CO-FOUNDER & CEO, EYEOTA
Kevin Tan is an accomplished entrepreneur and advertising industry technology leader with over 20 years of experience. Born and raised in the U.S., Tan moved overseas early in his career and has spent most of his time building successful global businesses in China and Singapore. Tan is the co-founder and CEO of Eyeota, the global leader for audience data in APAC and Europe. In 2016, Tan relocated to New York to launch Eyeota in the U.S. market. Prior to starting Eyeota in 2010, Tan was among the leadership team at Adify, which was acquired by Cox Enterprises in 2008. Tan’s other notable positons include VP, advertising sales and sponsorships for Viacom/MTV Asia-Pacific; CEO/Founder at iamasia (the leading internet audience measurement company in Asia); and managing director at Taylor Nelson Sofres China. He has also worked for AC Nielsen and has consulted for leading international digital marketing, advertising, market research, and audience data companies. Tan is a graduate of Duke University.
I have been involved in data since the beginning of my career. I started as a consultant, then moved into market research and into online data and the audience measurement side of the business. Later, I became involved in media, then advertising and ad tech. The latter brought me back directly into data, particularly as programmatic and audience-based targeting started.
It is exciting to see how data plays a part in everything, allowing decisions to be made much more quickly and semi-automatically. Data adds to the vast number of signals that can help make decisions. This is why we see a rise in artificial intelligence and automated systems—data allows us to use simplified and easy ways of giving instructions to digital systems. There has been an increase in voice-enabled systems, and voice will ultimately control most devices as the technology around it progresses. Voice-enabled systems are made possible by the amount of data that we have and that we’re collecting—we will see a lot more developments around this.
We see an intersection of an increased use of data for advertising, marketing and decision-making in the digital world—for example, ads based on previous behaviors, machine learning or based on a range of different data signals—with an increasing awareness by consumers that their data is being used to make decisions. In some cases, such as Netflix’s recommendation engine, this is interesting and helpful. However, for others, retargeting is scary and something many are not comfortable with it because of its aggressive nature.
While consumers like helpful suggestions based on data, they are not fully comfortable with using data to make decisions. The concern over decisions made by data and the ability to make more decisions with data are also intersecting. This brings us to a point at how we are looking at media. Media and its products and services have been fueled, empowered and paid for by advertising. That inherent contract between the consumer and the publisher or the provider of services meant that consumers would get that service for free based on the right to receive ads. Some consumers think since they are paying for internet or mobile services, which they equate as part of the contract, they should get all the services for free. This mentality has risen as the internet matures and millennials and even younger generations come on board.
There is a conflict in the industry where consumers are using ad blockers to get better online experiences—either due to poor experiences or an excessive overload of ads and the technology being inadequate to service it. These ad blockers are removing the ads from the publisher or content provider’s site, and they are not getting paid for their content. This will force them to go out of business, which will, in turn, decrease the amount of content available for consumers.
Here is where the opportunity exists – to redefine the value of the relationship between the consumer and the publisher or content provider. We are headed for several rocky years of clashes and will get to a point where we may see a demise of publishers we’ve known for years while consumers become familiar with the value proposition.
Prior to co-founding Eyeota, I ran international operations for an ad tech business called Adify, which created vertical ad networks for premium publishers. During this time, we saw an evolution of publishers moving from buying ads based on traditional styles of audiences to more sophisticated methods targeting certain content or sections. This drove the rise of vertical ad networks, and Adify allowed publishers to build out bigger ad networks of content from smaller sites and blogs and sell them alongside their main vertical of content.
Around that time, my co-founders and I saw the ability to target specific audiences and buy individual ads one by one through real-time bidding and auctions. This real-time bidding emerged into what we know as programmatic advertising and it changed the landscape dramatically. As we looked at the evolution of the industry, we saw a few companies already doing audience targeting in the U.S. though it was still very nascent. Outside of the U.S., the market was wide open and there would be an opportunity for this audience data. With my international experience and a team across the globe, we knew the digital market, publishers and advertising buyers very well. We knew better than anyone how to build and deploy technology that would allow us to collect audience data and provide it to the digital ecosystem. Thus, Eyeota was born.
We began to collect data locally and market by market. It posed numerous different challenges but it was very interesting. The ability to target audiences changes everything—from the way to place an ad or content to how you provide information. You now have these signals to make everything automated and you have central intelligence, or artificial automated intelligence, behind everything. We knew being able to collect this data and pull in this data was key to that.
Providing data into specific channels, programmatic advertising, the digital marketing ecosystem, or even financial models—this is just the beginning. Data is the essential building block behind everything. We are going to continue amassing more data and as we do so, we can do more things with it. We can provide it into more systems and drive more of the ecosystem. We have managed to do this outside of the few of the largest publishers that are continuing to dominate in their closed ecosystem, and we are collecting data outside of those systems and providing this data to everybody. That neutral data collection at the scale we are collecting is exciting. The vision we see is that we are going to continue to collect more data and become the independent data supplier and source of intelligence around audiences and what they like to do around the globe.
