Marketers need to be curious. AI isn't an magic bullet, it doesn't fix everything you need. But finding solutions that are powered by Artificial intelligence that do things more intelligently can give you a massive competitive advantage in the marketplace to do things in a competitive way.
How marketers can get started with artificial intelligence?
Yeah, I tend to look at three main steps.
The first is, think about all the things you do as a marketer. So, let's
say you're an inbound marketer in an agency or with a brand. If you make a
list, and you could just do this in an Excel spreadsheet if you want to or in a
Google sheet, just make a list of all the activities you do every week or every
month.
So, it might be developed email subject lines, build an editorial
strategy, figuring out when to send, monitor performance, whatever it is, just
create your list. Then go through and put a column for how much time you spend
every month doing that thing. Then make a leap of faith that someone, whether
it's an existing company you work with or another software company, has built a
more intelligent way to do that.
Take the things that you spend the most time doing. They will usually be
very data intensive, very time intensive. Look at those things and go see if
you can find something to pilot. Because AI isn't a switch you flip. We don't
just like all of a sudden go find a way to do everything more intelligently.
We do it at a use case level, a single activity level. And so, find the
things that you’re spending a ton of time on that are very inefficient that
might be able to be done better. So, the first is time intensive, data-driven
activities. Look for smarter ways to do it.
The second is think about all the data you have access to as a marketer.
So, you may have your M-Systems, your automation system, your call tracking system,
conversational (indistinct), all these sources of data. And try and figure out,
are we able to leverage all that data to better personalize, to tell a better
story, to better engage with consumers?
The third, and actually what ends up probably being the best way to
start, is go talk to your crotch platform companies, because you don't want to
have to go buy 15 or 20 new software tools to do each individual thing smarter.
What you want is to make bets on the platform companies that are taking a very
strategic approach to building smarter features within the product that you can
then use more intelligently.
Know More: Machine Learning
Do you see any kind of obstacles and things that people should look out
for as they're thinking about those sorts of things? - I think they try and...
Well, one, they don’t understand what AI is and they just asked for AI. So
first it's education on what it is. Then they probably try and achieve too much
right of way versus small scale pilot tests.
So, I think the smartest route is to find the thing that is kind of a
quick win that you can build support around and you have a greater probability
of it making an impact. So, an example might be media buying.
So if you're spending $5,000 a month, or 10,000 or 50,000, and humans
are doing it all, and they're the ones making the changes to the media buying
plan, and they're the ones moving the resources around, and they're the ones figuring
out which creative to offer and which audience segments to target, none of that
is a human better than a machine at. And so, if you're spending a ton of money,
go try and find a way to have that done more intelligently.
You can probably have quick wins, even if you just start with gone
division of your company instead of like the whole thing. So that's an example of
try and find something where the probability of it being better than what
you're doing is pretty good and the investment required to figure that out is
pretty little, versus going and trying to tackle some massive undertaking that
would take a year and then you'll find out, well, that didn't work, and half a
million dollars later we don't believe AI is going to work.
I think that's a great point about finding one area and then sort of
rolling it out across an organization. Again, thinking of the analogy to
electricity, it's like bringing in an electrician into a factory. And just
because you hire an electrician, he still needs to understand every single role
within that and how to best apply a more intelligent automation to that role.
So for the marketers who are curious, who try and find ways to go
explore, find better solutions, find more information, develop a better confidence
around what it is and how it can be used, those are the marketers that'll
probably excel in their careers and build competitive advantages for brands.
Are there any particular resources that you would recommend that marketer’s
kind of look into if they're trying to learn more about this?- Yeah, I mean,
selfishly, that's why we built the Marketing AI Institute for. So that's what
we built. Now, where we learn from, honestly, there aren't that many marketing
resources for it. A lot of individual brands are doing similar things. So, SAS
companies that are powered by AI are trying to create more demand for smarter
solutions, so you see a lot of it there. But the places we tend To go is Google
has a goggled, and its literally just free resource centre to teach about AI.
Microsoft teaches about AI; IBM has a ton of free resources and demos. So,
I would say go to the big companies that are building it, who are betting their
future on consumers demanding smarter solutions, and a lot of them are creating
resources to help educate the market so there is demand.
It's why Microsoft runs their Microsoft AI commercials. They're trying
to differentiate that these are smarter ways to do things. So yeah, I think once
you’re curious about it and you start looking around, you'll start seeing a lot
of resources out there for marketers to learn from. –
We're definitely fans of the human-centauromachies learning blog that
Google has out there, which, you know, is being very careful about avoiding
bias and things like that within machine learning. - Which is a whole mother topic.
Definitely. - It's not perfect, AI is not perfect, but it's a unique
opportunity I think, for many of us we won’t see something like this in our
careers again. That really gives us the chance to leap forward in our
capabilities and our knowledge.
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