Using Artificial Intelligence for Marketing

Welcome to digging deeper make creativity, your business advantage. Im, your host jason falls its been a while since weve been with you an odd combination of pto and covet issues, and my family have kept me away for a bit but that’s all behind us and were back here for another episode with you today and what An episode we have for you, folks, if you still scratch your head at the talk about ai, artificial intelligence or ml machine learning, uh, you wont have to any longer uh raj

Vinca tayson is here with us today. He is the co-author of the ai marketing canvas a five stage. Road map to implementing artificial intelligence in marketing raj is also the ronald drazinski professor of business administration in the darden graduate school of business administration at the university of virginia, where they like to name things hes also uh, the co-author of the book marketing analytics the bottom Line here

Is if you choose, if you could choose one guy, to learn a i from in the world today, raj is that guy and hes here with us today on digging deeper before we get into that, though folks uh, i want to talk about podcasts real quickly. Some of you are joining us on the live stream this morning. Thank you for doing so. Uh jump in the comments section say hello. Well have an opportunity for you to ask questions and whatnot. If you do that,

Throughout the show, but many of you are listening to the recording of the show on the digging deeper podcast on demand wherever you listen to podcasts, if you do, you are one of a hundred million americans each month that listens to podcasts for your business or, if Youre at an agency for your clients, business, ignoring podcasts as a method to reach an audience is not smart.

but podcasts can be difficult to find from that media buying perspective or that pr outreach perspective theyre hard to track its nearly impossible to find reliable audience size and demographic information so you know which podcasts are the right ones to sponsor and pitch well not anymore podcaster pro is the professional version of podchaser which helps anyone find manage rate and follow podcasts i like to think of it as an imdb for podcasts you dont have to clutter your.

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podcasts to pitch some of our clients at cornet for uh or looking at them in terms of who do we want to reach out and try to buy uh advertising on those podcasts so that were you know accomplishing the goals that we want to accomplish for our clients if your brand or agency would like to find out more just go to podchaserpro com falls there’s a button ive got to push podchaserpro com sign up there you can make your podcast outreach and media planning more effective the address is podchaserpro com falls gang if you are dialing into the.

broadcast today on the interwebs out there you can also jump in the comments section or hit at reply on twitter to ask questions and interact with us here on the show jump in the comments say hello and ask your question ill do my very best to surface it and answer as we go along i see the plumbing is working out there izzy house says yay good morning shes got a new book coming out october 1st and is taking some time from her day to jump in and listen to us.

today jump in and say hello to us on the comments today as we get going here okay folks were about to get more intelligent about artificial intelligence our guest today is anything but artificially intelligent hes i guess the word would be really intelligent hes widely known as one of the experts out there in the marketing analytics space his new book is the ai marketing canvas a five-stage road map to implementing artificial intelligence.

in marketing raj vika tazen good morning and welcome to the show how are you sir good morning jason im doing well nice to be here its a pleasure meeting you and thank you for having me i look forward to our conversation well were going to have a good one because this book is fantastic the ai marketing canvas im about to drop it but uh here it is its its all pretty and nice and.

purpley and i love the cover by the way its a very good cover design stands out on the shelf so raj when you throw the label of ai around these days in the marketing world i think you get two extreme responses you either get an immediate yes the marketing decision maker or ceo has either heard of it or understands and understands enough about it to know it can help you market in a more data-driven smart way and just wants to have it so they say yes then you have the other extreme which is oh my god.

this is too complicated i cant do this and then there’s a little bit of in between as well why do you think it is that some marketers are afraid of ai and there are instances out there where they are already using it and are there instances out there where theyre already using it but just dont know it that we can point to in order to maybe relax their.

concerns a bit uh great question uh so lets start with the first one in terms of why is there a difference in use of ai i think if you look at the data out there there is there are many surveys that are done many studies that have been done on marketing managers and responses have been collected and when we looked at it when when we wrote this book i think what we really found was that there was a lack of strategy on how to use ai like how does ai really help.

