This episode of The New World of Consumer Behavior features an interview with Dan Richardson, Head of Data for Asia Pacific at Yahoo!, a global media and tech company that connects people to their passions and provides partners with a full-stack platform for businesses to amplify growth and drive more meaningful connections across advertising and search. In his role, Dan is in charge of shaping the commercial data strategy and delivering effective audience engagement solutions to Yahoo’s agency, brand and publisher partners. From an industry side, Dan chaired the IAB Australia’s Data Council from 2018 to 2022, helping lead educational initiatives, and served on the IAB New Zealand Standards and Measurement Council. He previously served as a board director for the International Advertising Association and as president of the IAA's Young Professionals. In this episode, Dan talks about the growing importance of contextual targeting in digital advertising, why investing in building first-party data strategy is more critical than ever, and how crafting a fair and equitable ad funded internet is a key step for a balanced future online.
This episode of The New World of Consumer Behavior features an interview with Dan Richardson, Head of Data for Asia Pacific at Yahoo!, a global media and tech company that connects people to their passions and provides partners with a full-stack platform for businesses to amplify growth and drive more meaningful connections across advertising and search.
Dan is in charge of shaping the commercial data strategy and delivering effective audience engagement solutions to Yahoo’s agency, brand and publisher partners. From an industry side, Dan chaired the IAB Australia’s Data Council from 2018 to 2022, helping lead educational initiatives, and served on the IAB New Zealand Standards and Measurement Council. He previously served as a board director for the International Advertising Association and as president of the IAA's Young Professionals.
In this episode, Dan talks about the growing importance of contextual targeting in digital advertising, why investing in building first-party data strategy is more critical than ever, and how crafting a fair and equitable ad funded internet is a key step for a balanced future online.
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Key Quotes
“The key thing is to recognize that we also, as consumers and people, we all enjoy free content, add funded content. So that does require some form of identity or technology to be applied there. We really do need to find a middle ground that allows that to thrive, as well. There's great publishers out there, ourselves, but other global publishers employing journalists producing great content. Now to thrive that needs to be viable across the open web and not just housed within a particular operating system or walled garden. There needs to be room for both.” - Dan Richardson
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Episode Timestamps
02:14 Dan’s role at Yahoo!
03:47 How Dan uses data
06:38 Dan’s data sources
12:24 Contextual targeting in advertising
15:33 Next gen audiences
19:48 Consumer behavior data
22:14 Using data to solve problems
24:45 Data security
27:16 General Data Protection Regulation
33:39 Improving customer experiences
37:45 Data do’s and don'ts
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Links
Kat Harwood: Hello and welcome to the New World of Consumer Behavior: Lessons from Data Pioneers. I'm your host, Kat Harwood, Director of Corporate Communications at Near. This episode features an interview with Dan Richardson, Head of Data for Asia Pacific at Yahoo.
Dan is in charge of shaping the commercial data strategy and delivering effective audience engagement solutions to Yahoo's agency, brand, and publisher partners. From an industry side, Dan chaired the IAB Australia's Data Council from 2018 to 2022, helping lead educational initiatives, and served on the IAB New Zealand Standards and Measurement Council. He previously served as a board director for the International Advertising Association and as President of the IAA’s Young Professionals.
In this episode, Dan talks about the growing importance of contextual targeting in digital advertising, why investing in building first party data strategy is more critical than ever, and how crafting a fair and equitable ad funded internet is a key step for a balanced future online.
But first, here's a quick word from our sponsor:
Narrator: Imagine what your company could do with one of the world's largest volts. Of intelligence on consumer behavior, the possibilities for business efficiency are endless across people, places, and products, across retail, restaurants, tech and tourism.
Data is the key to unlocking insights that drive results. For your business Near is the Global SaaS leader in privacy led data intelligence with 1.6 billion data points worldwide. Go to near.com to learn how near can help your business make better decisions.
Kat Harwood: Now, please enjoy this interview with Dan Richardson.
Dan, it is so great to have you here on the show today. You are coming to us from sunny Sydney, and I think it's best to kick off with the basics. So if you could tell us a little bit about what you do day to day and your overall role at Yahoo, that would be great.
