If you are considering becoming a 1M/1M premium member and would like to join our mailing list to receive ongoing information, please sign up here.

Subscribe to our Feed

Thought Leaders in Big Data: Martin Smith, SVP, Ad Platforms and General Manager, TruEffect (Part 4)

Posted on Saturday, Jan 19th 2013

Sramana Mitra: What do you see as open problems or white spaces? When you look at your customers, what advice would you give an entrepreneur as to which direction to steer?

Martin Smith: There are a lot of solutions in the space that are called point solutions. I see opportunities for people who are able to bring those point solutions together in an efficient manner. I think the big white space for the industry is not focusing on performance, where a lot of investment dollars have already been brought in from the market, but focusing on the cost of performance. Developing tools, technologies, and capabilities that eliminate what we call the non-media overhead. From an entrepreneurial perspective, the opportunity is not to build a better mousetrap, but rather to figure out how to make the mousetrap significantly more efficient. Those are the areas where I think we are going to see tremendous developments.

The other areas people need to be working on relate to the massive proliferation we are going to see in the multiscreen environment. That is not just in comprehending desktop and mobile, but also comprehending IPTV and other areas. We have now an addressable digital footprint across all our devices. We have to learn how to be relevant to consumers not only in terms of what devices they are on, but also how these devices are being used. For example, somebody using his or her tablet in a hotspot when on the go has different behavioral aspects than if that same person is at home watching ESPN. Then a person is very much in entertainment mode. The challenge is in the way to make [ads] available and make them efficient. At the end of the day, we are all competing for a finite amount of ad dollars being delivered to a finite number of people.

SM: What are your predictions based on what you see in terms of your application of big data on advertising? What are your top three predictions for the year?

MS: I think what we are going to see next year is a radical [change]. As of December 25, 2012, we had around 110 million phone and tablet devices worldwide made available – we have a multi-channel engagement model, and our employees in the advertising space are going to come back to the office for the New Year and figure out how to be relevant and engage with new customers in this new world. I think there is a substantive shift that is going to happen in that side of the space. I think as an industry, people are relatively unprepared for it. That is probably going to be the biggest issue in 2013, and I hope that it will drive an  understanding of how to measure effectively in those environments while considering the underlying trend that we are also seeing, which is the increasingly empowered consumer. This is a trend we have been watching and trying to comprehend. I think that is also an area of white space that is going to be addressable by different companies.

SM: Is there anything else you would like to add?

MS: I think we could add a third element to that. In 2013 or 2014, we will start to see a substantial implementation of what we call data-driven addressability. This is one of the powering elements of big data because we are able to break down audiences into micro segments. We are starting to see a bit more of that. I think it is more than just conceptually achievable. There is an increasing capability to be able to do it, and to react to it with dynamically rendered content.

It has been feasible for the past five years. What we have not seen yet is a real understanding of the data aspects. I think there is a view in the industry that, “If you throw a lot of data at it and spend your time building massive amounts of profiles then you are going to be successful.” This model is incorrect. There is going to be a significant price adjustment – that seems to be a valid statement. I also see that the trend of the increasingly empowered consumer will eventually lead to the better management and choice by consumers about what data is being used and shared about them. There will be both legislative and commercial implications.

I think we have to start with what we call relevance. If you just build a lot of inferred profiles about people, it is technically interesting but commercially ineffective. However, when you are engaged relevantly with people who you have a relationship with, you can communicate more effectively. Between 60 and 80 percent of your sales will come from 20 percent of the people with whom you have a relationship. Therefore, it is a commercially incorrect place to start building 80 percent of the profiles against 20 percent of your revenue. I can give you a simple example. Every month I pay my credit card bill online, and then for 15 days I receive ads for a product I have owned for 15 years. It would be better to go from the inside out instead of starting from the outside and working in. That is one of the lessons that could be learned in this space, because it is a kind of reverse mathematics.

SM: Thank you very much, Martin.

MS: Thank you. It’s been a pleasure.

This segment is part 4 in the series : Thought Leaders in Big Data: Martin Smith, SVP, Ad Platforms and General Manager, TruEffect
1 2 3 4

Hacker News
() Comments

Featured Videos