At the cutting edge of design innovation, where data reigns supreme, we invite you to explore the transformative power of data in shaping creative experiences. In today’s fast-paced digital world, understanding the audience is key to crafting compelling experiences. This podcast delves deep into the intersection of data and design, revealing how analyzing user behavior, demographics, and preferences can revolutionize the creative process.
Greg, the CMO at Eyelit, the world's fastest-growing manufacturing software platform, leads global go-to-market strategy and execution for Eyelit and MESTEC, the company's pioneering applications. Prior to this role, Greg held global marketing executive roles at large and small technology brands across more than 9 industries, including 9+ years based in Europe. He holds a BA from Willamette University and an MBA from the University of Washington.
Taran is a seasoned marketing professional with over 20 years of global experience in technology, eCommerce, and go-to-market strategy. As founder of Growth Natives, he leverages his expertise in driving sustainable growth through high-impact digital experiences. With a track record of success at companies like i2 Technologies and Cvent, Taran excels in improving accountability, ROI measurement, and customer satisfaction.
Rukman's background in communication and management fuels her creativity as the Creative Director at Growth Natives. She skillfully blends her expertise to craft strategic content and design user-friendly digital experiences that captivate audiences and simplify the user journey. Her passion lies in transforming her creative spark into tangible business success, making her an invaluable asset to Growth Natives and a favorite among clients.
Harshika is a seasoned product manager with a passion for business transformation, design thinking, technology, marketing trends, SaaS security, and human-computer interactions. What interests her most is the intersection of these fields, which is why she stays on top of the latest industry insights to uncover strategies for success in today's dynamic business landscape.
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Hello and welcome everyone.
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My name is Hershey and I’m currently the lead product manager at the Growth,
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utilization of technology and keeping up with
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marketing trends is something that is of great interest to me.
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And today I have three very special guests
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with me to discuss about a very special topic.
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So we talk a lot about data, but I think there is a gap
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in also analyzing how data really impacts
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marketing and specifically design.
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So my first guest today here is Greg, who is the CMO for eyelet,
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the world’s fastest growing manufacturing software platform
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that compromises a pioneering application.
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So for Greg,
he has been responsible for the go to my
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IT strategy and execution on a global scale.
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Prior to his role, Greg has held a variety of global marketing executive position
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at large scale as well as more technology
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brands across nine plus industries.
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And he’s also had over nine years of experience in Europe.
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His educational background, consists of a B.A.,
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Willamette University and an MBA from the University of Washington.
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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.
00:14:56:06 – 00:14:58:15
I’m not someone who believes I answers everything.
00:14:58:15 – 00:15:00:06
I think it’s overhyped.
00:15:00:06 – 00:15:02:05
And I think you can easily get lazy.
00:15:02:05 – 00:15:03:23
I don’t I don’t like that.
00:15:03:23 – 00:15:07:18
But one of the things I can do is you can
00:15:07:18 – 00:15:12:24
now you know, go scrape, if you will, the prospects
00:15:12:24 – 00:15:15:24
you want to target and learn more about them.
00:15:16:01 – 00:15:19:08
And so that in me, in my mind, that’s a form of data, right.
00:15:19:21 – 00:15:22:17
Like are they going to do they have brands
00:15:22:17 – 00:15:25:20
they seem to prefer if you’re able
to find that out, that have a certain
00:15:25:20 – 00:15:30:16
look and feel or have a certain design oriented right, you could leverage that.
00:15:31:23 – 00:15:33:11
so that that
00:15:33:11 – 00:15:37:11
is a, I think, an exciting area for AI in terms of providing
00:15:37:11 – 00:15:41:07
an additional data source to inform the design upfront.
00:15:41:07 – 00:15:44:07
And then, of course, you’ve got to do the multivariate testing.
00:15:45:09 – 00:15:46:12
And that’s an excellent point.
00:15:46:12 – 00:15:49:17
I mean, there’s yeah, you know, I mean there’s I
00:15:50:10 – 00:15:53:22
today can help you like, you know, with all the known best practices.
00:15:55:03 – 00:15:58:24
So you know, even our design teams are drawn
00:15:59:00 – 00:16:02:00
is they like leveraging AI
00:16:03:11 – 00:16:04:16
to a fairly high degree
00:16:04:16 – 00:16:08:11
in terms of at least getting the wireframes or options of wireframes,
00:16:08:11 – 00:16:11:19
you know, like what is it’s just making everything so fast paced.
00:16:13:14 – 00:16:17:10
everything is with us,
with AI coming into the picture.
00:16:17:10 – 00:16:21:24
And yes, I agree with you that I may be overhyped, but I
00:16:22:23 – 00:16:23:19
a part of me also
00:16:23:19 – 00:16:26:19
feels that if you don’t incorporate in your,
00:16:26:20 – 00:16:31:18
design activities or operations, you would be
00:16:31:18 – 00:16:35:16
tend to left behind in the sense that it’s definitely making things faster.
00:16:37:05 – 00:16:37:14
Yeah.
00:16:37:14 – 00:16:40:21
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.
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