The Revenue-Focused Marketer

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So welcome, Greg.

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We’re super excited to have you today.

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Thank you.

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It’s a great topic, and I’m really looking forward to the conversation.

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so, the other two guests

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that I have with me, the first one is, a serial entrepreneur with over

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23 years of experience in leadership roles across B2B and e-commerce platforms.

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And he’s also the CEO and co-founder of Growth Leaders, as well as the growth.

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So welcome, Darren.

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Thank you.

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Very glad to be part of this.

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Yeah, always exciting to have you here.

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And last but not the least, with over

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five years of experience in research and design,

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our next speaker is an in-house expert that has really challenged world,

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creative streak and brought it to her professional life

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and adapted to the, business environment.

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She currently works
as the creative director

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and the manager of Customer Success at Group leaders.

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So welcome ruckman.

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Thank you RC.

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Very excited for this one.

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Yeah,
we’ll dive straight right into our topic.

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And I guess

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maybe Romain can start us off with really helping us understand

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what data driven design even means.

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Sure.

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so data
driven design is basically an approach

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that any designer would take.

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in understanding the end users

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needs before creating a specific product.

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So a design is not only about making

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things look beautiful or simple,

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or something that you can just create based off of your gut and intuition.

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And not to say that we can entirely negate those aspects,

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but those aspects somehow need to be validated.

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And that’s done by understanding data, analyzing performance metrics,

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conducting surveys, interviews, and really understanding

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that the designer is not the end user or maybe is just a user.

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But what you’re trying to make the product for is for potentially

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thousands and millions of users and basically understanding their needs.

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Before you dive into creating any product.

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Definitely.

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And then,

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Greg, what do you think are like, you know, some of the benefits,

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maybe that you have experience in your experience.

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So I’d like to build on what ruckman said,

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which I thought was really the the truth that I’ve experienced,

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you know, a lot of people today talk about us.

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It’s kind of the trendy thing to talk about.

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and see,

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but if you think about it, what’s really behind

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that is the design, because that’s where the user,

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the prospect, has the connection with your product.

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and as ruckman said, just something beautiful

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or very creative doesn’t necessarily mean it’s going to be effective.

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And so the opportunity we have now where you can

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instrument everything and measure everything, whether it’s every square

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and circle screen or a device or how someone engages, with content,

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you have the opportunity now to take the best

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of design creativity and and look and feel,

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but really match that to how we can engage

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and provoke the right customer action.

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So for me,
this is really about making CSS or UX,

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whatever you want to call it, sort of going beyond the hype

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and really addressing what will make a difference, what will

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convince someone to use your your platform?

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What will convince someone to stay with it?

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Because that’s where the connection happens.

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And and how do you take a fabulous graphic designer and channel that?

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Right.

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Because graphic design by itself is not enough.

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You know, it needs to be married to the way that the user

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will be, really hooked and connected.

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So yeah, sorry, that was really long and wordy.

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No, I think that’s that’s absolutely right.

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And I think it’s,

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you know, over, over time

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the importance of empirical evidence over non empirical,

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I think is actually growing

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so that we have seen, you know, across the board,

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even traditional companies that are not digital in any way,

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whether it is clothing,

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whether it is like food products, they are also incorporating like,

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you know, data driven design in their products.

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So if you think about like, you know, how augmented reality is changing,

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you know, where people can actually like, you know, try on clothes virtually

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and companies are actually running real,

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you know, time

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analysis on how the users

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are interacting with their brand even before they launch a product.

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so, you know, all the major global brands

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have augmented reality shops where they are

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actually having consumers like, you know, they have their beta consumers,

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they have them try on those products virtually.

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Like these
people are sitting all across the world,

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and they are trying and giving their feedback.

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So just think about like, you know, they they can incorporate localization.

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They can correlate, you know, how somebody in China feels about their dress

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versus somebody in Europe or somebody in the US.

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So it’s like you can, you know, it’s having a huge impact on how

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you are able to give a very personalized experience as well.

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And if you talk about like, you know, web experience,

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the same website is catering to a teenager

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as well as, you know, an older person.

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But they can with the empirical evidence they have,

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they can actually change the user experience to show

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what is relevant to that particular audience.

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So there’s like a huge shift that is happening.

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Some of it is apparent and some of it is not even apparent.

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But behind the scenes, there is a lot of data that is at work.

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Yeah.

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And actually one one thing that I think is really happening in

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this context is brands are now visual.

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First used to be words first, right.

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You know, if you were the CMO of a consumer or B2B

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brand, you put so much effort into the strapline, right?

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And the about paragraph.

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And I’m not saying that’s not so important, but,

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you know, especially as the generation of people who’ve grown up digitally,

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you know, who grew up in an image, first world become the consumer,

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the look and feel is their brand before any words.

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and that’s why a data driven design is so, so important.

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I have a really favorite example.

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A few years back, I was doing it.

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My team was doing a survey.

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We wanted to get feedback, and we would give you a buy

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you a cup of Starbucks coffee if you would fill it out.

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So we did an A and a B test, have a coffee at us.

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And the A was beautifully designed.

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It was a great postcard, digitally

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and paper based with stunning photography of a cup of coffee.

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If you wanted to drink

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this like it was, you could see this theme, like photography is incredible.

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Like you talk, you want to drink it right then and there.

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And the B was a person sitting in the cafe, having the coffee.

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Well, guess which one performed best.

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It’s the person.

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So that’s an example where design great design itself is not enough.

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You’ve got to have the data.

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And the data shows that people, people imagery

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at least at the time, would outperform non people imagery.

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to me that’s an example of data driven design.

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And and not just celebrating something that’s beautiful that a great graphic

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designer artist artistry.

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But doing it with much more intention.

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relevance.

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And then the relevance is, is extremely important.

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And then you can only understand relevance

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and or visual force to a more granular level.

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now, as
like I would say about 2 to 3 years

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ago, videos worked great, but now there has been data

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that has come about and said that there are users

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that will interact on a specific product,

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but not on a specific product, for example,

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an edu tech or an e-learning product would have tons and tons of videos.

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But for example, products, you would think that product like Airbnb

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would have beautiful videos of, apartments and places

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that people would want to go to, but that actually cost bounce rate.

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People just want to see high quality static images.

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So that is all real data as opposed like understanding

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where an image would work, where videos would work.

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So like just to understand visual force at a more granular level.

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And you know, I think in that in that context,

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something that’s become real important is it means that you can no longer.

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And maybe it’s been true for a while, but I think there’s still people doing this.

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You can no longer design

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these sort of monolithic marketing strategies and campaigns

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where you’re going to put an enormous investment into creating all these assets,

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because then you’ve you’ve used the budget and time and you’ve got this thing

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that’s really hard and expensive to change.

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so you have to design more micro level

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campaigns or strategies because you can get the data and adapt.

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so you, for example, like you wouldn’t say,

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hey, it’s the image first world, you know, video platform as well.

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I’m going to put a 100% of my budget and effort into a series of videos, right?

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The smarter thing now is to say, I’m going to do a few, I’m

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going to do a few static images and measure and then, you know, invest

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in that format and that graphic approach that works better.

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So you’ve got to be I, in my experience,

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much more micro in how you design and execute

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marketing so that you can actually use the data right.

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You haven’t sort of boxed yourself in to this incredibly

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long running thing that might not perform optimally.

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Right. Or that.

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So you can take advantage of the data.

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right.

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Definitely.

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And I think a b testing, like you mentioned

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before, also serves
great purpose in marketing today.

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Like, I don’t know,

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even if it’s a campaign, even if it’s a design, just having options

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and seeing what was expressed makes a huge difference.

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that makes me want to sort of ask you,

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then how do you think the amalgamation of design and data analytics really works?

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And like, what aspects do you like?

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Is it data first and then you make design?

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Or is it you make a design and you have the data and then you analyze it.

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How do they typically

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work to you?

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So I think there’s like,

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I would say, you know, it has to be pre design as well as post design.

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you know

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pre design is predominantly based on best practices.

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That’s driven by data from the past.

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So for example like you know where do you place

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you know your CTAs

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is you know,

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you’d see that majority of the websites have the form on the right hand side.

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So there’s a reason it’s on the right hand side because that’s,

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been proven that if you have the form on the right hand side,

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you will get more form filled.

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So, you know, those are certain things that are like best practices.

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They are known.

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you know, you have to incorporate them.

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And that’s like the pre design thing.

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Once you designed it, then you run, you know, analytics

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and experiments that will tell you like you know which variant.

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So you mentioned A-B testing or it multi variant testing.

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You know you can run

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multiple tests which tell you

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you know what works.

