Episode Transcript
[00:00:00] Jennie Wong: The whole hacking shopper psychology initially all started with the same
problem that we started with a minute ago, which was how do you get past overwhelm, right?
Like how do you break out of analysis paralysis? And so the e commerce startup that I founded,
oh gosh, I guess over a decade ago now, was kind of based on some of these principles about
what drives conversion.
So I think what's really interesting is that higher ed can borrow more than just that lesson from e
commerce, right? So like, understanding the paradox of choice is helpful, but there are a variety
of e commerce strategies that higher ed can use. And it's kind of interesting that this is an
underinvested area because if you think about it, you have a company like, you know, a shoe
company, right, that is using all of these conversion tactics for $50 sale or $150 sale.
And higher ed is not yet necessarily hip to those campaigns or tactics. But you know, you're
talking about $50,000 of tuition for like a single year.
[00:01:17] Jeff Dillon: Welcome to the EdTech Connect podcast, your source for exploring the cutting
edge world of educational technology. I' Jeff Dillon and I'm excited to bring you insights and
inspiration from the brightest minds and innovators shaping the future of education.
We'll dive into conversations with leading experts, educators and solution providers who are
transforming the learning landscape. Be sure to subscribe and leave a review on your favorite
podcast platform so you don't miss an episode. So sit back, relax, and let's dive in.
Dr. Jennie Wong is the Global Industry Director for Education at Slalom, where she works with
colleges and university clients around the world and leads AI and data strategy and
implementation. Backed by a PhD in Organizational Communication from USC, Jennie helps
institutions move from raw data to real world impact, guiding everything from secure research
clouds to genai pilots for IT faculty, alumni and students at Slalom. She's earned multiple Team
Mogul awards for client delivery excellence and is the author of the recent article Data Strategy
for Higher Education fuel for the AI engine. Her career spans talent management for Fortune
100 companies, a neuroscience based e commerce startup featured in TechCrunch, and a
nationally syndicated entrepreneurship column recognized among 100 women of worth and top
mompreneurs. Jennie pairs business acuity with a passion for teaching leaders. Her mantra is
leading is teaching. When she's not advising campuses on AI readiness, you might find her
mentoring rising tech talent or practicing her conversational Mandarin with occasional wine notes
thanks to her sommelier coursework.
Well, welcome to the show, Jennie. It's great to have you.
[00:03:17] Jennie Wong: Good to be here, Jeff. Thanks for having me.
[00:03:19] Jeff Dillon: So you began your career studying organizational communication and now you
guide universities on AI and data strategy. What drew you to higher ed tech and how has that
academic foundation helped?
[00:03:34] Jennie Wong: Well, it has been a little bit of a windy road from being a former academic
social science researcher studying organizational communication to my current role leading the
education industry sector for Slalom. But when I look back, I think there are certain themes that
make it make sense. And I think those themes are basically experience, behavior and strategy.
So I was drawn to the study of organizations initially because I was really interested in the
employee experience.
So I used a variety of different methodologies like survey methodology and the process of writing
my dissertation and getting my PhD. But then I realized that if I stayed in academia, I would
probably have to do a lot of my studies and data collection using the population that was most
easily available to me, which would have been undergraduates.
And I really wanted to be inside of larger organizations that have such an impact on so many
people's daily lives.
[00:04:40] Jeff Dillon: Well, speaking of larger organizations, you are part of one of the most
prestigious, like high ed tech consulting firms, Slalom and the education practice has posted a
triple digit sales growth under your direction. So what were the first moves that set that surge in
motion?
[00:04:59] Jennie Wong: Well, thanks, Jeff. Yes, initially upon stepping into this role as its first
incumbent back in 2023, we did see really wonderful sur in growth to the tune of, as you said,
triple digit growth in the first 12 months. And what I would attribute that to is a couple of things.
One, to begin with the customer in mind, I really advocated for a focus on Personas, customer
Personas, buyer Personas, to help the wider organization. Right. So Slalom is full of technology
consultants and business advisory consultants.
And we're very expert at certain things like aws, Microsoft, Google and Salesforce. But not all of
our practitioners are necessarily thinking strategically about higher ed and how do we grow that
business. So one of the engines of that initial growth was definitely trying to articulate the
different types of constituents that are within that environment. And then I would say the second
big element or driver of that growth was, was getting really tightly linked and aligned with those
partners of aws, Microsoft, Google and Salesforce. Because, you know, that is the actual
technology that we do a lot of our work on. So we're 100% services provider and we are doing a
lot of our customer service against those platforms. So wanting to get hooked up there.