[00:02:21] Dan Richardson: Yeah, thanks for having me, Kat. A pleasure to be here and it is sunny in Sydney for once, um, which is, it's nice to report.
It's been a bit of a crazy year down here weather wise. But in my current role at Yahoo, I look after our apac, uh, region, but that is specifically for our commercial data strategy. So, If you break that down, it's essentially working with marketers and publishers to help them build, uh, omnichannel strategies.
So that could be using audiences for targeting, for insights, segmentation, really getting into the testing of how we're using that data and those audiences effectively, but also extending, [00:03:00] uh, at the moment in a big way towards measurement. So that's online to offline measure. Understanding which channel consumers are engaging with most, and then what's their journey.
And finally, privacy, which is a big one, an ever growing piece of the role at the moment. So lots of stuff happening, but essentially working with all of our agencies, publishers across the APAC region to help them do better with our toolkit. Wow,
[00:03:27] Kat Harwood: wonderful. It sounds like you have a lot in your toolkit to work with and a lot going on.
And as you know here at Near, we use data to really help companies develop business strategies and be more strategic, which it sounds like you're very well aware of and also grow and scale. So if you will, how are you and your team currently using data, and then how are you using data to better understand the behavior of your customers or consumers?
[00:03:54] Dan Richardson: Well, Yahoo has been around for, uh, 28 years now. You can refer to us as [00:04:00] one of the, uh, the OG. The grandfathers of the internet. So we've, we've seen a lot of different data, uh, come and go. So when we started using data, it was very much Dave and Jerry's, uh, worldwide web search, and then evolving to be a, um, a global publisher, uh, which we still are, and then into an ad tech business, in fact, a full stack.
Ad tech business. So that means we service ad buyers or brands on the demand side and publishers on the sell side in our exchange. And that all, all comes through to a unified view of consumers or an identity graph, which I know you guys are working on. But essentially we see about 200 billion, uh, cross screen, uh, data signals globally, uh, every day.
And to bring that down to apac, we're, we're looking at over a hundred million. Unique user, the profiles in APAC every month. So that's the total sphere. And I think, um, if you break that down to an even more important piece of that, which is, you know, how many people do [00:05:00] we know to be in a, a registered or addressable state, where we're confident that the identifiers that are coming through let us know who they are and, and what type of advertis.
They'd like to receive. So that sits at about 58 million, uh, across the region. So there's a lot of different data signals in there coming in, but we're really focused on, uh, our first party data. It's even more important these days to have a very strong first party data strategy and not rely on vendors or third parties necessarily.
So for us, that would be people who are coming to our. So Yahoo Finance, the Yahoo Mail, uh, logging in news, sport, lifestyle, people who are searching on those sites, and then marrying that with other information as well, such as, you know, mobile location or behavior across, uh, the open web, not just our, our own and operated properties.
To answer your question, there's a lot of different things that we use, but that's the summary. [00:06:00] So
[00:06:00] Kat Harwood: many. It's amazing. You think back 28 years. I remember when Yahoo first started and it was definitely, you know, one of the first emails that I probably had and search engines that I used. And it's just incredible to see where we've come from, from, you know, day one to now and we just have so much more data and we know what to do with it.
You know, we have higher quality data and it just really helps us make those, you know, strategic decisions. So really interesting to get that background. So, Said, let's take a deeper look at the vault of data that you're pulling from. So when your organization started using data, how many different sources did you consider and how many do you use today?
[00:06:42] Dan Richardson: I think it's fair to say that, um, we're using a lot more data these days than we used to, particularly due to the evolution of program. Ad buying and selling. Uh, so if you think about the old days, you'd have typically, uh, people interacting with, uh, a website or an app, [00:07:00] and you're able to collect a, uh, a cookie or an ad ID there, and then pass that into your, your data lake.
Now you could match that to a, a form of identity, which you could use to target or measure them anywhere across the open. Now that's, that's becoming a lot more challenging these days. So I think what we're doing is, is really doubling down on how we invest in that value exchange with consumers. So that type.