We have been in the U.S. market for a little under 18 months and it is already providing a substantial part of our business. That is in part due to the U.S. being the biggest market for audience data in the world and also to our pre-existing relationships with the biggest players in the world. We work with all the major technology companies, such as Google, AppNexus, Turn, MediaMath, The Trading Desk, AOL, among others, as well as all the media agency groups, such as Publicis, WPP, IPG, Dentsu, Aegis Network, and others. We also work with all the major brand advertisers. Since everyone knows us from our work internationally, it’s been relatively easy to enter this market.
As we continue to grow in the U.S., Europe and Asia-Pacific, we are in a unique position that covers the globe. The globe is not a single market—it’s made up of many different markets with different consumer behaviors and different types of data. There is a reason that even big consumer packaged goods companies do not sell the same product with the same brand and the same chemical mix in every single market. People are fundamentally different. We are tuned in to this in our ability to collect data on a very local level to understand different people, their likes, dislikes, habits and more, and provide it back into the global digital ecosystem.
We allow marketers and advertisers to have a single source of global data to make differentiated decisions in each market based on cultures, populations, buying behaviors, preferences and more. We will see the ability to expand on this and work with brands at a global scale. Not only do we pull in data signals from online and mobile sources, we also work with offline data, such as data from research companies and offline customer records and the like, and activate it in a digital world.
There are few companies that do what we do. We have built our system to be compliant with the strictest privacy laws and regulations across Europe. These laws make it difficult for systems that work in the U.S. to be exported internationally. The way we have built our system is differentiated and allows us to succeed on a global scale.
We have been working very closely with a lot of companies that collect a lot of data and have historically built consumer frameworks around customers globally for marketers and brands. They have years of taking data from market research studies, purchases or a range of things that are not necessarily digital, and have created models based off these insights. What we have done is take our knowledge of how these traditional market research and consumer insights companies work and merge it with the data we have around the globe—we’re connected to 3.5 billion unique profiles on a monthly basis.
This allows us to provide companies with new sources of data into their traditional models, as well as take the traditional models and frameworks and attach them to the digital world and activate them. We can take systems and models that have been built for decades and make them relevant and actionable in this digital, data-driven, AI-driven economy. It’s at the forefront of where marketers are going and we’re right there with it. It’s exciting for these companies, for the media agency groups taking frameworks they are familiar with and adapting it to this world, and for the brands because they can now do more things globally at scale and digitally.
In the early stages of our development, between our beta and full production launch, we built an early version of the platform using a specific technology. It got us to market quickly but we realized that it was going to be expensive if we were going to scale our data. Then suddenly, we started scaling our data and we were selling our data. We had too much data and the cost of running this technology in the way we had built it also scaled massively. Pretty quickly, the cost was a lot higher than we wanted it to be because we became more successful than we anticipated.
We always had a contingency plan and we were getting ready to transfer. But we had been so successful with data acquisition that the data kept growing rapidly and the cost of maintaining that growth was tremendous, forcing us to speed up development of the longer-term solution. Before we were able to transition to a new system, we ended up having to go for six to nine months beyond where we would have liked because it was costing us so much to collect and house all that data.
This taught us a valuable lesson. You always have to think four to five steps ahead. The moment your gut tells you to put a contingency plan in place, you should execute on it. Hopefully, you are wrong and you get excess coverage. If you are right, things will get timed perfectly.
The ideal experience for a user of our data is being able to find the data they need to target their advertising or marketing experience to the right customer in the right environment at the right point in their purchase cycle or to achieve that sale or that increase of awareness or another objective.
This happens every day for us. It is a matter of getting the right data and making sure that data is available on the right platform. Oftentimes, a brand or user of that data will want to deploy a campaign across multiple platforms. Having the ubiquitous distribution that we’ve built up, and will continue to build as more platforms arise, is exactly the ideal experience for a customer or a client.
We also work with publishers and data owners. The ideal experience for them is to help turn their valuable audience base or the data they put together into something that can be deployed everywhere—distribution is key—and monetized.
Motivating people is always challenging because the time when it is needed is when times are tough or when you are trying to get someone to do something not naturally intuitive, which can seem frightening or intimidating.
You have to inspire people. Work with them and show them ways to overcome and address challenges or fear. Part of that is enthusiasm and excitement, but also a rationalized approach. Allow people to voice their concerns, get a sense of why people would not be necessarily inclined to go towards a certain direction. Allow them to put those concerns on the table and talk it through. Give them a rational explanation or example of why it might be good and show how it can be done.
Our industry is in a constant period of change and flux, and I don’t see that changing any time soon. Technology is advancing, the use of data is advancing, the use of math and science is increasing, and consumer behavior is also rapidly changing. We are already seeing a differentiation in how consumers adopt information, how they are influenced, how they use social networks and how they communicate with others.
For those in the industry or want to be in the industry, my advice is to always learn and always be willing to learn. You have to constantly approach life in that perspective. The ability to absorb and embrace change and to be flexible in approach is the key to success.