[00:06:26] Jeff Dillon: Well, that makes sense. I think you have such a great partner network.
So Jennie, can you talk about the framework you've created with your approach to AI?
[00:06:35] Jennie Wong: Absolutely. So I think that it's hard to find a leader in higher ed right now who is
not being asked the question, what is our data and AI strategy?
Organizations know they need to get more value out of their data. They know that they need to
get from maybe proof of concept and different pilots that they're running right now to more
scalable value.
And so for us, the North Star that we use when it comes to data and AI strategy for higher ed is
of course, the strategic value. And we consider that like a destination.
And then we consider AI, whether it is like old AI of machine learning, or the now AI of
generative AI, or the thing that's rapidly coming next, which is agentic AI.
All of these things represent the engine. But if you think about the engine in a car, our approach
is to say to get all the way to your destination, you can't just have a car that only has an engine.
You essentially need three additional things. We use this metaphor of the car to say that to guide
your journey, you need to have a steering wheel, and that is the functional expertise of what is
the department that this AI implementation needs to serve.
So it could be a business function, like human resources, or it could be an academic function, or
it could be, you know, something that's really unique to higher education, like admissions and
enrollment. So you've got to have that understanding, that functional understanding to the
steering wheel. You also have to have a way to integrate, whether it's a large language model or
reasoning engine, you have to have a way to integrate that into your systems of execution.
So that could be your email automation platform, that could be your learning management
system. That's an integration we're working on right now for one of our customers. And then the
last thing you need is the gas for the car, and that's your data. So we say data is your fuel for the
AI engine. So that's kind of the approach that we've created, is to make sure that we're bringing
all of those things together.
So you're not just looking at a pilot, but rather you are being able to get this new generation of
technology to get you all the way to strategic value.
[00:08:55] Jeff Dillon: This is part of the reason I wanted you on this podcast is because I saw that,
that model, that diagram of the car metaphor, it made a lot of sense to me. So hopefully we can
put a link to that in the show notes, if that's published yet.
[00:09:06] Jennie Wong: Yes, absolutely. We have it available for folks to look at on one of our articles
on slalom on medium so what part?
[00:09:13] Jeff Dillon: Imagine this car with the steering wheel and the, you know, the engine. And
what part of the car are schools struggling with the most? What's missing?
[00:09:21] Jennie Wong: I would say that it starts with a sense of overwhelm. I would say the first
problem that we see very commonly is that there is an overwhelming amount of choices
because, you know, you're being told, like, let's say you're a mission area owner, like, let's say
you lead student success or academic advisement or one of these functions, right? And you're
being told that AI can do all the things and anything, right? And you might need all the data,
right?
And so the very first barrier that we see is this sense of overwhelm.
So the way that we try to help our clients with that very first problem is to provide what we call a
map of the territory to really simplify a definition of strategic value that is specific to higher
education.
We talk about if we've got a big room of stakeholders representing multiple departments, we talk
about type 1 strategic value, which is enhancing the inflow of resources into the university.
Or there's type 2 strategic value, which is where you are improving the impact of spending those
resources, right? So that could be like the efficiency of your accounts payable team, or that
could be delivering more personalized student success supports to improve your year over year
persistence rates, right? And so we try to simplify and then provide within each function a couple
of simple models so that folks can say, hey, this is where it hurts the most. Like, this is where we
have the most repetitive or inefficient processes, where we have a human being that's swiveling
between three screens.
And can data and AI solve this for us? Once you clear away that problem of the overwhelm of
choices and thinking, you have to have all the data and all has to be perfect, you can actually
unlock value very quickly.
[00:11:17] Jeff Dillon: That makes sense to me. I'm curious, which Genai use case has surprised you
the most in terms of measurable impact for students or faculty?
[00:11:26] Jennie Wong: We delivered a proof of concept last year for UCLA's business school, the
Anderson School of Management, where we used kind of the CAR model that I just described to
support their advancement team with alumni fundraising.
And kind of like what I was saying before, we weren't going after the entire alumni engagement
process.
We really kind of called our shot and we said, okay, you have a reunion campaign going on
where you are trying to engage these 3,000 alumni for whom 2024 is a reunion year.
And so as a part of Your existing sequence.
Let's do an A B test between your current email solicitation in this sequence where you know,
this advancement team, they know what they're doing, they're already using best practices,
they're already using a certain level of personalization, they're already using Salesforce
Marketing Cloud. Right. But let's see if we can double down on number one, adding the engine
of AI which they were not using prior to our involvement.