Data set can remain viable, but also using things like artificial intelligence and machine learning, um, algorithms to collect other data which we can, uh, use freely. So commonly, uh, before we deliver an impression in the programmatic ecosystem. That instances is called pre-bid cuz it's a bidding auction type arrangement these days.
So that's where we can really go. What is the mobile operating system or device or browser? Potentially location time. Many, many signals in there. [00:08:00] In addition to say the context of the page that somebody is, is browsing or the, um, the types of app categories. So once you feed that into a, uh, an algorithm, you can start to infer people's attributes, which is relevant and important for marketers and publish.
So that's kind of where we're, where we're moving our investment at the moment compared to how we all used to do it, which is basically collect as much data as we can on consumers and use it how we want and not really tell them what's happening, which is obviously not the way, uh, to behave anymore.
Absolutely,
[00:08:34] Kat Harwood: definitely a lot more important to use that privacy in the way you use data today. And it's definitely a focus for your organization and ours as well. And on that topic of, of Id, correct me if I'm wrong, I believe this is from your research, you say today 30% of inventory is without id, and by 2023, that number is set to drastically increase to 75%.
So, Said, [00:09:00] what's the importance of non-addressable or unknown idealist audiences and how can they be reached?
[00:09:06] Dan Richardson: Yeah, I think if we, um, if we look at that stat, 30% of consumers are unknown. That's a broad brush across the globe. What we really suggest is, is looking at your audience profile by. So how many people are living their day to day lives on a, an iOS or a Safari versus a, uh, Chrome or a Firefox?
Now that differs greatly, uh, across markets. So I'm sitting here based in Sydney, Australia, and we know that at least half of the population are, are on an. And only a small percentage of those people have opted in for relevant advertising or location tracking. But, uh, if you go to India, it might be 10% or less.
So it's really about sitting down and looking at data availability. So if we [00:10:00] look at how we put people into two different areas these days, they're either known or unknown addressable or non-ad address. Id available or not available. So I, I think that's a good way to look at how people are existing on the internet in terms of data availability.
And then you can start using technology to understand how much is it going to cost you to reach people, unknown environments versus unknown. And what is the performance? So whether that's your online metrics, like cost per click or cost per thousand, or conversion or what have. What we know is that from the past, I guess few years, uh, at least since intelligent tracking prevention 1.0 was introduced by Apple and Safari in 2017, which meant that any cookie that was deemed to be third party or foreign to, uh, a website, for example, was blocked.
What we know is that from that time, people have really focused on, you know, how can we bring in alternative identifiers, [00:11:00] which are more consent. Such as an email ID or a phone number id. So that's, that's been evolving. And for us, we, uh, have invested in, uh, connect id, which is our identity solution, which lives across our entire stack.
And that's based on, on those types of things, a consent based email. But to go to the heart of your question, cat, which is about the unknown or idealist audiences that is growing. So maybe it's 30%, maybe it's 50%, maybe it's even more depending on your target audience. There are some, some advertisers we work with where almost all of their customers are using iPhone.
It depends on the demographic. Uh, so for us, as, as I said before, yeah, it's, it's about, you know, how do we go into using things like algorithms and machine learning to infer someone's qualities, but without tracking them across devices and, and doing things which [00:12:00] consumers are, you know, maybe not comfortable
[00:12:01] Kat Harwood: with.
Yeah. That's amazing. Just listening to you talk how the use of data has really evolved over the years. You go from having too much to, you know, not having consent. Now we have consent, you know, and just really getting into the detail of the data that you have. So how does contextual targeting play a role for you?
[00:12:22] Dan Richardson: It's really interesting to talk about that. I think in last year working with the IAB in Australia, uh, we actually worked with them to produce a contextual targeting handbook. Now that was designed to address a, a growing interest in contextual, but also to explain how it's evolved. So we all know traditional contextual targeting.
It's based on categorizing the type of website or app someone's using. Or potentially, uh, looking at the content of the page. And that could be largely, um, language based content. Uh, and that's been used for a long time with regards to targeting or even [00:13:00] suppression and brand safety. What we're finding is that we've been able to use contextual data to help better infer people's age or gender or interests in combination with other types of programmatic data signals, and that's what we call NextGen audiences.