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And you know, you can keep adding complexity to it

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in terms of if you know your users like I was referring earlier, like, you know,

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if it has certain demographics, if it is certain,

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you know, segments of your target audience,

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there would be like, a need for personalization as well as conversion

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optimization based on, the analysis that you see post-launch as well.

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So the redesigning, you got to make sure it’s all best practices

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that are data driven.

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Once you built launched, then you collect data

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from real user experience and see, like, you know what makes sense.

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You should run like multi variant tests on it as well.

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and the end goal is that, you know, you have to

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make the end consumer happy

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and give them the experience that they deserve

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or they want.

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And you know one of the one of the new sort of or I’m sorry.

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Go ahead, go ahead, go ahead, go ahead.

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Sorry.

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So one of the new new ways maybe to do what

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what Taryn referenced is and I’m not if I’m not, I want to be clear.

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I’m not someone who believes I answers everything.

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I think it’s overhyped.

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And I think you can easily get lazy.

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I don’t I don’t like that.

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But one of the things I can do is you can

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now you know, go scrape, if you will, the prospects

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you want to target and learn more about them.

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And so that in me, in my mind, that’s a form of data, right.

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Like are they going to do they have brands

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they seem to prefer if you’re able
to find that out, that have a certain

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look and feel or have a certain design oriented right, you could leverage that.

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so that that

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is a, I think, an exciting area for AI in terms of providing

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an additional data source to inform the design upfront.

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And then, of course, you’ve got to do the multivariate testing.

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And that’s an excellent point.

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I mean, there’s yeah, you know, I mean there’s I

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today can help you like, you know, with all the known best practices.

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So you know, even our design teams are drawn

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is they like leveraging AI

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to a fairly high degree

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in terms of at least getting the wireframes or options of wireframes,

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you know, like what is it’s just making everything so fast paced.

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everything is with us,
with AI coming into the picture.

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And yes, I agree with you that I may be overhyped, but I

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a part of me also

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feels that if you don’t incorporate in your,

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design activities or operations, you would be

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tend to left behind in the sense that it’s definitely making things faster.

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Yeah.

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No, I, I agree, I, I think my, my experience

00:16:40:21 – 00:16:43:21
and my current purview is I can make you better,

00:16:44:13 – 00:16:48:09
but it doesn’t replace the IQ and the ideation

00:16:48:09 – 00:16:51:10
that needs to come
from a talented designer.

00:16:52:09 – 00:16:53:03
absolutely.

00:16:53:03 – 00:16:56:03
And and I think you need to put them
together,

00:16:56:06 – 00:16:59:03
not one versus the other.

00:16:59:03 – 00:17:01:21
It doesn’t work without really good input.

00:17:01:21 – 00:17:04:21
And that input can really come from like,
you know, like I can

00:17:04:23 – 00:17:09:12
I is like an assistant that you have,
you know, if you train them

00:17:09:12 – 00:17:12:14
well, if you give them good instructions,
if they know, like, you know,

00:17:13:20 – 00:17:14:09
it’s like a

00:17:14:09 – 00:17:18:20
barista, you know, if you know the guy,
if they know the kind of coffee you want

00:17:18:20 – 00:17:22:03
and you tell them once and they get it and they’ll, like, reproduce it,

00:17:22:12 – 00:17:26:00
that’s like, you know, so that AI assistant is like a,

00:17:26:16 – 00:17:29:09
a good barista that understands

00:17:29:09 – 00:17:32:09
you and then is able to deliver the right experience.

00:17:32:16 – 00:17:35:05
And I think same way.

00:17:35:05 – 00:17:38:21
but I do agree
that AI is something that helps.

00:17:39:08 – 00:17:41:21
It’s also something that you have to be careful about

00:17:41:21 – 00:17:44:21
because overuse can also kill you as well.

00:17:45:03 – 00:17:46:10
it can you absolutely.

00:17:46:10 – 00:17:50:04
I, I feel like, yes, we’re talking about data and we’re talking

00:17:50:04 – 00:17:52:01
about numerical evidence.

00:17:52:01 – 00:17:53:10
but as designers,

00:17:53:10 – 00:17:56:22
we also, by the end of the day, have to empathize with the end user.

00:17:57:06 – 00:17:59:13
That’s a big part of our job role.

00:17:59:13 – 00:18:04:23
and that can only happen with human IQ and even IQ, for that matter.

00:18:04:23 – 00:18:08:19
So, yeah, I definitely would lag behind on that.

00:18:09:06 – 00:18:12:06
And I think you see the the biggest risk of using

00:18:12:18 – 00:18:17:00
or using AI is you could be calling, creativity.

00:18:17:18 – 00:18:19:23
Yeah. So if you think about it like, you know, the

00:18:21:08 – 00:18:24:01
no AI for example, like they were like,

00:18:24:01 – 00:18:28:05
you know, the music players before the iPod came in,

00:18:29:10 – 00:18:32:02
but, you know, no way

00:18:32:02 – 00:18:35:03
I could have actually thought of like, you know, this should be the right kind

00:18:35:03 – 00:18:37:13
of experience that people would be looking for.

00:18:37:13 – 00:18:39:16
It really took,

00:18:39:16 – 00:18:41:18
you know, the human sense of, you know,

00:18:41:18 – 00:18:44:18
what prevails.

00:18:44:21 – 00:18:47:21
And what could be the next great thing?

00:18:49:11 – 00:18:51:18
you know, if I too, would have been used

00:18:51:18 – 00:18:54:18
probably giving you a variant of a Walkman
or variant of,

00:18:56:01 – 00:18:58:05
you know, a CD player would have never thought

00:18:58:05 – 00:19:01:05
of something so out of the box

00:19:01:08 – 00:19:04:06
because it’s only based on, you know, what it is learned

00:19:04:06 – 00:19:06:20
over time and

00:19:06:20 – 00:19:10:15
the the iPod had not happened yet.

00:19:11:00 – 00:19:15:22
So, in fact, iPod not was even
not the first digital audio player.

00:19:17:00 – 00:19:19:05
it was not the first audio digital player.

00:19:19:05 – 00:19:23:16
you know, I never was the first company
that came out with mass

00:19:23:16 – 00:19:27:14
produced digital players, but they the user experience was terrible.

00:19:28:02 – 00:19:30:15
And so, you know,

00:19:30:15 – 00:19:31:11
Apple won the game.

00:19:31:11 – 00:19:34:02
But anyhow,

00:19:34:02 – 00:19:37:02
Hershey, any comments on any for us?

00:19:38:02 – 00:19:42:00
Yeah, I definitely agree with the the point the device shared.

00:19:42:00 – 00:19:45:05
And like, you know,
you know, it’s making such a huge impact.

00:19:45:05 – 00:19:48:19
But obviously like you can’t let go of the human touch

00:19:49:04 – 00:19:53:14
and especially to point out,
like innovation to have anything

00:19:53:14 – 00:19:57:23
that is innovative, you can’t just
rely on the data that’s in the past.

00:19:59:01 – 00:20:01:06
so, Greg, maybe you can shed some light on

00:20:01:06 – 00:20:04:11
like how do you really identify
what are relevant data points?

00:20:04:11 – 00:20:08:02
Because they’re there is a lot of data that might come in.

00:20:08:10 – 00:20:11:03
How do you sort of
go about the relevancy of them?

00:20:12:21 – 00:20:14:22
It’s a great question.

00:20:14:22 – 00:20:18:11
I, I’m not sure I have a great answer,
but I’ll tell you something

00:20:18:11 – 00:20:19:20
I’m very focused on.

00:20:19:20 – 00:20:24:02
And I would say increasingly
in the last few years, with something

00:20:24:02 – 00:20:29:10
that I call the provocation,
and that is why does this matter now?

00:20:29:20 – 00:20:35:01
I think a huge difference maker or a game
changer in the effectiveness of your

00:20:35:01 – 00:20:40:05
marketing is if you can not only explain
why you have a value proposition,

00:20:40:14 – 00:20:45:23
why you would create value,
how you’re differentiated, but why now?

00:20:46:05 – 00:20:51:08
I think that a huge, huge advantage,
and I think a lot of brands,

00:20:52:08 – 00:20:53:20
fail to do that.

00:20:53:20 – 00:20:57:08
You know, I don’t think it’s good enough
to be relevant or good or better

00:20:57:08 – 00:20:59:19
or cheap or faster. It has to be now.

00:20:59:19 – 00:21:02:19
So that’s where I think

00:21:02:24 – 00:21:06:02
data elements that might help you identify

00:21:06:03 – 00:21:10:18
the now piece could be really important.

00:21:10:18 – 00:21:12:17
And how also help you focus. Right.