our marketing strategy there is marketing there is customer engagement how does ai help that and so that’s where we began is that was the number one concern i think you can train people you can hire new people who know this ai and coding but the number one concern and the challenge marketing leaders have is how do we use ai to improve our customer engagement and that’s exactly what we try to address in this book is how ai can.

actually help you be better marketers and where do you begin and what are the steps in there so lets lets lets start there then lets start with some basics i want to make sure first of all that no one out there is confused namely me artificial intelligence machine learning what are the differences in those two and what does each refer to so that we can at least think intelligently about.

them great yes and this is one thing we definitely wanted to address as well and this was all actually uh something that i wanted to know myself before writing this book is that there’s this wide terminology and jargon out there and they sometimes seem very uh overlapping and confusing so what is ai what is ml and so i think the way we think about it is ml is the bigger bucket there are many things you can do in machine learning and ai is one aspect of machine learning.

and the way we look at ai is basically that is self learning unsupervised learning that it can learn by itself right and so what happens with machine learning is that its using data to predict events so you can think of marketing as predicting consumer reactions if you just consider marketing to be that like you could predict using qualitative intuition or you can predict using data so you can use machine learning for all of that right if a consumer is going to like a particular.

ad you can have very different ways of knowing how theyre going to like the ad one aspect of that is ai and the the main difference why ai actually took off is because it used to be about rules and expert systems the old age of ai used to be expert systems where if it was like you know um pen it would say a pen is like you know itll try to explain the features of the pen but then.

you can always have different colored pens and different like feel like there’s always a new kind of pen out there that doesnt fit the mold and so it was getting really difficult and it was very difficult to do it at scale so when google images started that was one of the like watson definitely was ahead of google images but to me google images is the first consumer grade ai and what they did was really change the.

way ai is approached from rules to data-driven exploration where they would give a lot of pre-coded images to the machine and the machine learns whether its a cab whether its a pen or a pencil or a scissor right and then when you show new images it becomes a more probabilistic prediction exercise as to whether something is more like a pen or more like a scissor or a pencil interesting so that’s why ai and machine.

learning actually overlap very nice so i know there’s also a term that you use in the book and that is used in this category that’s kind of i think a subset of ai or at least a term we should also know which is a neural network what is a neural network and give us an example of that so neural network lets take the same example of images and this time let me make it a little more attractive case of whether.

something is a dog or a muffin right so a neural like you can think of uh the same what happens in a neural network is it tries to uh break down like the prediction exercise just like a human learns uh the faces like a baby has to unlearn so many different faces when it was born and one of the most sophisticated neural networks is in a babys head when like and the way it learns is parents are telling mommy.

daddy uh grandma grandpa and its theyre giving the baby precoded images that the baby is trying to learn and decipher okay if someone else walks in if my dads brother walks in there are still some features that are different so baby is trying to learn from trial and error and by giving it a lot of information and our and the neural network actually uh tries to replicate our neural uh networks in the brain right its like just like how drain.

networks are structured except that it is in a machine and we are trying to help the machine learn by giving it a lot of images of dogs and muffins and saying this is dog this is nothing now you figure out how to do that right and the way it happens is in neural networks you have just a neural net or you have a deep learning network right so the way.

to think about it is uh just a neural network is like a cheese sandwich okay its just like two buns and a cheeseburger in between right the deep learning is like a triple decker uh beef uh burger with like bacon and like lettuce on top so you have layering there is a lot of layers in between for extra goodness and for extra depth in learning so you can.

get more nuance in how you learn about the differences and so that’s kind of how neural net works okay so getting deeper into this now i think the audience here probably doesnt need to be convinced that ai is worth investing in but heres what im guessing people might think about it number one it requires complex computer coding to set up number two it requires complex computer coding to use.

number three it complies requires complex computer coding to understand and number four we dont have the resources to use it are any of those true and why or why not they are true and not true here is the reason why they are true because yes there is requires a lot of complex codes to develop a neural network to use a neural network the no particles are the silver lining is that a lot of these.