So let's pretend we're in a cooking class. And we've got some ingredients. Your biggest ingredient that you've got there. The first one, that is your, your known audience. So that's people who you know, the age and gender and interest of, cause they've been happy to tell you that. And they're registered to the logged in.
Number two, ingredient contextual, whether it's app or website. Number three ingredient would be other signals that you are detecting across, uh, the internet when you're about to deliver. So if you think of those as the ingredients, now you've got the mixing bowl. So the mixing bowl is where you pop them all in.
You're stirring them around. Could be a mixing bowl, or it could be a big purple blender if it's, uh, at Yahoo . [00:14:00]
[00:14:00] Kat Harwood: That's right. Let's use the purple blender, ,
[00:14:03] Dan Richardson: sprinkle a little bit of data science on top of that. Uh, so that's, uh, to be completely nerdy, a real time, uh, machine learning algorithm. And then you can start to infer people's age and gender and interest and, and be, be valid.
Those modeled or inferred audiences against your known audiences, but you can do so in real time. That's critical because you are not relying on fingerprinting or tracking people across all the, the different places they're going using things like a cookie. , which are obviously blocked by Safari and under scrutiny or maybe being blocked by Google, um, or a mobile advertising Id such as your Apple id fa or your Google ad id, which are also being a bit more scarce these days.
Mm-hmm. .
[00:14:50] Kat Harwood: Mm-hmm. . Yeah. It's really changed and thank you so much for that visual. I love that . I was imagining all the ingredients going into this bowl, getting a little hungry. We're talking about [00:15:00] cookies. Very, very cool. It's helpful.
[00:15:02] Dan Richardson: Snows too. You've got cookies, you've got uh, you've got blenders. Um, but let, let's be honest, you know, when, when you start talking about machine learning algorithms, uh, there's only a small percentage of people out there who are, um, gonna be tuning in and really, really listening intently.
Uh, it does put some people to sleep. So , that's when we need to try and explain things better. To ourselves and to consumers as well.
[00:15:25] Kat Harwood: No, it's so helpful. So who are the NextGen
[00:15:28] Dan Richardson: audiences? So, NextGen audiences are, uh, uh, people just like you and myself, except there's no, no identifier available. So when an ad is about to be delivered to them, there is.
No cookie, there is no ad id, there's no registered, uh, logged in id. There's just general behaviors which are, um, being tracked. As I mentioned before in my Purple Blender example, it's just the same except they're, uh, obfuscated, if you could use that word. And that's growing, as I mentioned, across, um, different environments.
Apple for
[00:15:59] Kat Harwood: sure. [00:16:00] Absolutely. And I, I feel for consumers listening who don't work with data every day, but are obviously using their iPhones to surf the net or what have you, there's so much comfort in knowing what's going on presently with the use of data. It's such a safer place to navigate the internet and your phone and so forth.
So it's good to see the direction that we've taken everything.
[00:16:22] Dan Richardson: I think we need to, um, recognize that there are concerns and, uh, and consumers want more trust, control, choice. Uh, that's something we've tried to make really easy, um, with our, um, consent dashboard and, you know, letting people opt in or opt out.
The key thing is to recognize that we also as, as consumers and people, We all enjoy free content, ad funded content, so that does require, um, some form of identity or technology to be applied there. So we, we really do need to find a middle ground that allows that to thrive as well. Um, there's great [00:17:00] publishers out there ourself, but other, um, you know, global publishers employing journalists, producing great content now to thrive that needs to be viable across the open.
And, you know, not just housed within a particular operating system or wall garden, there needs to be room for both. So how
[00:17:17] Kat Harwood: do you use data to validate customer profiles and segmentation?
[00:17:21] Dan Richardson: What we look at before is, uh, as I mentioned, the people that we know and they do declare some data to us, age, gender, other things like that.
And that's what we validate all the other data sets, uh, against. Um, when it comes to segmentation, The focus is firmly on on first party data. For us, the big things which we're using is firstly the ability to match our known users to brands who are bringing their audiences into the platform. That's either directly in our UI or via integrations.
And to do that safely and to build on that, it's to enrich the view of that audience. So [00:18:00] maybe your brand that is coming into a platform and you know, the behaviors of an audience on your app or your, your website, you know a bit about them. What we can do at Yahoo is add on other attributes as well. So search.