00:21:12:17 – 00:21:16:18
Because with AI,
which I think is a great way to go

00:21:16:18 – 00:21:21:21
get the data much faster,
much more efficiently.

00:21:22:05 – 00:21:24:07
But you don’t need 10,000 data points.

00:21:24:07 – 00:21:26:11
And what are you going to do with 10,000
data points like that?

00:21:26:11 – 00:21:29:15
So could we go get 50 or 25 data points?

00:21:29:15 – 00:21:32:23
That might help us to figure out
what is that provocation.

00:21:32:23 – 00:21:33:09
Right.

00:21:34:17 – 00:21:38:22
and often it’s not so obvious, right?

00:21:38:22 – 00:21:39:24
I mean, we all could

00:21:39:24 – 00:21:43:20
say, oh, we’re going to sell to so-and-so
because they want to save time or money.

00:21:43:20 – 00:21:48:08
I mean, that’s quite commonplace,
but is that an insight enough

00:21:48:08 – 00:21:51:08
to really provoke strong interest?

00:21:51:12 – 00:21:55:04
My experience is, no, it’s it’s
something everyone else is saying.

00:21:55:04 – 00:21:56:14
It’s this sea of sameness.

00:21:56:14 – 00:22:00:13
Can you find that provocation
that’s a little deeper?

00:22:01:04 – 00:22:03:02
It’s maybe not so apparent.

00:22:03:02 – 00:22:06:02
And so that’s where I would love to see

00:22:06:18 – 00:22:07:18
the profession go.

00:22:07:18 – 00:22:09:17
And I think you guys are really focused
on this.

00:22:09:17 – 00:22:12:17
It’s one of the things I’m excited
about working with you on,

00:22:13:02 – 00:22:16:11
with your team
is let’s go find the provocation.

00:22:16:11 – 00:22:19:11
Let’s go get the data
that tells us the provocation.

00:22:19:20 – 00:22:22:21
because that will, I think, inform design

00:22:23:03 – 00:22:26:02
that is more precisely targeted,

00:22:26:02 – 00:22:28:23
that is going to provoke more interest.

00:22:28:23 – 00:22:31:10
and then beyond that design, help us

00:22:31:10 – 00:22:34:15
come up with words,
the words that are also going to be,

00:22:35:15 – 00:22:36:17
more likely to

00:22:36:17 – 00:22:39:17
really energize that prospect.

00:22:39:17 – 00:22:40:19
Great example.

00:22:40:19 – 00:22:41:03
I’m sorry.

00:22:41:03 – 00:22:44:03
I’m going to just add on to what just Greg said,

00:22:44:13 – 00:22:47:13
you know, a great example that I can offer

00:22:47:21 – 00:22:50:20
is, you know, Amazon back in the day,

00:22:50:20 – 00:22:53:20
they figured out, like, you know, one click order

00:22:54:05 – 00:22:56:10
and they patented it

00:22:56:10 – 00:22:59:07
because they saw it as a game changer.

00:22:59:07 – 00:23:02:14
And you know, that patent existed till 2017.

00:23:02:14 – 00:23:06:10
So no other e-commerce website could have a one click or until 2017.

00:23:06:17 – 00:23:09:17
It gave them such a huge competitive advantage.

00:23:10:12 – 00:23:12:24
So that’s like, you know, and again,

00:23:12:24 – 00:23:16:16
it was all based on data driven design.

00:23:17:19 – 00:23:19:21
They ran an experiment back

00:23:19:21 – 00:23:23:06
in, I think the late 90s or the early 2000 that,

00:23:24:00 – 00:23:27:00
hey, if we give people an option

00:23:27:06 – 00:23:29:04
that they are and,

00:23:29:04 – 00:23:33:05
you know, back
then it was actually if you think about it

00:23:33:12 – 00:23:36:24
from a security perspective, it was very out of the box

00:23:37:12 – 00:23:40:02
because you were asking a person to store their credit card,

00:23:40:02 – 00:23:43:02
all their, you know, personal information, everything.

00:23:43:02 – 00:23:47:16
And then you are like giving them the ability to place an order, right?

00:23:47:16 – 00:23:50:02
Just a single click of a button.

00:23:50:02 – 00:23:53:01
The first thing intuitively that would come to mind is

00:23:53:01 – 00:23:55:07
this could lead to abuse, but it did not.

00:23:55:07 – 00:23:58:07
I mean, they ran experiments and they saw that, you know, people love it.

00:23:58:24 – 00:24:01:24
And for years they were able to keep their customers

00:24:02:04 – 00:24:04:24
from going through the competitors because of the competitors.

00:24:04:24 – 00:24:07:18
Every time you had to go through the entire checkout process.

00:24:09:03 – 00:24:09:17
So if you’re

00:24:09:17 – 00:24:12:17
somebody who wants to order, like, you know,

00:24:13:23 – 00:24:15:08
just household stuff

00:24:15:08 – 00:24:19:21
on a monthly basis many times a month, how easy it is for you to go and say,

00:24:19:21 – 00:24:22:21
you know, like, okay, I want like, you know,

00:24:24:18 – 00:24:26:17
toilet paper,

00:24:26:17 – 00:24:28:02
I mean, like toothpaste.

00:24:28:02 – 00:24:31:02
I like whatever you need, like, just one click and it is ordered.

00:24:31:08 – 00:24:32:06
How beautiful is that?

00:24:32:06 – 00:24:33:23
And that was all driven by data.

00:24:33:23 – 00:24:35:07
And that’s what,

00:24:35:07 – 00:24:39:00
you know, how you can actually make it a competitive advantage as well.

00:24:39:24 – 00:24:43:07
this is an extreme example, but even in your daily use,

00:24:43:08 – 00:24:45:03
you don’t have to patent anything.

00:24:45:03 – 00:24:49:02
There are like so many interventions that you are running with your customers.

00:24:49:16 – 00:24:52:16
If you think about how it makes their lives easy,

00:24:52:18 – 00:24:54:18
what is it that they’re looking for when they’re engaging with you?

00:24:56:09 – 00:24:56:19
and if you

00:24:56:19 – 00:25:00:09
think about it like, you know, Amazon was just selling commodities,

00:25:00:17 – 00:25:04:14
you can buy that commodity like 100 different ways, 100 different vendors.

00:25:05:07 – 00:25:06:22
Favorite example of that?

00:25:06:22 – 00:25:08:15
It’s the fast forward.

00:25:08:15 – 00:25:11:16
It’s it’s
not it’s extremely bold or powerful.

00:25:11:16 – 00:25:15:08
But you know,
we all know the abandoned rate on

00:25:15:10 – 00:25:18:10
a form is like 90% plus.

00:25:18:21 – 00:25:22:12
So recently I’m trying to remember exactly

00:25:22:14 – 00:25:26:15
I don’t remember exactly when, but we tried this thing called it.

00:25:26:16 – 00:25:28:24
And I don’t know if this is exactly
the right technical term,

00:25:28:24 – 00:25:31:15
but the prompted form

00:25:31:15 – 00:25:33:23
and basically it asks

00:25:33:23 – 00:25:37:12
you field by field, it doesn’t show you this thing you have to fill out.

00:25:37:22 – 00:25:40:17
And we think if the abandoned rate was like

00:25:40:17 – 00:25:43:20
95%, we gained five points or more with that.

00:25:44:07 – 00:25:47:19
To me, that’s a perfect example of data driven design, right?

00:25:47:24 – 00:25:51:11
It may seem small, but the provocation is, you know what?

00:25:51:12 – 00:25:53:22
People hate filling. Things happen.

00:25:53:22 – 00:25:54:18
You know, it’s online.

00:25:54:18 – 00:25:57:02
It’s supposed to be one click like so.

00:25:57:02 – 00:26:01:20
You can make small changes like that, that make an enormous difference, right?

00:26:01:23 – 00:26:02:15
Yeah.

00:26:02:15 – 00:26:05:08
And I think that’s when Amazon figured out, you know, the provocation

00:26:05:08 – 00:26:09:06
back then was online shopping was still not easy enough

00:26:09:15 – 00:26:13:08
to activate people on the scale that Amazon was able to achieve.

00:26:13:08 – 00:26:16:11
And it was divine that that made the difference.

00:26:16:23 – 00:26:17:09
Yeah.

00:26:17:09 – 00:26:21:00
And I feel another thing that people even today,

00:26:21:09 – 00:26:24:17
tend to overlook, in terms of data, is that

00:26:25:06 – 00:26:29:19
65% of website traffic comes from mobile devices

00:26:29:19 – 00:26:35:07
and most designers are actually still going the old way.