cloud service providers google facebook or amazon have these general purpose neural networks built in already so if you want an image recognition feature for your app that you’re building there are plug-and-plays that you can use that are standard image recognition apps that you can use where the coding is taken care of you’re sending the data to this app and letting the app like there’s an api connection for example its becoming.

like that but to make it good yes you need a few data scientists to you know train and make the uh image recognizer customizable and good for your purpose so that’s kind of where you need to do some training its not just about okay im gonna put this uh off-the-shelf um tool that is available into my system that will work like an off-the-shelf too right but to make it really uh when once you see some benefits then you would need to invest in terms of people and resources to.

start customizing it for your own purposes very nice all right before we get to the the stages of the canvas here let me let me sell the promise to motivate people to pay attention to the marketers are going to use artificial intelligence for a few primary purposes and functions what are the most common examples of ai in marketing to just get people thinking whats in it yeah great question great question really uh so uh the first things and it.

also relates to the earlier question you asked about where are people already using ai that they really dont know about right so the first thing is if you’re using advertising online and if you’re using programmatic advertising it is all ai it is all machine driven except that your agency is using it and delivering the results for you so or even a lot of website optimizers are using ai to optimize websites based on consumer reactions so certainly that is one place where ai.

is used a lot another place where ai gets used is when you’re looking at recommendation systems like netflix or amazon or if somebody if you have a content website somebodys reading the web news and you can say here are some other articles you might be interested in the third then the third one would be where you’re looking at if you have an app and you want to include some image recognition or video recognition or text recognition in your app that would be ai as well then the fourth is in an enterprise system if you’re trying to predict.

whether a customer is going to churn you have a lot of data about customer transactions in retail or in b2b and you want to predict whether a customer wants to churn and what kind of offers would keep the customer those are all powerful things that im sure that the marketers out there want to get their hands on so those are the things they might want now lets tell them how we get there take us through the five stages of the ai marketing canvas so the five stages are you start with.

the foundation none of this is possible unless you have good data so the first step is actually collecting data and now when we say data for ai that data needs to be customer focused that is its about you know jason and whatever jasons react interactions is with this company right and then you’re looking at once you have data youll never have perfect data but you have enough data that you can start doing experiments the second stage is experimentation where we say let a.

thousand flowers bloom see where your return is and one of the guidance we give in that is that you want to look for value pockets where you think that automation or personalization is something the customer prefers and would find value from it if you see those are some of that if you find pockets like that those are right for experimentation and we even at this stage recommend you to test the roi and see where the results are and push further in that then the next step is expansion where.

you’re looking at the customer journey itself you’re looking at acquisition retention growth and advocacy and looking at transforming and personalizing some aspects of this customer journey either acquisition and retention or retention and growth at this point you’re also looking at assigning a marketing champion somebody who is going to be responsible you’re getting more investment in there and really starting to develop and connecting your marketing function and ai initiatives with other divisions like operations finance and i t for example the fourth step is transformation where you are personalizing the entire customer journey here you’re making big bets at.

the board level on whether you want to build an ai capability or acquire an ai company because this is where customization really takes root this is where you’re going above and beyond the rest of your competition and making ai your real capability the fifth and final step is something very unique which we call monetization where if you’re really good at this and if you have transformed your organization you’re already making money because your customer is engaged with you but with monetization what you’re doing is that you are getting a new source of revenue.

where you are providing this capability that you have for ai and personalization as a service for other companies and so you have a new service revenue that you can develop if you do all your first four steps right there’s an extra kicker in terms of the monetization and service revenues that are possible interesting so if im a marketer out there and i get your book which again the the ai marketing canvas uh is is out now and available on the interwebs well share links to all the the book site and amazon and whatnot here in a moment but.

if im a marketer and im going to read this book and im going to start putting all this into practice what are some roadblocks and challenges that marketers need to watch for as they dive into adopting ai for their organizations so there are challenges in moving across each of these stages really because the first stage is the foundation a lot of effort actually happens in the foundation stage more than we can even think right it is always never underestimate how much time it will take.