Purchase behavior from the different commercial emails or receipts, which are coming into Yahoo Mail, which we anonymize and use for, for insights or targeting, what types of apps people are using, um, which you guys obviously know a lot about it at near, but for us, we, we see that through our owned and operated properties, but also through, uh, flurry, our mobile sdk.
So what types of apps are, are part of their daily. So to answer that question, custom or audience segmentation is really about adding on those extra. Unknowns for a brand or publisher, uh, that enriches their view and tells them something more, tells 'em something that they didn't know, um, which can help inform not just, uh, [00:19:00] a targeting strategy, but also their overall customer engagement strategy.
Or if you're a media agency, inform your writing of a brief. So yeah, it's really interesting. You know, when I started at at Yahoo about seven years ago, it was just target. Now it's all really about insights and working a lot more upstream, but that's more fun, right? Because it's not just about display banners anymore.
[00:19:27] Kat Harwood: Yeah, there's, there's so many more layers now to work with. It does make it more interesting. But with all that said, there has to be some problems here or challenges that you're trying to solve. So do you have any problems that you're trying to solve or questions that you need to answer when using consumer behavior data?
[00:19:45] Dan Richardson: I think the, uh, the greatest challenge, uh, and opportunity that we've seen is the emergence of new channels. So moving, uh, traditional out of. You know, glue and paper, uh, billboards into the [00:20:00] programmatic ecosystem. Moving from just people watching linear television to watching on connected TVs through subscription, uh, apps, which are starting to monetize like Netflix or Disney or, or other free apps which have ads in them.
So connected TV, digital outta the home. Uh, that's been really interesting because the data sets you're collecting there are. If you look at digital out of home, you know you're not delivering that into a browser or an app. You're delivering that to a screen, and then you need to understand at exactly what time and what radius or vicinity someone's device was passing by and dwelling where they exposed to that ad.
They need to bring that back into your identity graph and understand what was the result of seeing. In combination with your other channels video or in feed native display, and then what was the outcome? So that's been challenging, but we're really getting on top of that now and making that [00:21:00] part of the omnichannel piece.
And it's the same for, uh, connected tv, which is not a, uh, a one to one medium. You, you might have a household watching at, at the same time. So that's where we're using things such, uh, as looking at the devices in the house, the resting position and IP address, and bringing that back into to understand people.
That has been a challenge, but it's really actually starting to to work now and pay off because funny enough, consumers expect the same experie. They want you to, to get it all right. We want that experience. Yeah. Yeah. They, it needs to be relevant and even innovative, which we're finding with our work in augmented reality and object placement, um, for example.
So yeah, challenges and opportunities.
[00:21:49] Kat Harwood: Definitely it's, it's just the innovations in technology are fascinating to me and somewhat, almost magic in a way. Just, you know, what we can gather and infer based on the data that we have. [00:22:00] So has your organization used data to solve these problems in the past and to what result and or what would you have done in the past without having these data sets available and any big misses as a.
[00:22:14] Dan Richardson: Well, a lot of this data has, you know, not been necessarily available in the past. We've had mobile, uh, location and advertising IDs for a while. Um, we've had to do a lot of custom work to understand, as I mentioned, you know, who is in the household, who is watching connected tv. We're now, um, building on that to incorporate.
Television as well, working with, uh, partners like Cyber TV to basically telemarketer, uh, you know, how can they, uh, understand what is the incremental reach by buying connected TV video on top of your linear buy or vice versa, and how can you optimize that? So that is something which we've really worked on, um, developing, I think [00:23:00] in, in terms of, of.
It's hard to pinpoint something there, but the way we use data has definitely evolved. It's no longer a focus for us as a business to, uh, work with many, many, many different partners to just bring in cookie based audiences. That's getting a lot harder, and that's not where we're at. We actually, uh, have, have.
Um, have a few really solid partners whom we're, we're working on that are like-minded, who have first party data consent and help us, um, plug a gap or add value. If you skip back to maybe 10, 15 years ago, uh, and earlier in my career, I was helping, uh, run the operations of Acumen, which is a trading desk.