00:26:35:07 – 00:26:36:20
They take,

00:26:36:20 – 00:26:39:24
you know, a download from the customer, the lookup or reference,

00:26:39:24 – 00:26:43:15
build a wireframe on their desktop and then come up with a website.

00:26:43:15 – 00:26:47:11
What they tend to overlook is that the bounce rate really happens

00:26:47:11 – 00:26:48:14
because people are trying

00:26:48:14 – 00:26:52:02
to access their website or their product on their mobile devices.

00:26:52:17 – 00:26:58:18
And it was not built mobile first and it was a non responsive design.

00:27:00:12 – 00:27:02:13
that but that said,

00:27:02:13 – 00:27:05:10
e-commerce platforms, users

00:27:05:10 – 00:27:08:10
on e-commerce platforms usually tend to convert

00:27:08:22 – 00:27:13:02
if they’re on their desktop as opposed to that they are on their mobile devices.

00:27:13:02 – 00:27:15:06
Yes, they will go through your products,

00:27:15:06 – 00:27:17:16
they will go through your stuff on their mobile devices.

00:27:17:16 – 00:27:21:18
But you know, and I think this could be because they want like a larger view

00:27:21:18 – 00:27:23:02
of what they’re about to purchase.

00:27:23:02 – 00:27:24:22
So they’ll go on their desktop.

00:27:24:22 – 00:27:28:21
So this is all data and really understanding the end user

00:27:28:22 – 00:27:32:05
who is trying to, interact with your product

00:27:32:07 – 00:27:35:06
before designing anything.

00:27:35:06 – 00:27:37:15
Actually, I have a great example

00:27:37:15 – 00:27:40:15
here, and it involves some work you just did for us.

00:27:40:21 – 00:27:43:21
So you’ve made this beautiful new landing page,

00:27:44:07 – 00:27:47:20
to help promote a new product with navy blue in the back.

00:27:47:20 – 00:27:49:19
And I personally love navy blue.

00:27:49:19 – 00:27:53:16
I have no design sense, no talent in that regard, but I do that navy blue.

00:27:54:00 – 00:27:55:08
I thought it looked sharp.

00:27:55:08 – 00:27:58:21
And so a colleague said, hey, this looks great, but isn’t it

00:27:59:02 – 00:28:02:16
isn’t white like isn’t supposed to be, white isn’t simple.

00:28:02:16 – 00:28:04:10
And Apple kind of pioneered that.

00:28:04:10 – 00:28:07:13
So I said I don’t know about that.

00:28:07:13 – 00:28:09:03
And so we worked together.

00:28:09:03 – 00:28:10:24
We did a little research.

00:28:10:24 – 00:28:16:02
It turns out that dark colors on mobile
devices have higher consumption

00:28:16:02 – 00:28:19:02
of content, because lighter text,

00:28:19:17 – 00:28:22:13
on dark backgrounds is easier to read.

00:28:22:13 – 00:28:24:06
So there’s another example,

00:28:24:06 – 00:28:27:21
so that I don’t know that that’s why you guys did it might have been.

00:28:28:08 – 00:28:30:05
But what you did is beautiful.

00:28:30:05 – 00:28:32:17
But I am sold like I’m now.

00:28:32:17 – 00:28:36:00
I’m really so not only do I love Navy with white text,

00:28:36:01 – 00:28:40:06
but it’s going to drive more consumption right on, especially on a mobile device.

00:28:40:22 – 00:28:45:07
Yes, that’s that’s the battle I have fought internally as well.

00:28:45:18 – 00:28:46:02
Greg.

00:28:47:01 – 00:28:49:15
Oh, this is dark mode.

00:28:49:15 – 00:28:51:09
And everybody was like, why dark mode?

00:28:51:09 – 00:28:54:09
I’m like, guys, because the world is mobile.

00:28:54:12 – 00:28:57:15
And you know, that’s what we need to do

00:28:57:21 – 00:29:00:21
because that’s why Apple came out with dark mode.

00:29:01:06 – 00:29:04:06
Because they like, you know, people’s engagements

00:29:04:12 – 00:29:08:18
both on App Store as well as like, you know, with, everything else.

00:29:09:16 – 00:29:11:23
it was much better in dark mode.

00:29:11:23 – 00:29:14:19
So anyhow,

00:29:14:19 – 00:29:15:24
yeah, that’s enough.

00:29:15:24 – 00:29:18:24
My obsession with, like, dark mode and

00:29:19:08 – 00:29:22:00
dark mode always dark.

00:29:22:00 – 00:29:25:00
I am a fancy.

00:29:25:08 – 00:29:27:23
I think I’m definitely part of this club, too.

00:29:27:23 – 00:29:30:06
you know, given the choice.

00:29:30:06 – 00:29:34:04
And I also think it’s nice that some products like including

00:29:34:05 – 00:29:37:23
even the product that we have a degree that gives you the option to switch

00:29:37:23 – 00:29:42:08
between modes because I think preference, again, based on the target

00:29:42:08 – 00:29:45:22
audience changes and whether accessing it from also.

00:29:46:05 – 00:29:49:19
So just having the option to like, you know, switch between those two modes,

00:29:50:01 – 00:29:52:05
I think has been a game changer.

00:29:52:05 – 00:29:56:20
And I do want to transition
to talk about our next topic here.

00:29:57:04 – 00:30:00:11
So with data it’s always changing.

00:30:00:11 – 00:30:04:13
And then I think one of the bigger issues that people sense is like garbage

00:30:04:13 – 00:30:06:04
in, garbage out. Right.

00:30:06:04 – 00:30:10:10
So how do you guys really go about like identifying

00:30:10:10 – 00:30:14:20
like what are the best tools or techniques that you find for data collection?

00:30:15:05 – 00:30:19:07
Because, I think just having trust in the data

00:30:19:07 – 00:30:23:09
that you’re using is very important to be able to really make these decisions.

00:30:25:20 – 00:30:27:00
So actually, as

00:30:27:00 – 00:30:30:00
far as tools are concerned, I think,

00:30:30:01 – 00:30:33:06
I mean, over the last decade, there has been so much evolution

00:30:33:06 – 00:30:36:06
in, in martech and design tech.

00:30:37:17 – 00:30:39:09
there’s

00:30:39:09 – 00:30:42:09
and every tool out there is good enough.

00:30:42:09 – 00:30:45:06
I think the biggest challenge

00:30:45:06 – 00:30:48:06
in using technology is how well it is implemented.

00:30:50:14 – 00:30:54:06
you know,
I keep going back to our customers

00:30:54:06 – 00:30:58:24
as well as our partners that, you know, build what is right for you.

00:31:00:04 – 00:31:03:24
So if it is, you know, an e-commerce store,

00:31:05:08 – 00:31:08:13
the analytics and the measurements you need are different.

00:31:08:22 – 00:31:11:22
If it’s a B2B website, it’s different.

00:31:12:08 – 00:31:14:10
If it is,

00:31:14:10 – 00:31:17:04
and, you know, there’s,

00:31:17:04 – 00:31:18:18
like I was saying earlier, there’s also like

00:31:18:18 – 00:31:21:18
a lot of best practices, data that is available.

00:31:21:19 – 00:31:23:12
So if somebody is just getting started

00:31:23:12 – 00:31:26:13
and they don’t want to invest in like, you know, tons of technology,

00:31:27:03 – 00:31:30:09
they should just rely on best practices that people have published

00:31:30:09 – 00:31:31:08
and say, this works.

00:31:32:17 – 00:31:33:04
rather than

00:31:33:04 – 00:31:36:04
trying to build something on their own, you know,

00:31:36:23 – 00:31:39:19
the if you are going to implement technology,

00:31:39:19 – 00:31:43:21
make sure that you implement it in a way that’s easy for your teams.

00:31:45:07 – 00:31:48:07
you know, usually,

00:31:48:21 – 00:31:51:09
what we see is like, there’s a lot of tech debt

00:31:51:09 – 00:31:54:04
that companies acquire over time because they’ve just, like, kind of been

00:31:54:04 – 00:31:58:05
investing in the tech stack, but there’s not enough use of it.

00:31:58:05 – 00:32:02:01
Like there’s shelf, there’s like, so avoid that at any cost.

00:32:03:05 – 00:32:05:13
you know, all tools,

00:32:05:13 – 00:32:08:13
in my opinion, are somewhat equal.

00:32:09:10 – 00:32:13:13
If you some of them will be easier to use, will get you the same results.

00:32:13:13 – 00:32:16:13
Some of them will be harder to use, will get you the same results.

00:32:17:08 – 00:32:19:20
some of them may be 80% accurate.

