new version of the blurry customer, right? So it's like we thought, oh yeah, we know the customer and we do, we know the customer. But the thing is, we as human beings, as consumers, we are changing every moment of every day based on our surroundings and what is happening to us. And we should be able to quickly adapt to that through ai. So hopefully that helps. There's also, aI helping us through something. So if something is typed into ai, so like planning a trip to Bali, it's like knowing that information and then being able to not only serve up everything that's appropriate for a trip to Bali and planning, it's also like filling a cart. To show'em, hey this would, these would be the appropriate things to purchase for that trip. So it's just like all these individual moments being ready and dynamic and immediately shifting to meet the needs of the consumer. And we expect it these days. We expect it when people so let's go with, when, when a woman is pregnant, right? She's expecting immediately, like her interests have changed and she wants to know all about the baby. She wants to be prepared, she want so it's like immediately recognizing that and serving up different content that either meets that needs or accommodates that need. That's the type of stuff. That, that we're expecting as consumers. Have you ever gotten an ad where you look at it and you're like, what is this I'll give you an example, A coworker he brings it to me all the time. There's a large department store in the United States that he has signed up for their CRM program and they send him. Everything from women's dresses all the way to kids' clothes, and his kids are older. He's what are they doing? Like they, they should clearly have information on me and should know more about me to give me more appropriate things. And so when I talk about like dynamic, it's more around. Send, so first it would be, the static would just be, okay, let's just send him men's clothing. What he is interested in and what he tends to buy. So sending him men's clothing. And then if he was also buying for like these adult children, it would be like maybe that specific stuff that like gifting for them, right? That's the static version. And then the dynamic would be, if we knew something else that was happening. So again, let's use like the weather, it's raining, it would be like, here's a discount on umbrellas and really great rain gear, because people's mindset is on that. It may not be for that particular day, but your mindset might be like, you know what, I'm gonna be more prepared. For the next time that it rains. So that's the difference. And the progression

ben parker:

Yeah, so it's just, yeah, so it's just more like a deeper. Few, isn't it? Like I, I think that's the common theme I'm seeing with AI now. It's just whatever the business concept, it's just, it's going in deeper, isn't it? Like it's to know more about you and it's gonna be able to give you better results.

allison olson:

better results. Exactly.

ben parker:

So what types of data are most valuable for enabling adaptive experiences?

allison olson:

That, that's an excellent question. Obviously I've talked a lot about weather. Weather is a key one. Also, any indication of major national events, meaning, I could let's say like a very tragic event. Also knowing about large storms, whether they're in the area or not. If they could do major damage somewhere else, that could really change people's mindset. If they're like watching the news and it looks like like Florida's gonna get hit by some terrible storm, everyone's really concerned for their family and loved ones that live in Florida, there might be a different message that needs to go out, or a softening of an existing message that needs to go out. So there, there's a lot of data that comes into play, obviously, when people. Offer up their own data into ai. That's very helpful. If it's, if it's within the same platform, right? So if they're saying, Hey, I'm planning this trip to Bali, and then it's like, Hey, we could be helpful and give them all this different information. There, there's also if you went on for an adaptive experience, if you went on to a website, so going back to that example of, the pregnant woman who was planning the nursery and planning for a baby to join the family, then she could. Go to a retailer's website and tell them, Hey, I want this kind of color for the wall. I want, this this is the theme I kind of wanna do. And they can suggest through AI all of these different things for her to maybe put on her registry and she can put it, she can place it in the room. There's just amazing things that can be done now with AI that actually like really help the consumer out. It helps the company out because then it's increasing specific sales. And again, it's more hyper targeted, so then it's what the consumer actually wants.

ben parker:

So is there signals that you find are most predictive of changing user needs?

allison olson:

Yeah. Depends on the vertical. It, yeah it depends on the vertical. Like I said I'm using weather'cause that's such a general one that affects a lot of'em. But yeah, it just, it depends. In healthcare there are several different ones. Let's go with easy ones in banking. When folks are about to get married, they tend to have conversations about joining accounts, right? And Hey, are we going to go to a new bank and start fresh? And then we'll both, join accounts in this new bank. And so knowing that people are about to get married, which is a tougher, piece of data than just, marriage certificate exists. That, that's a very predictive one. And moving, having really timely moving data, that's also one that's a great one for furniture stores, paint stores. Also even for banking, people always want ATMs that are close to their house. It's also good for gyms. When people move, they're immediately looking to get resettled into their new area. So making sure that all of that kind of data is very timely is critical.