Um, at the time for Omnicom Group, it's basically like an all you can eat buffet and you can just choose whatever data you. From the internet, not sure where it comes from. Does it perform great? Does it not perform, turn it off? That methodology is is kind of out the window now and we really need to [00:24:00] curate those types of relationships.
So I'm not sure if that's a miss, but it's definitely something we've deliberately had to change cuz it's not working anymore.
[00:24:07] Kat Harwood: Interesting. Yeah, those partnerships are so important. When you find the right partnerships, you, you stick with them. With Yahoo being a consumer facing brand with a user base of 900 million globally, we are keenly aware of what's at stake here and how to keep consumers feeling safe and valued.
We know security is always on the minds of consumers. So how does data security play a role in the way you are using data at ya?
[00:24:32] Dan Richardson: Security is huge. And I think in, you know, we're, we're all facing new challenges, uh, at the moment, particularly with cyber security. Data breaches are happening to a lot of companies.
I think, uh, it would be silly of us to say that, you know, we're not, uh, a target. I think every, every big company, if you do have customer data is at the moment, we all have to act that way. Yeah. So it really is about being super diligent. Uh, One of the benefits [00:25:00] is whether you are a brand in our buy side or a publisher in our exchange, or a consumer on any of our properties or apps, there is only one Id.
Which we use, uh, and federate across the ecosystem to, uh, deliver advertising. We're not working with any third parties. We don't license technology to do that. In fact, we really don't rely on third parties very much to do this. So it means that there is a lot lower risk of data leakage. Uh, it means we can have a firm grasp of data security, um, for brands.
It also means we're not paying all these third parties who've got their hand in the. But let's go into consumers. I think where we've been really focused, uh, is to make their, their choices more visible. So instead of just, let's just go back to the old days, you'd have a privacy statement that said somewhere and a clause.
How do we use data these days? You can go to the Yahoo Privacy Dashboard and you can say, [00:26:00] here's what I'm comfortable with being, uh, collected or not used. Or collected. Here are my preferences, or maybe I wanna opt. Of everything now that you can do that with one click of the button, you know, we had that privacy dashboard.
It's really easy to opt out. And then we participate in a number of opt out choice, um, programs. I'm not gonna read out all the acronyms, but some people will recognize Nia or daa. But yeah, look, the final point I'll make is that I think as a tech company and publisher company, we have a responsibility, uh, not just to deliver better ads and creative, but to step up and own that narrative a bit more around privacy.
And consent. Cause at the moment, uh, that narrative is being controlled by three parties, so that would be your government or your regulator. And it would be Google or Apple. Uh, so the ecosystem's much bigger, so that's why we work with people like the IAB and different industry bodies to help surface better ways to
[00:26:56] Kat Harwood: do things.
When it comes to general data protection [00:27:00] regulation or gdpr. How will GDPR and enhance user privacy impacts the world of digital
[00:27:07] Dan Richardson: advertising? Well in, in apac, it's, um, been a little bit different. So if you're listening in Europe or different parts of America, you'll be under different privacy regulation.
There are updates to general data protection or personal data, how it's defined and used, particularly in markets, uh, like Singapore. There's changes happening in Malaysia, Indonesia, every market is, is different. The general movement is that as an organization, if you are collect. A data signal. And that could be things like a, a personal, traditionally defined personal, uh, information, like an email, a phone number.
It might be, it might be your, um, mobile ad ID on your phone or an IP address, uh, if you are collecting a data signal. And it can be, it can be mapped or bridged to another data signal or signals, and the user can be reasonably. [00:28:00] Then that is what's being regulated more strictly. And then there is, there is a very real possibility that those types of, uh, of data signals will become unavailable.
You know, we're, we're already seeing that, uh, around IP address. We're seeing that with, you know, your email identifier being removed by Apple. And, and so I think we're, we're all having to get used to, to doing more with less and having that really consent based first party data seed to model out from, and, and, you know, a lot of smart people are having to work a lot harder to, to get it.