00:32:19:20 – 00:32:22:08
The others may be like, you know, 90% accurate.

00:32:22:08 – 00:32:25:08
But the key is like, all you’re looking for when you’re trying to make data

00:32:25:08 – 00:32:29:02
driven decisions is directional insights.

00:32:30:21 – 00:32:32:09
you know, whether it is,

00:32:32:09 – 00:32:35:09
you know, Google Analytics, whether it is,

00:32:36:10 – 00:32:40:17
you know, technologies like Hotjar or Optimizely that you can use for like,

00:32:40:17 – 00:32:45:02
you know, multivariate testing, maybe testing, looking at user behavior,

00:32:46:03 – 00:32:48:01
all that is great.

00:32:48:01 – 00:32:51:03
But if it is not implemented right,

00:32:51:03 – 00:32:54:05
and if it is not interpreted right, you know you’ve lost the battle.

00:32:54:20 – 00:32:57:15
So the most important thing is like implement it right.

00:32:57:15 – 00:33:02:11
And then make sure that you spend enough time analyzing the data as well.

00:33:02:24 – 00:33:05:24
And a lot of times you also have to,

00:33:07:09 – 00:33:09:15
depend on,

00:33:09:15 – 00:33:12:18
you can’t just it just can’t be purely like, you know, data, data, data.

00:33:13:11 – 00:33:17:10
You have to, you know, have a sense of, you know, the,

00:33:17:22 – 00:33:20:22
the underlying non empirical things as well.

00:33:21:00 – 00:33:24:00
Like for example, like, you know, seasonality.

00:33:24:03 – 00:33:27:23
So if you run tests on your website

00:33:27:23 – 00:33:30:23
during Thanksgiving, that’s going to be completely different

00:33:31:02 – 00:33:34:02
than if you ran it in the summer basically.

00:33:34:02 – 00:33:36:10
Or if you’re like running a flash sale.

00:33:37:13 – 00:33:39:23
then the kind of testing you need is different.

00:33:39:23 – 00:33:42:20
Then, you know, if you’re wanting

00:33:42:20 – 00:33:45:20
allowing users to engage on on a piece of content

00:33:46:05 – 00:33:49:12
so it can’t be like you can’t use the same metrics like, okay, like if, if,

00:33:49:24 – 00:33:53:14
for example, like this webinar, if people are bouncing after five minutes

00:33:53:14 – 00:33:56:17
of watching it, that means like we’ve done a very poor job of this webinar

00:33:57:12 – 00:34:00:14
or if it is like an e-commerce site, if somebody spent like even two minutes on

00:34:00:22 – 00:34:03:22
a product. And that’s amazing, actually.

00:34:04:04 – 00:34:07:23
So you you have to have the right benchmarks,

00:34:08:03 – 00:34:11:02
the metrics against which you want to measure as well.

00:34:11:02 – 00:34:14:02
And you can’t just like be that one size cuts all.

00:34:14:11 – 00:34:18:02
So sorry for the long answer, but I do think that that’s it’s a very,

00:34:18:02 – 00:34:21:02
very important as but like I see it so many times

00:34:21:03 – 00:34:24:16
that our customers have bought technology, but they’re not able to use it

00:34:25:00 – 00:34:28:14
because either they are able to implement it, right, or they don’t have

00:34:28:19 – 00:34:31:11
the right set of benchmarks, metrics that they want to measure.

00:34:33:12 – 00:34:33:17
Yeah.

00:34:33:17 – 00:34:36:17
You know, I’ll share a favorite example of mine

00:34:36:17 – 00:34:40:03
that’s more recent that I think sort of answers your question.

00:34:40:03 – 00:34:44:04
Not fully, but one thing I say, though, and I made this point

00:34:44:04 – 00:34:48:09
earlier, is I am bullish on AI in the context

00:34:48:09 – 00:34:52:04
of scraping as a form of data collection because I do think

00:34:52:16 – 00:34:57:10
that my fellow Okemos, I don’t think it’s because they’re lazy,

00:34:57:10 – 00:35:03:02
but have gotten comfortable with these sort of generic ISP’s.

00:35:03:02 – 00:35:03:12
Right.

00:35:03:12 – 00:35:08:05
There’s a title and like, it’s just kind of obvious stuff

00:35:08:05 – 00:35:12:05
that that, that anyone might know or guess.

00:35:12:16 – 00:35:13:11
And, you know,

00:35:13:11 – 00:35:17:13
I think getting a love of deep are really can make a difference is one thing.

00:35:17:13 – 00:35:21:03
So getting data about the prospect

00:35:21:17 – 00:35:23:24
at a deeper level, I think is really critical.

00:35:23:24 – 00:35:25:22
I think marketers have to work harder at that.

00:35:25:22 – 00:35:28:16
And I I’m anxious to see if I can do more.

00:35:28:16 – 00:35:28:23
There.

00:35:28:23 – 00:35:29:17
And there’s sort of

00:35:29:17 – 00:35:33:16
maybe we move into this mode where it’s something I want to do with the growth

00:35:33:16 – 00:35:34:11
native Siem.

00:35:34:11 – 00:35:37:04
There’s the idea of a dynamic ICP.

00:35:37:04 – 00:35:40:07
You know, there’s no longer this fixed slide that doesn’t really change.

00:35:41:08 – 00:35:42:15
but the other

00:35:42:15 – 00:35:45:19
point I want to make,
though, is I think marketers, because it’s

00:35:45:19 – 00:35:48:19
so easy to get data
now, are measuring too many things

00:35:49:00 – 00:35:51:17
and, and it’s vanity.

00:35:51:17 – 00:35:54:00
so I’ll give you this example. So,

00:35:54:00 – 00:35:57:22
we did this email cat scale campaign,
you know, where you can

00:35:58:09 – 00:36:01:24
prime these domains
so that you don’t show up as spam,

00:36:01:24 – 00:36:04:24
and you can send a million
and a half emails in three months, right.

00:36:05:06 – 00:36:06:24
Like this incredible scale.

00:36:06:24 – 00:36:10:03
And I know it sounds like frightening,
but you.

00:36:10:14 – 00:36:13:11
Anyway, I tried this,

00:36:13:11 – 00:36:19:02
and at the beginning, what typically
happens is the open rates are quite high.

00:36:19:02 – 00:36:22:16
You’re not bouncing because you’ve primed
the domains and you’ve got like spam.

00:36:22:22 – 00:36:24:16
Over time, the open rates go down.

00:36:24:16 – 00:36:27:13
So at the end of this campaign,
which I think did

00:36:27:13 – 00:36:30:13
almost a month and a half of emails,
I don’t remember exactly the number.

00:36:30:15 – 00:36:33:15
We went from like 80%
open rates down to like ten.

00:36:33:21 – 00:36:37:23
The the marketer in me is like,
oh my gosh, like I am terrible, I suck.

00:36:38:07 – 00:36:40:18
This is like the worst thing ever.

00:36:40:18 – 00:36:43:23
I just I’m going to go,
you know, find a different customer.

00:36:43:23 – 00:36:45:20
Like I can’t stand this, right.

00:36:45:20 – 00:36:47:07
Like how can I be so bad?

00:36:47:07 – 00:36:50:11
But you know what we got like 80 meetings

00:36:50:23 – 00:36:54:00
out of this campaign
just for a B2B technology scenario.

00:36:54:14 – 00:36:56:13
That’s all that matters, right?

00:36:56:13 – 00:36:57:15
We’re very low cost.

00:36:57:15 – 00:36:58:19
We got 80 meetings.

00:36:58:19 – 00:37:01:19
Who cares with the open mic?
But it’s right.

00:37:02:01 – 00:37:04:03
It didn’t matter, you know.

00:37:04:03 – 00:37:07:20
So I think it is now maybe too easy

00:37:07:20 – 00:37:11:12
to measure too many things
and they feel good about it.

00:37:11:12 – 00:37:13:00
It makes a nice dashboard.

00:37:13:00 – 00:37:16:06
You can have a great slide
for your board review or whatever,

00:37:16:14 – 00:37:20:10
but you really should measure a few things
that really matter.

00:37:20:16 – 00:37:24:04
And in the B2B technology
space, it’s clearly

00:37:24:09 – 00:37:26:04
did you get a meeting with the customer?

00:37:26:04 – 00:37:29:04
Unless you sell online without sales

00:37:29:08 – 00:37:31:23
salespeople,
did you get a meeting or did they?

00:37:31:23 – 00:37:34:13
Oh, will they return your call? Will
they read your email?

00:37:34:13 – 00:37:36:15
Like those three things really matters.