ben parker:

Okay, and so how would you. Deeper personalization and consumer comfort around privacy and transparency.

allison olson:

It's an excellent question. So this is not so where where I have an ethical issue is when it comes to just think like Cambridge Analytica, right? That's where I have big, strong issues against what they even did to even get to the point where they received all of the repercussions that they did. I have a big problem with using this data to manipulate people. What I view using this data for is actually being way more efficient from a company standpoint. So then you're only going for the exact right individuals and you're figuring out the right way to talk to them at the right time and the right number of. The frequency of how often you need to talk to them. And that helps the consumer because if you were the consumer, like my colleague who kept getting emails about women's dresses and women's shoes that's a bad experience for him too. Also, I'm sure you've gotten somehow like on lists. I have gotten on some lists where I am my mom's power of attorneys, so they think she lives at our house. So I get a lot of things trying to sell in to seniors, and it's just one of those things where th that's a waste for them. It's a bad experience for me'cause she does not live with us and so it. It's not good for the consumers. It's also expensive, unnecessarily for the company. And so to me it just feels like a much more tailored experience that is needed. So the piece that I'll throw out there is we also as consumers are expecting this. And as one company moves to do it better and better, and there are many companies that are doing that, but I'm saying like whichever one is on top for personalization, they set the bar for consumers across the board. And so every company, even like the small like plumbing shop down the street is held to this new standard. And I'll give you an example of what I mean. I ordered shoes. I don't know few months back now directly from the shoe company instead of through Amazon. And it's been a while since I've ordered something outside of Amazon. And as Amazon, you can order it and then you blink and it's at your front door, right? It's so fast. I think their longest one is two days or three days. And you would've thought it took a year or two to get these shoes. It was probably like five to seven business days or five to 10 business days. By the time I got the shoes, I just was like, what in the world? That took so long because our bar as consumers is this really fast, tight shipping from the time we order to the time that it shows up. So that's the component too, where it's like we are expecting this, a single man that lives on his own in his twenties. Will be a little annoyed and perturbed if he gets like coupons for diapers at Target sent to him with his name on it, right? Like we have this expectation as consumers that brands know us and so that, that. Those two coupled together with delivering them the right message at the right time. That is where all of this comes from, and it is ethically and morally the responsibility of companies to make sure that's used in. In the way in which I'm speaking about it, right? We do. We do marketing, we do advertising. That is what we're doing. We are not trying to get, so from my perspective, we are not trying to get anyone that would not already be interested in, unless she's like women's dresses, to try to sell them women's dresses because number one it doesn't make any sense. It's inefficient. And then it's not a good experience for them. So it's just all about trying to find the people that would buy these products and then giving them the message that would resonate the most with them.

ben parker:

I agree. If you kept getting women's dresses, you'd get a bit annoyed. What are the big challenges of delivering adaptive personalization in real time then?

allison olson:

Oh yes. So I will start with it from the ground up. The biggest issue is most companies do not have their data set up in a manner. Which data can be transferred back and forth in real time. Meaning they have a whole bunch of tables this system's over here, this other system's over there, like Yeah, we can query'em. Yeah, but if you run a query and that query takes, even five minutes, right? That. Is not what we need to process ai. Like it needs to all be in the same environment. It needs to be very quickly and seamlessly transferred between so that AI can start to run models and learn from the data that is there and be able to quickly pull everything that it needs. So I would say that is the biggest thing, slapping AI on top of a data infrastructure that is not ready for it. Very often results in failure. In addition, I would say a lot of companies seem to be, there's like a top down push. We need AI without any guidance, so it's we need ai, and then everybody's okay, I'll just go onto chat GPT and start using it every day. You need actually governance of ai, right? You cannot be just putting your company's stuff out there on chat. GPT. You need like an enterprise level. A system, you need governance around what people can and can't put in there. You cannot have client data ever going into a public AI type of a system where it immediately is learning from that. That's why you always wanna get an enterprise related licenses so that it stays internal. I would say another big thing for AI that I find, and this is a big Merkel plug here, is that. A lot of our competitors have built like black box AI tools and they'll talk about how great they're, and I'm sure they I'm sure they're wonderful. The issue is if you're a company and you are signing up for these AI tools and do not own them, you did not pay this company to build them in your platform and in your system, as soon as you go to try to RFP that work, you lose. That entire AI platform. So I think the biggest thing, if you're looking into who's gonna provide the ai, and this is our big the, like the Merkel DSU way is that we build custom for the clients in their platforms so that they can own it. And that's a big piece for us. And it's a big differentiator because in the end of the day, we want the clients to be as successful as possible.