Secondly, doubling down on the steering wheel because we brought even more evidence based
fundraising best practices, like kind of out of my background of social science research and you
know, sort of behavioral design and then the integration to Salesforce Marketing Cloud where
we have a very deep and wide bench of talent. So they got more out of their existing platform
and then that gas. Right. The fuel for the engine was making sure that we were leveraging
some, some actually very readily accessible data that they weren't necessarily using in their sort
of prior efforts. Bringing that all together, we were able to actually more than double fundraising
outcomes from that single email.
[00:13:15] Jeff Dillon: Wow. For the institutions who want to unlock results like that, what kind of data
strategy do they need?
[00:13:21] Jennie Wong: Well, I want to start by making sure we give credit to like all of your listeners in
higher ed, because I'm sure they are already getting value out of their data to a greater or lesser
extent. And every institution already has some version of data strategy. So I think it's important
to say that our posture is not like, you're not currently doing data strategy, so you should start
doing data strategy. Like quite the opposite. You know, we conceive of data strategy as an
iterative process. Right. So you kind of are looping through strategy execution and enablement.
Right. And that, that moving through data strategy, data execution and data enablement is
iterative. And you're going to kind of run that cycle as the technology changes and as the
demands of your organization institutional mission shift. Right. Like in the current environment,
we certainly see a whole new set of challenges that data and AI need to solve in this present
environment.
And so I would say that within that there's like two pieces of very good news.
So one is that when you think about your data strategy, you don't need to dichotomize between
centralized or decentralized. Those are not your only options.
Because I think for a lot of higher ed, the right answer is going to be a federated model because
it matches the reality and culture of higher ed being highly federated.
So that simply means that you only centralize the things that really make sense to centralize like
maybe you're purchasing power for one of these major cloud providers and then for everything
else you can use a different organizing principle like data domains. So I think that's one piece of
really good news on data strategy. And then I would just say the other piece of really good news
is that the new wave of agent AI tools is going to allow both your sort of data savvy, but also your
more like, you know, your non data practitioners to just like have a conversation with your data
and you can kind of achieve that like now and today.
[00:15:34] Jeff Dillon: Yeah, I love that. Look at it the way you're kind of describing it, switching to
something else like kind of your background. You co founded a startup that hacked online
shopper psychology.
What lessons from E commerce conversion now inform student engagement strategies?
[00:15:53] Jennie Wong: That's such a fascinating question. I really appreciate you asking that because
the funny thing is is that the whole like hacking shopper psychology initially all started with the
same problem that we started with a minute ago, which was how do you get past overwhelm,
right? Like how do you break out of analysis paralysis?
And so the E commerce startup that I founded, oh gosh, I guess over a decade ago now, was
kind of based on some of these principles about what drives conversion.
So I think what's really interesting is that higher ed can borrow more than just that lesson from E
commerce, right? So like understanding the paradox of choice is helpful, but there are a variety
of e commerce strategies that higher ed can use. And it's kind of interesting that this is an
underinvested area because if you think about it, you have a company like you know, a shoe
company, right, that is using all of these conversion tactics for $50 sale or $150 sale and higher
ed is not yet necessarily hip to those campaigns or tactics. But you know, you're talking about
$50,000 of tuition for like a single year, but you're not using as sophisticated a tool set. I'll just
give one example. Like I talked about the paradox of choice and how to, you know, and there
are different techniques for that. But another great example is like running a comeback
campaign.
So one thing that E commerce retailers know that is much cheaper and more efficient and more
effective to get somebody who has already bought from you once to then buy from you a second
time and then turn them into sort of a true customer, right? So they'll run like a comeback
campaign. They know it's economically efficient to offer you the one time only customer, like a
discount code or something like that.
Some universities are using this Notion. But there are also many universities that are not
necessarily looking at, hey, we have a student that maybe stopped coming back a year or two
ago, maybe we should go back and run a comeback campaign to that student. And even if
something in their life means that they might no longer be a traditional four year degree
candidate, can we re engage them through something online or certificate program or something
that's for working adults. Right.
[00:18:20] Jeff Dillon: I'm seeing that. I think you're talking about stop outs that like, hey, they've been
here but we need them to finish. And I'm even seeing continuing education divisions really
ramping up their marketing efforts because the traditional younger students are harder to get
now. So it kind of falls in line, I think with what you're saying. It's pretty fascinating to me. But
talking about conversions, we often feel these budget pressures and it makes ROI the board's
favorite acronym. Which metrics best prove the value of AI initiatives in year one versus year
three?