[00:28:38] Kat Harwood: There's that, and you definitely have to get a little bit more creative with what you have. Um, and you've talked a lot about consumer behavior. I think this is a really good topic, especially because it's changed so much in recent years post pandemic. So what are some of the most significant shifts you've seen in consumer behavior in the last two years or so and how has it impacted your business?[00:29:00]
[00:29:00] Dan Richardson: Well, I think, uh, a couple of years ago when we all went into lock, That was a very interesting time to work in data and insights, um, because the way consumers were behaving really did change. So, and, and as the data person, we, we, we've always said, you know, past behavior is the best predictor of, of future behavior or future purchase.
Well, if you go back to March, 2020 that was all out the window. Yeah.
[00:29:27] Kat Harwood: No one's moving. Everyone's home .
[00:29:32] Dan Richardson: Exactly, exactly. So we were very lucky that we are able to understand, analyze data sets from within our, um, platforms, particularly from Yahoo Mail, which is, is really is a commerce platform for people to.
Organize and activate on their loyalty coupons purchases. Um, so that was fascinating to see the purchase behaviors, uh, So if you think back to that time, it might have been, [00:30:00] um, home office, or it might have been people buying, uh, trampolines or kids toys or entertainment at home. Yeah. Basically, and, and basic needs.
What was really fascinating is that we could see a rough translation of, you know, Maslow's hierarchy of needs coming. In the purchase behavior there. So people ticking off basic needs. So, um, food, groceries, getting their, you know, home office sorted, you know, making sure that everyone was okay. And then what we started to see past the first phase of lockdowns was more of a, uh, an increase in purchase around things that make you feel a bit better about yourself.
So if we're talking about, um, clothes or fashion or home exercise, that was really fascinating. What do we know about consumers and how things have changed? Well, in addition to traditional channels and emerging such, as I mentioned, digital at home or connected tv, uh, we're seeing a, a [00:31:00] really thriving, uh, cohort of people who are engaging with brands in virtual spaces.
For example, people who are in, in the metaverse or wanting to engage with augmented reality, activat. So the expectation though, as I said earlier, is that we deliver a seamless and innovative experience there. So it doesn't matter if you've just engaged with a virtual object, you know, maybe it's, um, a, a virtual can of Jack Daniels, which is something we're working on right now.
Interesting. Yeah. But once you've done that, you really expect that all the other ads that come to you knew that and anticipate your next need, so, That's a very interesting situation to be in. The consumer expectation is here, but data availability is ratcheting down. So in the middle there, we're working, we're working a lot harder.
You need a lot of ingenuity and you need to get in there and try and make things work. It's not as easy [00:32:00] as it used to be. It's
[00:32:01] Kat Harwood: not, and I mean you sort of, you touch on this, but you have, you had to do any extreme pivots to your business with these shifts that have
[00:32:08] Dan Richardson: happened. I think that the biggest pivot for us, And I've observed this over the past seven or eight years, being at Yahoo, was moving from a publisher to a tech business that started with developing an infe native advertising platform, which we called Gemini.
Uh, it meant buying other ad tech as well, you know, ad exchanges. Uh, we actually had 13 different sets of ad tech, which we had built, required, um, which needed to be migrated and merged into one single platform. Really hard considering you've got supply exchanges, all different things, and then one id, which you need to federate.
The entire ecosystem. Now, any publisher who has maybe bought another website before on a different domain to use a very simple example, [00:33:00] um, or brought people into their stable will understand how tricky it is to, to take people from very different environments and ecosystems and, and map them to one itd, but that's essentially what you need to do to deliver an ad in the ecosystem we're in.
So
[00:33:13] Kat Harwood: much goes into it. It's incredible. Okay, so let's talk about your customers, because I know you have a ton of them. With great use cases, how are you using consumer behavior data to improve your customers experiences? And can you give us some examples or use cases of how personalizing experiences for customers and why it's important?
[00:33:36] Dan Richardson: Yeah, I think as I said earlier, that the expectations have never been higher for a seamless or innovative experience. So one particular piece of work we've been been doing, which has been really fun, has actually been in collaboration with Tourism Tasmania and Stockholm Publicist Agency. I think for a moment where would be probably the coldest place to go in [00:34:00] Australia, in the middle of winter, uh, it's probably this tiny little island.