to get all the data in one shape especially if you’re a company that has grown through acquisitions or if you have legacy systems merging all of this to be about one customer is going to be a big shift and also the mindset at this point with the data foundation level you’re also laying the foundation of mindset shifts in terms of the people in your organization to think about marketing as more of a uh you know.

qualitative and quantitative business um and using the and wanting to use ai the second uh challenge ends up being when you go from experimentation to expansion because this is when you want to bring in other folks outside of your marketing organization to support your endeavor technology i t operations customer success teams finance all of these guys have to go and.

work with you and so you need to have like collaborating and connecting with the other departments then the next challenge is when you go into transformation is the whole thing about build versus buy are you building your own data science department or are you going to buy an ai capability and the final is of course once you do.

all this we just said monetization easier said than done because you need a platform to build for that and also new skills of like you know consulting services that needs to be developed in your organization very good well all of all of that information and more is in the book the ai marketing canvas uh by raj vikitazin and uh jim mulcinsky is here its the beautiful purple uh book and well share links to it over there uh in the comments section raj if people wanted to connect with you or learn more about the book and whatnot.

where can they find you on the interwebs i am on linkedin im on twitter i love to connect with your audience and know more about how they are approaching ai the book website is also www aincbook com would love to hear your thoughts in all of this connect with me in any of these platforms excellent very much well thank you very much raj for the lesson today i love it when we can uh make people smarter uh selfishly me but them too so thank you so much for joining us today.

on digging deeper and good luck with the book sir thank you jason for having me it was a pleasure all right that my friends is the author of the ai marketing canvas uh raj of inca tation and here i want to hold the book i was holding it in front of my face earlier but i want you to see the book again its a beautiful i love the design it just really is it stands off the shelf heres the back a little bit but yeah.

good stuff from stanford university press the ai marketing canvas i have it earmarked i have a page leaf stuck in here so that i can refer to it in a meeting later not because i havent read the whole thing i read the whole thing its fantastic and i learned a lot about ai and machine learning and neural networks and whatnot you know just in the first few chapters.

you’re going to get you know sort of a a bachelors degree if you will on ai from the professor of course so good to have him here and i hope you guys all go out and get it the last thing i wanted to touch base with you on this week again uh my apologies for the last few weeks we havent been here uh with you on the big show uh had i mentioned earlier at the top of the show uh there was the tail.

end of the summer time there had some vacation to to worry with but also unfortunately had some covet impact in my family uh had a family member pass away a few weeks ago and so weve been kind of focused on that so i know that that everybody understands those situations and that digging deeper may not necessarily be a high priority during weeks where were dealing with something like that but the experiences just wanted me to make make sure that as we sign off today to kind of reiterate to everybody you know get vaccinated if.

you havent been already and certainly if you are in situations in social settings even if you are vaccinated its probably smart to wear a mask and keep distance from people uh that you dont know very well because that’s continuing to spread the delta variant and whatnot uh it has had a an immediate and uh big impact on my family now it was more distant before ive got several family members right now who currently are positive for covet and are quarantining trying to do all the things to stay healthy so take care of each other folks.

put on those masks get vaccinated if you’re not if you are high risk get those booster vaccinations as well i am high risk because of a medication that i take for psoriasis so its a biologic so i qualified for the booster i went and got the booster so lets make sure that we uh stay safe and stay healthy because its impacting a lot more people its not going away so we have to be vigilant for that so just want to take a moment and kind of.

give you a little context as to why we havent been on the air in a couple weeks and encourage you to do what you can do to take care of yourself and take care of others and this is the point of the program where jason has to figure out how to push too many buttons at once and you know i normally screw.

that up but hopefully ive got it right today that’s going to do it for this edition of digging deeper make creativity your business advantage if you like the episode share it with a friend or colleague who might as well digging deeper is a production of the cornet group find us online at teamcornet com our executive producer is christy heiler.

creative director is jason majeski associate producer is ashley harris our theme music is composed by rex banner im your host jason falls thanks for joining us folks until next time i will see you on the interwebs.