[00:18:56] Jennie Wong: So higher ed doesn't measure ROI in quite the same way that commercial
industries measure that. So I think we have to be a little more nuanced now. Type 1 strategic
value, which I alluded to before, which is the inflow of resources into the university. You can use
more traditional measurements, right? So the value of your corporate partnerships, you know,
like if you're applying AI to sort of say, you know, how do we improve the productivity of our
public private partnerships or how do we improve something like, you know, fan ticket sales
through college athletics department or how do we improve alumni giving, then you can use kind
of very traditional measurements there.
Type 2 strategic value oftentimes is more either efficiency of your business, administrative
functions or the effectiveness of your mission areas.
So for those you will want to look at, obviously there are sort of the big ticket items of year over
year persistence rates or your enrollment yield and those sorts of things. But you can also look
at these more leading indicators before you sort of get to the ultimate outcome measures.
Things like application abandonment.
Right. Like what is your current rate of students starting your online application process and then
leaving it unfinished and can you move the needle there through some sort of application of data
and AI? Like I said, it's a little more nuanced, but I think that has a lot of value, especially for
institutions that are really looking to make sure that they are being open and inclusive to student
profiles that might be first generation English learners or lower income.
[00:20:37] Jeff Dillon: You mentioned the application process. It makes me think of this company I've
been following, Mutara, who's reinventing the application Process because it's kind of old
fashioned. I know a lot of schools have the common app now and we have a shared experience,
but getting the smallest piece of data in the very first step, like I need your name, your email and
a couple things and then let's treat it like a process rather than something that's going to take
you a few hours in one sitting. And it's, it's quite fascinating studying this user behavior from all
these other industries. But I want to ask you, looking ahead five years, what campus job do you
think will change the most because of AI and why?
[00:21:15] Jennie Wong: I think just about every campus job is going to have hopefully the benefit of AI.
Like, I definitely don't think of it as humans or AI. I just think that we are all on a progression to
humans assisted by AI and we have a kind of specific taxonomy for agentic AI that kind of
demonstrates that it's again, it's not binary like I was saying before. It's not either the human has
to do the final click or the human is completely out of the loop. Right. But rather that in the day of
whether that is a career counselor for a university or whether that is the facilities manager for a
university or whether that is a teaching assistant for a university. Right. No matter what is the job
that you hold, that there will be different aspects of your workday five years from now where you
are receiving higher or lower levels of assistance from AI as appropriate to the task. So like
lower risk tasks, potentially much more independent automation, things that are being escalated
to you because they are more complex or let's say it's a student having an emotional crisis or
something like that, then it should immediately get that constituent or that student to a human
being and that's where you should be spending the majority of your time.
[00:22:42] Jeff Dillon: Yeah, I think you're right on with that take. I see it in my own daily activities
already.
Well, finally I want to wrap it up with one last question. What book, podcast or practice keeps
you curious and inspired outside of work?
[00:22:57] Jennie Wong: So I look to thought leadership that is talking about what I call the 5 to 9, right.
The personal part of life.
Because I think outside of business hours is where the competition for our attention is actually
the most fierce.
So I get inspired by best practices and principles that come out of fields like, you know,
entertainment or other types of, you know, like media and engagement.
And I see that as really rich fodder for coming together then with the sort of the business part of
the day, the 9 to 5. And I recently saw a really cool example of that. I got to experience a great
example of that at Arizona State University, where they have a partnership with an immersive
VR company called Dreamscape. So they're using something called Dreamscape Learn at ASU
to do things like using VR headsets to teach biology and chemistry. And I got to actually
experience one of their chemistry adventures.
[00:24:02] Jeff Dillon: Wow, that's cool. We just had Gemma Garcia from ASU on a couple weeks
ago, so I'll have to check that out.
[00:24:08] Jennie Wong: That's awesome.
[00:24:09] Jeff Dillon: Well, thanks for taking the time, Jennie. It was great to have you on. And we'll
put links to your profile and slalom in in the show notes.
[00:24:17] Jennie Wong: Thank you. I appreciate that. And yeah, anybody that wants to learn more
about our approach to data and AI strategy for higher education, they can find the show notes
and link to our article on Medium.
[00:24:28] Jeff Dillon: All right, thanks, Jennie. Bye Bye.
[00:24:29] Jennie Wong: Thanks, Jeff.
[00:24:36] Jeff Dillon: We wrap up this episode. Remember, EdTech Connect is your trusted
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