Right down the bottom, you know where the Tasmanian devil comes from. That place is incredibly cold, , but incredibly beautiful as well. I've been there a couple of times myself. It is just spectacular, especially if you love food or hiking or or wine. But you know, basically the mission was really how do we understand?
What people are looking for and where they wanna travel. So we actually worked, uh, with a number of different partners to try and get more people to visit Tasmania, but our biggest challenge was to get them to, to go down there in the middle of winter. Because we wanted to increase distribution of tourist dollars and spend and visitation in winter.
So what we did was we knew that we had to invest in a few big channels, particularly for tourism. So digital out of homes very important. We knew we were gonna use audio and then some high impact [00:35:00] display in Feed Native. Where we started was actually bringing in intelligence from the agency, Starcom, but also from JC to co the digital out home, um, partner.
We're working. Now they know a lot about where people go and, uh, who walks past their billboards and they can enrich their view. But the trick was to pass that into our ecosystem via our connection with Adobe, to profile them against all of our Yahoo first party data, to search purchase behavior, to find something new, to use that then to inform even better creative across, uh, audio display native.
Just to mention a few, uh, and then to drive a result. So what we're able to do is to use those insights to deliver the campaign, but then also look at who had been exposed to the media and then either been online or traveled. Down to, to Tasmania. So that's particularly interesting because we're looking at, for example, [00:36:00] someone who's gone past a a billboard, um, and then seen another ad.
Um, we connect that all with the, the mobile ad id, um, which we get from ourselves and match with ne. And then what we're able to do is actually understand that we saw about 51% of people who had seen these ads actually travel to Tasmania in the off. In the middle of of winter. So we observed that and they were five times more likely to visit a tourist attraction compared to regular audiences.
And they're also 87%, uh, more likely to visit the website for Tourism Tasmania as well. So we have what's. We call air as a, a really solid online to offline journey and a great partnership as well. So that's really fun and I think it ticks the boxes for consumers and brands.
[00:36:53] Kat Harwood: Absolutely. What a fascinating use case and really interesting how you can couple that online and offline behavior to come to these [00:37:00] conclusions.
I wanna go now to Tasmania. Sounds like a really interesting place. Dan, this has been such a great conversation. It's been so interesting to hear how you use data in your day to day and how it's really evolved with you from, you know, when you first started at Yahoo, to what's happened through the pandemic.
You truly are an expert in your field and a thought leader. So if you don't mind, I would love to know some of your data dos and data don'ts for our listeners out
[00:37:28] Dan Richardson: there. I think it's all about the quality of the data that you're working with, not just to be accurate, um, but also to have good governance.
You know, these days you really should only be working with a data set which has that consent baked in. Now that could be explicit consent from a customer or is compliant. You know, you, you really need to be on the side of the consumer there. I would ask anyone you're working with, you know, how are they guaranteeing that for you around governance and ethics?
We've moved beyond, uh, just [00:38:00] compliance with regulation. It really is about, uh, governance and ethics, um, as well. So once you've established that, uh, and you find like-minded partners who are able to enrich your audience view, uh, then it's about being able to apply that data. The entire internet. So that could be just working with a few select great publishers, but also testing, uh, identity solutions as well.
And the critical thing is, you know, you wanna achieve as much scale as you can, but make sure that you are a compliant. And look, the other part is to always, you know what I tell my team, always bring a perspective. Bring a point of view and lead with an insight. Uh, and that can help build big ideas and in turn do better creative experiences for customers.
And it's also a lot more fun. So, uh, they're my two things. I
[00:38:48] Kat Harwood: could see that. Yeah, definitely use inspiration to make those choices with data. Absolutely. Well, thank you so much. This has been a great conversation. I really appreciate your time.
[00:38:59] Dan Richardson: Thanks Kat and happy to be here and chat soon.
[00:39:06] Kat Harwood: Thank you for listening to this episode of The New World of Consumer Behavior. To learn more about this topic, check out the case study on our website. The link is in the show notes below. If you enjoyed the show, please take a moment to leave a rating and a review and tell a friend. This podcast was brought to you by Near, one of the world's largest sources of intelligence on people, places, and products.