00:37:36:15 – 00:37:41:07
But do we have to really track
the open rates on every like maybe not.

00:37:41:18 – 00:37:43:02
And so I actually think,

00:37:44:06 – 00:37:44:17
this is

00:37:44:17 – 00:37:47:17
an area that marketers have to start
thinking about is,

00:37:47:17 – 00:37:51:03
is maybe not trying to measure
so many things

00:37:51:03 – 00:37:54:09
because that can take a lot of time just making sense of it and publishing it.

00:37:54:09 – 00:37:58:11
And, I think the ideal CMO dashboard

00:37:58:11 – 00:38:01:17
moving forward is actually skinnier, not bigger.

00:38:01:23 – 00:38:04:23
Even though you can measure more things.

00:38:04:23 – 00:38:06:15
Right. I totally agree with you, Greg.

00:38:06:15 – 00:38:07:19
And I think that

00:38:07:19 – 00:38:09:10
goes back to what I was saying, that,
you know,

00:38:09:10 – 00:38:12:23
you got to have the metrics, you know,
what is important to you, like the

00:38:13:09 – 00:38:16:06
I mean, one thing that comes to mind is

00:38:16:06 – 00:38:19:06
it’s not related to design, though,
but like, you know,

00:38:20:19 – 00:38:22:02
on social media,

00:38:22:02 – 00:38:25:01
you know, people are doing influencer
marketing these days

00:38:25:01 – 00:38:28:07
and you don’t even know, like,
you know, the influencer using

00:38:28:07 – 00:38:32:16
how many fake followers they have, like,
they’re, you know, I mean, they’re like,

00:38:35:10 – 00:38:36:16
there’s like studies that are like,

00:38:36:16 – 00:38:41:09
you know, 60, 70% of the followers
or some of the,

00:38:41:09 – 00:38:44:09
the largest celebrities
are actually fake profiles.

00:38:45:11 – 00:38:47:01
even on LinkedIn.

00:38:47:01 – 00:38:50:05
I think they’re trying to clean up
like there’s, like almost like 40 million,

00:38:52:01 – 00:38:54:00
fake profiles, I believe.

00:38:54:00 – 00:38:57:03
So it’s, you know, I mean, now if you say,
oh, you know, my,

00:38:57:10 – 00:39:01:03
my post got like, you know, 500 likes,
but how many of them were fake,

00:39:01:05 – 00:39:02:23
you know, did you

00:39:02:23 – 00:39:06:11
and if their goal is to actually get a
meeting or like, you know, drive business

00:39:06:11 – 00:39:09:11
for your business,
did that actually happen or not?

00:39:09:12 – 00:39:12:23
So, you know,
if a post gets you a lot of likes,

00:39:12:23 – 00:39:16:10
but it doesn’t get you a single meeting,
it’s useless

00:39:16:17 – 00:39:20:18
versus a post that may get like
just a handful of likes, but got you

00:39:21:24 – 00:39:24:12
got you in front of the right people.

00:39:24:12 – 00:39:27:12
so I think that’s a very, very important
point that you just made, Greg.

00:39:28:12 – 00:39:30:24
but it has to be like the right metrics.

00:39:30:24 – 00:39:33:24
You know, what matters to the business.

00:39:33:24 – 00:39:36:13
And and building on that,
you mentioned benchmarks.

00:39:36:13 – 00:39:40:24
So I had the privilege to work recently
for a subsidiary of Bain

00:39:41:05 – 00:39:44:05
that did performance
benchmarking for SAS companies.

00:39:45:03 – 00:39:50:01
the founder is really
the pioneer who started that whole field.

00:39:50:09 – 00:39:54:09
And as a marketer,
I hadn’t really focused on that.

00:39:54:09 – 00:39:58:14
You know, I focus on open rates
and bounce rates and time on site and,

00:39:59:02 – 00:40:02:07
you know, conversion
rates, all well-intended. But

00:40:03:15 – 00:40:06:10
I think the modern CMO

00:40:06:10 – 00:40:09:21
not only should focus on, like the things
that matter like a meeting.

00:40:09:21 – 00:40:10:05
Right?

00:40:10:05 – 00:40:12:04
Or do they want to return your call,

00:40:12:04 – 00:40:15:13
but also like,
are you creating longer term value?

00:40:15:13 – 00:40:16:24
And that’s magic number.

00:40:16:24 – 00:40:18:20
That’s rule 40, right?

00:40:18:20 – 00:40:22:04
These are metrics
that describe commercially

00:40:22:04 – 00:40:25:11
why are you executing effectively.

00:40:25:20 – 00:40:27:22
And I think that is really important.

00:40:27:22 – 00:40:29:18
And they’re just a few of them.

00:40:29:18 – 00:40:31:20
But you should have that context.

00:40:31:20 – 00:40:36:18
And if you use a performance benchmarking
service like the company I came from,

00:40:36:18 – 00:40:40:08
I’m not here to promote that companies
specifically, but they are really good at.

00:40:40:08 – 00:40:44:10
But but if you use a service
or some way to get that,

00:40:44:16 – 00:40:49:15
you can see not only
are you on the right trajectory

00:40:49:15 – 00:40:53:22
in terms of magic number or rule of 40
in terms of profitability, but also

00:40:54:11 – 00:40:58:00
what are you spending to get
a meeting versus your competitors?

00:40:58:00 – 00:41:02:14
Right, as dollars for marketing qualified
lead, how many marketing qualified leads

00:41:02:14 – 00:41:08:12
does it take you to get a closed one up
deal versus your competitors?

00:41:08:20 – 00:41:12:10
I really think that’s where marketers
have to go, as well

00:41:12:10 – 00:41:17:13
as not only these marketing
or very commercially specific metrics,

00:41:17:18 – 00:41:21:04
but benchmarks as well that so, you know,

00:41:21:09 – 00:41:23:24
as a marketer
being the conscience of the company,

00:41:23:24 – 00:41:27:03
which is what I believe ultimately
were responsible for, were the conscience

00:41:27:03 – 00:41:30:03
for performance of the company,
because we have this very broad role

00:41:30:21 – 00:41:33:21
also looking at benchmarks which describe

00:41:33:21 – 00:41:36:24
is the company making long term traction

00:41:37:08 – 00:41:41:16
in a profitable way, in a way
that that’s creating value for the brand.

00:41:44:19 – 00:41:45:18
Oh, absolutely.

00:41:45:18 – 00:41:47:16
And that’s a

00:41:47:16 – 00:41:50:04
you know,
I mean, that that’s great insight, right?

00:41:50:04 – 00:41:53:04
I and I do think and that’s why we,

00:41:53:22 – 00:41:56:16
you know, we try like to call a customer,

00:41:56:16 – 00:41:59:16
especially the CMO is like another revenue
focused marketers.

00:41:59:19 – 00:42:02:08
So, you know, we like to work with revenue
focused marketers

00:42:02:08 – 00:42:05:13
because that’s what I think we shift
as the it’s not just the vanity metrics.

00:42:05:13 – 00:42:08:13
It’s like, you know,
what is the revenue that,

00:42:09:09 – 00:42:12:02
you know, that we are impacting,

00:42:12:02 – 00:42:15:09
as an agency
or like the CMO in their chair.

00:42:15:09 – 00:42:18:09
So, okay.

00:42:19:03 – 00:42:20:01
Right.

00:42:20:01 – 00:42:24:10
Of that is really like just I guess
most designers would understand out there.

00:42:24:23 – 00:42:27:18
what you guys talk about is,

00:42:27:18 – 00:42:31:06
you know, like, to Darren’s point,
people who don’t have high investments

00:42:31:06 – 00:42:35:04
to making extremely technical
tools like Hotjar, Crazy Egg,

00:42:36:03 – 00:42:36:12
Google

00:42:36:12 – 00:42:39:13
Analytics, what we really do
for those customers.

00:42:39:13 – 00:42:43:08
Now, let’s say a customer has come
and is really,

00:42:43:08 – 00:42:45:20
like, attached to his or her product.

00:42:45:20 – 00:42:49:22
And they have like this rigid sense of how
they want their design to look like.

00:42:49:22 – 00:42:51:14
Greg, everyone’s not like you.

00:42:51:14 – 00:42:55:19
So, what we really do for

00:42:55:19 – 00:43:00:04
those customers is we make
and this is sort of like AB testing.

00:43:01:06 – 00:43:04:13
and this is one of our best practices
that has really proven to be good over

00:43:04:13 – 00:43:06:07
the years is like,

00:43:06:07 – 00:43:11:23
we will make a design which is exactly
how the customer wanted it.

00:43:12:10 – 00:43:16:09
And then we will make a B design,
which is based off of our experience

00:43:16:09 – 00:43:19:09
and the data
that is relevant to that industry.