ben parker:

No, it's obviously big difference. So then obviously the last three years we've had the boom. How, how is generative AI changing the possibilities for tone experiences on an individual level?

allison olson:

Oh my goodness. Everything. It's going to, it's going to change how we shop. So instead of going on and you're like, you do a search, right? And you're like, okay, so let's use an example. Let's say my 10-year-old is Hey, I want to get into lacrosse and I don't know much about lacrosse. And so instead of me having to go and Google what do 10 year olds need for lacrosse and going to all these different places? I could go to one particular sporting website and I could just use their AI driven software and type in with agen ai. I have a 10-year-old, like a 10-year-old that is, wants to start lacrosse, what do I need to buy? And it could find it for me and put it in the cart already, and then I just have to look in the cart and see if it makes sense. But it would all be fit to the size of a 10-year-old. And so I wouldn't have to go through all of these different gloves and whatever, I don't know, lacrosse, so I'm gonna butcher whatever I say about it. But, the mallets or whatever they hold in their hand, like all of that, it would've already done all that research for me and it would make shopping so much easier. And I. Very likely might buy more because I would know that I needed to maybe they need special shoes or special shorts or special, something that I was unaware of. And so that, that's just an example, one of the many examples of what all like it can do.

ben parker:

Brilliant. Yeah, no, I think it's gonna be fascinating. Times ahead. You just, yeah. Your example is good. Just, it's just making it a lot easier for us, isn't it? We're getting, it's a free ride. It's making us lazy, easier,

allison olson:

as consumers. As consumers, for sure. The one thing I did wanna say, Ben, is like thinking about our field and the future of our field. So I get the question a lot. Will AI eliminate all of our jobs in data and analytics? I do not think so. If they're using AI correctly, no. Because, and this is my own personal opinion with this. And just to be clear, we build out self-service analytics tools as well, but this is more for think about, just like the queue of tickets that we get of just I wanna see, sweater purchases. By the different colors of sweater quarter over quarter for the last three years. Like really specific ad hoc requests that take someone time out of their day to go and pull that they could pull that very quickly through this tool. And so this executive can have the bar chart or whatever they want and they can put that they can put that in their deck and go about their day. All of that does to me is free up. The analyst and data scientist to be in the background building out more cool stuff, right? You are always going to need people to make sure that the data is set up in such a way where AI can use it and that it's coming in, that it's clean, that we are following all the data governance that's in place. So I feel like that's critical for that where. I would give advice to folks is do not like the more we in our jobs act like machines, the more a machine could come and replace us. So where I would give suggestion is be a strategic thinker. Do not just get results. Just even right now even before, being fully AI led. When you pull a query and you get numbers, validate'em. Think about'em. What's the business impact? Have an opinion on'em. And I say this for every level. In fact, it tends to be my guidance most for the people that are just a few years out of college because they feel like who would want my opinion? I'm here to tell you I would, and everyone else you're handing that to. In fact, some people are ex. Affecting it. So they may ask for that sweater example that I was saying. You do the work to pull the query to get them that sweater information when you send it over. What you should be saying is, I am noticing the largest spike in orange sweaters being in the fall, September and October. Maybe we should consider changing around our advertising to focus on orange sweaters. That timeframe, that is what they're actually wanting from us, right? So just handing them, here's what I pulled. And we can see it right away, but without that sentence like that sentence is literally gonna set you apart in your career.

ben parker:

I think it's obviously from when I hate shopping and like Christmas, it gonna isn't.

allison olson:

I, I believe so. Yes, I believe so. And I also think it's gonna help. With like clutter, you know how you just go in your email and there's just clutter. There's so many people, so many companies emailing you, et cetera. Like all of that is gonna really get cut down with ai if companies are doing it right so that you're only getting messages about things that you. Would consider buying, have bought in the past anything like that. So you're not just getting something that, that is completely random.

ben parker:

Brilliant. Cool. Alright, we'll it there Allison, it's been a pleasure discussing this with you. You've shared some great insights and thanks for joining.

allison olson:

Thank you, Ben. Thanks for having me.