00:43:19:20 – 00:43:23:10
And in 80 to 85% of the cases
over the years,

00:43:23:10 – 00:43:27:00
the customer has gone with the design
that we created.

00:43:27:19 – 00:43:28:01
Right?

00:43:28:01 – 00:43:31:20
So like data really matters
by the end of the day.

00:43:31:20 – 00:43:35:02
And in design you can really always
just showing that you can’t.

00:43:35:02 – 00:43:37:23
Most of the times
you can’t talk people through it.

00:43:37:23 – 00:43:42:12
So we are willing to put in that
like invest that extra time

00:43:42:12 – 00:43:45:21
to be able to convince our customer
and then their potential customers.

00:43:47:19 – 00:43:50:00
And this, this is this brings up
another point

00:43:50:00 – 00:43:53:19
that I’m very passionate about,
which is it’s not just your data.

00:43:54:09 – 00:43:58:11
Like,
yeah, for me, the value of being a client

00:43:58:11 – 00:44:01:17
and growth natives
is you have a wide range of clients,

00:44:01:23 – 00:44:06:17
so you’re seeing this much broader
set of things that work and don’t work.

00:44:06:22 – 00:44:11:04
You’re trying a hundred things
and all of us produce data.

00:44:11:10 – 00:44:13:08
And I benefit from that.

00:44:13:08 – 00:44:15:13
Right? It’s not just my data.

00:44:15:13 – 00:44:18:13
And that’s going to make me more effective
more quickly.

00:44:19:12 – 00:44:23:23
and that’s that’s the huge advantage
of having a partner

00:44:23:23 – 00:44:28:08
like growth natives, you know,
you can’t just look at your own data.

00:44:28:08 – 00:44:31:05
And actually, it’s a big reason
that I don’t believe

00:44:31:05 – 00:44:35:07
the future of marketing
is to have these capabilities in-house.

00:44:35:19 – 00:44:39:15
You want people who look at all
kinds of different

00:44:39:15 – 00:44:43:05
companies and brands and techniques
and tools helping you.

00:44:43:16 – 00:44:46:04
You will be too narrow, too myopic.

00:44:46:04 – 00:44:49:04
If it’s all your data, your perspective.

00:44:50:10 – 00:44:51:18
Correct?

00:44:51:18 – 00:44:52:08
Absolutely.

00:44:52:08 – 00:44:56:22
And I’ll and I’ll go back to the Amazon
example like, you know, we started

00:44:56:22 – 00:45:00:22
doing one click registrations
for our customers for webinars, right.

00:45:01:05 – 00:45:05:13
And like the number of registrations
you get just like

00:45:05:22 – 00:45:10:03
it’s almost like 30, 40% more
because there’s no form to fill.

00:45:10:03 – 00:45:11:02
Like, you know, it’s totally like

00:45:11:02 – 00:45:14:07
because if I’m sending you an email,
I know it’s going to Greg.

00:45:14:15 – 00:45:17:04
It says, Greg, would you like to sign up
for this webinar?

00:45:17:04 – 00:45:19:24
And you click one button

00:45:19:24 – 00:45:22:12
and it sends you your confirmation,
puts it on your calendar.

00:45:22:12 – 00:45:23:16
Like how good is that?

00:45:23:16 – 00:45:24:22
Versus like, you know,

00:45:24:22 – 00:45:27:15
you have to fill out a form
and then like consent and all that.

00:45:27:15 – 00:45:29:08
Like and we already know who you are.

00:45:29:08 – 00:45:32:04
Why make it go through
that extra step basically.

00:45:32:04 – 00:45:35:17
And you know, so that’s
because it’s like another one

00:45:35:17 – 00:45:39:15
click buy from e-commerce is applicable
in so many other places.

00:45:39:15 – 00:45:42:15
Basically,
you know, if it has worked, you know,

00:45:42:15 – 00:45:45:21
you have to learn from it
and see where else can you apply.

00:45:47:08 – 00:45:49:23
anyhow.

00:45:49:23 – 00:45:52:24
I mean, I can take a step further,
like I mentioned earlier, like,

00:45:52:24 – 00:45:56:19
you know, augmented reality,
I think is going to suddenly change

00:45:57:12 – 00:46:00:12
the way products are designed.

00:46:00:20 – 00:46:03:20
as well
as, like new user experiences designed.

00:46:04:13 – 00:46:07:20
there’s also like, and it’s going
to, you know, it’s going to translate

00:46:07:20 – 00:46:11:07
from just consumer to B2B
very soon as well.

00:46:12:09 – 00:46:14:02
things like, you know,

00:46:14:02 – 00:46:17:02
you would have websites where you could
actually go in and experience

00:46:17:07 – 00:46:20:07
how a car would feel before you buy it,
now that you’ll be able to like

00:46:20:11 – 00:46:24:09
I said, what I would like feels like,
you know, how does the interior

00:46:24:09 – 00:46:25:23
feel when you’re sitting in it?

00:46:25:23 – 00:46:27:14
And there’s already like products out

00:46:27:14 – 00:46:29:24
there, but like,
you know, there’s going to be a lot more

00:46:29:24 – 00:46:31:17
advancement in augmented reality.

00:46:32:19 – 00:46:33:00
think

00:46:33:00 – 00:46:36:00
about
it like, you know, across industries,

00:46:36:00 – 00:46:39:17
you can actually like,
you know, virtually feel what your kitchen

00:46:40:03 – 00:46:44:05
would look like before you build it
with all the different variations of,

00:46:44:05 – 00:46:47:09
you know, what kind of cabinets you want,
what kind of like, you know, flooring

00:46:47:09 – 00:46:50:09
you want,
what kind of appliances you want.

00:46:50:19 – 00:46:54:04
You can run all those
before you actually pick

00:46:54:18 – 00:46:57:18
versus like,
you know, earlier, you have to walk into,

00:46:58:12 – 00:47:01:14
a place maybe they would have like
ten displays at the max.

00:47:02:04 – 00:47:03:17
And then you have to
imagine everything else.

00:47:03:17 – 00:47:06:17
Now you can actually have like millions
of combinations

00:47:06:18 – 00:47:09:05
of how you want,

00:47:09:05 – 00:47:13:00
you know, your kitchen or your bedroom
or whatever you’re designing.

00:47:13:05 – 00:47:14:03
So I think there’s going to be like

00:47:14:03 – 00:47:17:20
a huge, shift
from an augmented reality perspective.

00:47:18:09 – 00:47:21:00
There’s also, you know, Greg mentioned AI

00:47:21:00 – 00:47:25:10
and how it’ll help accelerate
some of the design thinking,

00:47:26:11 – 00:47:27:05
I think that’s going to

00:47:27:05 – 00:47:30:08
be, a very, very important aspect as well.

00:47:31:05 – 00:47:36:02
And lastly, I do think that,

00:47:37:02 – 00:47:40:24
you know, companies are going to be able

00:47:40:24 – 00:47:43:24
to personalize experiences at scale.

00:47:44:04 – 00:47:47:09
Yeah, like it has been talked
about for a very long time,

00:47:48:16 – 00:47:50:01
but not achieved yet.

00:47:50:01 – 00:47:52:16
But I do think that the next frontier

00:47:52:16 – 00:47:56:00
is going to be the moment I identify you,
who you are.

00:47:56:05 – 00:47:59:22
I’m going to serve up
such amazing, personalized,

00:48:00:06 – 00:48:03:06
curated content,

00:48:03:11 – 00:48:06:11
that it’s going to make it very,
very sticky.

00:48:06:13 – 00:48:09:08
So I think those are the three things
that I think

00:48:09:08 – 00:48:12:11
I see in the next,
like 5 to 10 years are just going to,

00:48:13:20 – 00:48:16:05
you know, be,

00:48:16:05 – 00:48:20:04
at a different scale and different level
than we have experienced so far.

00:48:23:05 – 00:48:26:09
Yeah, I guess I would do that by saying,
I think three things.

00:48:26:09 – 00:48:30:00
The first is, I think I will help us out.

00:48:30:00 – 00:48:34:02
Marketers help,
you know, agencies like Growth Natives

00:48:34:13 – 00:48:38:07
find the data
that will make a difference to design.

00:48:38:18 – 00:48:40:08
You know, it’s not a 100 data point.

00:48:40:08 – 00:48:41:07
It’s three.

00:48:41:07 – 00:48:44:08
And they’re probably data points
that are not on the surface.

00:48:44:08 – 00:48:48:08
Like we have to work harder to get them,
but they’ll make the difference.

00:48:48:08 – 00:48:51:22
I think I has tremendous potential help
you find those.

00:48:51:22 – 00:48:55:22
That’s the first
the second is I think inbound

00:48:56:04 – 00:48:58:23
is dominating right now.

00:48:58:23 – 00:49:03:06
And probably that’s only going to increase
because that people were selling

00:49:03:06 – 00:49:06:06
to, you know, increasing
had grown up digitally.

00:49:06:07 – 00:49:08:07
They control their experience.

00:49:08:07 – 00:49:09:16
So they don’t want to be sold to you

00:49:09:16 – 00:49:11:23
because that’s
not a controlled experience.

00:49:11:23 – 00:49:15:15
They want to determine how they learn
and how they consume information.

00:49:15:15 – 00:49:19:20
So the opportunity is to win, to be better

00:49:19:20 – 00:49:23:24
than your competitor
by creating an inbound experience.

00:49:23:24 – 00:49:25:22
As time mentioned,

00:49:25:22 – 00:49:29:20
maybe it’s an immersive thing where
you can sit in a car or maybe virtual,

00:49:29:21 – 00:49:33:12
some sort of augmented reality,
but you can create a better,

00:49:34:06 – 00:49:38:05
experience for inbound, which I think is

00:49:38:19 – 00:49:40:03
I think
there will always be some outbound,

00:49:40:03 – 00:49:43:11
but I think the inbound is going to be the
the clearly dominant way

00:49:43:11 – 00:49:46:15
that people connect with brands and decide

00:49:46:20 – 00:49:49:20
how to buy and make decisions.

00:49:50:04 – 00:49:53:01
the third point I’d make is
and I don’t remember who

00:49:53:01 – 00:49:54:11
coined this phrase, but I love it.

00:49:54:11 – 00:49:56:07
It’s a participation economy.

00:49:57:06 – 00:49:59:02
and it sort of builds on the last point

00:49:59:02 – 00:50:03:06
that they increasingly that people
were all selling to, and marketing

00:50:03:06 – 00:50:07:19
to have grown up with the ability
to control how they participate.

00:50:08:16 – 00:50:12:23
and so I think we can use design

00:50:13:04 – 00:50:16:01
to make that participation,

00:50:16:01 – 00:50:18:23
more compelling, whether it’s one click,

00:50:18:23 – 00:50:22:12
to register for webinar,
one click to buy laundry soap.

00:50:22:20 – 00:50:25:14
But there are many different

00:50:25:14 – 00:50:29:12
instances of that many that we don’t know
about yet we haven’t discovered.

00:50:29:12 – 00:50:34:16
But I think the idea of helping people
participate in in your brand

00:50:34:24 – 00:50:38:15
is going to make an enormous difference,
and we need data to do that.

00:50:38:15 – 00:50:41:15
It that’s not it’s not design alone.

00:50:42:00 – 00:50:44:01
Those are three, three areas where I think

00:50:44:01 – 00:50:48:03
there’s lots of upside,
but it requires getting the right data.

00:50:48:03 – 00:50:51:10
And it’s it’s a few data points
probably in the under the surface.

00:50:51:10 – 00:50:53:13
And you can go find those right ones.

00:50:53:13 – 00:50:55:08
I think that will make all the difference.

00:50:59:13 – 00:51:02:13
Yeah, I guess, most of it.

00:51:03:05 – 00:51:05:22
Well, yeah, I think that definitely

00:51:05:22 – 00:51:08:22
sounds like a very exciting future.

00:51:08:24 – 00:51:13:02
I know I would definitely like
to be a part of it, even as a consumer.

00:51:13:13 – 00:51:16:13
I think there are exciting things ahead
there.

00:51:16:13 – 00:51:19:13
And you were saying something
I was just going to say,

00:51:19:22 – 00:51:22:13
you know, one of my favorite
saying is like, you know, in God

00:51:22:13 – 00:51:25:13
we trust,
but for everything else, show me data.

00:51:25:20 – 00:51:28:20
And I think that’s really the, you know,

00:51:29:06 – 00:51:31:04
so, yeah,

00:51:31:04 – 00:51:34:04
you know, there is there is trust,

00:51:34:17 – 00:51:37:17
in data that has to be built.

00:51:37:22 – 00:51:40:14
and then once you have that trust in data,

00:51:40:14 – 00:51:44:20
it can really help
you drive a lot of great decisions.

00:51:45:17 – 00:51:49:02
And, you know, we’ve talked
so many examples today

00:51:49:11 – 00:51:52:11
that actually prove it
beyond a certain point.

00:51:53:01 – 00:51:54:12
But data is important.

00:51:55:15 – 00:51:56:09
when designing

00:51:56:09 – 00:52:00:13
experiences, data is important
when making business decisions. And,

00:52:01:17 – 00:52:05:17
you know, the way the world is shaping
up, it’s becoming a,

00:52:06:12 – 00:52:09:17
you know, very experiential economy.

00:52:10:14 – 00:52:14:08
So it’s not just about like, you know,
like everything is about experiences,

00:52:14:08 – 00:52:18:09
whether it is travel, whether it just
like, you know, you buying a car,

00:52:18:09 – 00:52:22:13
whether it is like buying
a piece of software, whether it is so big.

00:52:22:20 – 00:52:26:16
Experiences
are now the most important thing

00:52:27:05 – 00:52:30:09
in how people make their buying decision.

00:52:32:18 – 00:52:34:15
And, you know, like

00:52:34:15 – 00:52:37:14
there’s so many studies out there

00:52:37:14 – 00:52:41:08
that the experience with the brand
is the most important thing.

00:52:41:08 – 00:52:43:08
And it’s not just like before they buy.

00:52:43:08 – 00:52:46:08
It’s also like
while they’re using your product.

00:52:46:09 – 00:52:49:09
Also like,
you know, post the the whole life,

00:52:49:11 – 00:52:52:01
you have to like look at the design

00:52:53:00 – 00:52:56:14
and design their, experience
with the product like throughout.

00:52:56:14 – 00:52:58:13
It’s not just like,
you know, they’re coming to

00:52:58:13 – 00:53:01:05
like if we use the Apple example,
like Apple is a great website,

00:53:01:05 – 00:53:04:05
you come there, you buy the product,
but that product is great as well

00:53:04:05 – 00:53:09:08
when they use that, like,
you know, and Apple has been the only

00:53:10:11 – 00:53:13:07
thorn,
which is an extremely commoditized thing

00:53:13:07 – 00:53:16:07
where people actually
line up a day before to buy it.

00:53:17:03 – 00:53:18:15
So why is that?

00:53:18:15 – 00:53:21:15
It’s just because people want more
of that experience.

00:53:21:18 – 00:53:25:17
People want like,
you know, the first ones to have it

00:53:26:07 – 00:53:30:06
and and see how, you know, different
it is on a faster desktop.

00:53:30:16 – 00:53:33:16
So it’s that,

00:53:34:05 – 00:53:36:10
you know, that mentality

00:53:36:10 – 00:53:39:01
that companies have to embrace

00:53:39:01 – 00:53:42:09
that it’s it’s a great design

00:53:42:21 – 00:53:45:21
then that’s driven by data and it’s driven

00:53:46:02 – 00:53:49:15
by ultimately what the consumer wants.

00:53:53:00 – 00:53:54:11
Definitely.

00:53:54:11 – 00:53:57:01
Wow. This is such an exciting session.

00:53:57:01 – 00:54:01:12
I know we’re running out of time,
but I just wanted to take this, time

00:54:01:12 – 00:54:04:12
to thank all three of you
for your time today.

00:54:04:19 – 00:54:08:18
I know I have learned a lot, and I’m sure the people that tune in

00:54:08:18 – 00:54:11:14
to listening to this webinar will also learn a lot,

00:54:11:14 – 00:54:15:10
and especially the examples I think I’m taking a lot back

00:54:15:10 – 00:54:17:07
with just the examples that you guys share.

00:54:17:07 – 00:54:20:07
So thank you so much for your time today.

00:54:20:16 – 00:54:21:03
Thank you.

00:54:21:03 – 00:54:22:05
It is a pleasure.

00:54:22:05 – 00:54:24:05
Pleasure to be part of this. Thank you for hosting.

00:54:24:05 – 00:54:27:05
Great conversation. Great topic.

00:54:27:08 – 00:54:29:01
and I’m excited for the work.

00:54:29:01 – 00:54:31:12
You guys will do for my brand.

00:54:31:12 – 00:54:33:11
in this area.

00:54:33:11 – 00:54:34:23
Thanks, Greg.

00:54:34:23 – 00:54:36:11
Thanks, everybody. Thank you.