100 milliseconds is not a lot of time, yet that is how long an auction for an advertising spot takes. With big data analytics, advertisers no longer have to choose randomly which spots to bid for. And as many examples show, intuition can be flawed: if you want to sell men’s deodorant, don’t advertise to a sports fan but to his wife. WBJ sat down with Piotr Prajsnar, CEO of Cloud Technologies, to talk about the real life applications and the surprising effects of big data in advertising
Interview by Beata Socha
WBJ: Your company claims to analyze over nine billion internet accounts on a regular basis. How can this huge amount of data be monetized?
Piotr Prajsnar: We got into Big Data after years of experience in data mining and internet advertising, an
industry that absorbs new technologies like a sponge. AdTech (Advertising Tech) has been around for over 10 years and in 2010 AdTech firms went through a revolution, by means of so-called Programmatic Buying, an automated auctioning system for internet advertising. The way internet advertising now works is as follows: an internet user opens a website and at that moment the browser contacts an auction system,
where an auction between different advertisers takes place. The winner of the auction is the one who is willing to pay the most for the banner at that moment and on that website. The entire auction takes about 100 milliseconds.
So how do advertisers decide which websites and at what times they want to advertise?
That is where we come in. We analyze over nine billion internet accounts and we gather data that makes advertising much more effective. We are a ratings agency for clients of sorts. We can tell advertisers which user is looking for a laptop and how much a given user is willing to spend. A banner displayed for that person is worth much more to a laptop retailer than to, say, a shoe store.
Advertisers would rather spend more on advertising but in a more efficient way, reaching people who are actually planning to spend money on products that the advertiser offers. By providing information about internet users, we bring order to the internet advertising ecosystem, which also makes advertising far less annoying.
How much do you know about the users you analyze?
First of all, we analyze devices, not people. Actual users are all anonymous. We analyze internet traffic on more than nine billion devices. We collect the data and then we analyze it. We create profiles, e.g. of people who visit automotive websites.
Before Big Data analytics, advertisers had to target their clients by advertising on themed portals, so a car retailer would advertise on a car portal. But knowing which car brands the user likes makes the ads way more effective. And we can provide that information. Still, we are not an intelligence agency and we do not record the data: we usually “forget” it after 30 days. Internet information is very transitory, anyway. The lifetime of cookie files, which we analyze, is about a week. After a month only a tenth of them “survive.”
Is data from social media more useful than scanning internet activity?
I wouldn’t say it’s more useful. Our data covers a much higher percentage of internet users. There are few places we don’t have access to. Social media, like Facebook and LinkedIn, protect their data. They may provide more “calorific” data, but they only cover a portion of the market. For instance, there are some 25 million internet users in Poland. Meanwhile, there are over 10 million Facebook accounts in Poland, and only some of them are active. You have no intel on the rest of the market.
Google is planning to incorporate an inbuilt adblocker into its next version of Chrome. How will that affect the advertising market?
In the long term adblockers could eradicate free content on the internet. Poland is the leader in adblock activity. Nearly 50 percent of website views is generated by people using adblockers. In Poland advertising spend per user is nearly PLN 150 a year. If advertising becomes ineffective because all ads are blocked, users will have to pay for the content themselves.
The advertising market saw the news of Google’s plans to have a built-in adblocker in its browser as a clear sign of monopolizing the market. What Facebook and Google are doing is strengthening their already monopolistic positions. The Interactive Advertising Bureau (IAB) is monitoring the situation and legal questions have already been raised.
Apart from advertising, what else are you using Big Data analytics for?
About 30 percent of our business comes from data consulting. According to Gartner, by 2020 approximately 80 percent of business processes will be automated. We are integrating with companies’ CRM systems and help companies improve their cross-sell and up-sell, as well as lower the client exit rate.
What kind of companies use Big Data in their business?
For instance banks, which can use Big Data to segment their clients better. Banks know what we buy; however, usually too late to benefit from it in any way. If you’ve already purchased a car, it’s too late; the bank already knows that the client could afford it. It would have been better to know about his purchasing plans sooner. If they had known, they might have offered him leasing options etc. Banks don’t want to call people up and offer their products randomly.
Similarly, you can help call centers get through to potential clients. If a call center calls you randomly, they will most likely irritate you. But we managed to use internet data to check when a client is viewing popular pastime websites. Because when they are browsing them, it means they have nothing better to do. That’s when you should call them.
Did that have measurable effects?
Absolutely. The percentage of people who took the call increased by 8 percentage points on average.
Still, many entrepreneurs and managers wonder whether the insights they get from big data are in any way better than intuition and experience. Why should they pay extra for it?
Intuition is good, but we use data mining to reach levels that cannot be accessed by intuition, to discover entirely new things. For instance, an airline’s media planner, in one early advertising campaign aided by Big Data, wanted to increase ticket sales to Italy and they decided to target the airline’s advertising campaign at businesspeople and people who are interested in travelling. That’s what his intuition told him was the right way. However, it turned out that the people who were the No. 1 client group at that specific time period were people interested in interior design. Perhaps it was because Tuscany was a source of inspiration for them, perhaps the destination correlated with their wealth. We don’t know why the campaign worked and we don’t need to know. The media planner was good but the machine was better.
There’s another example: a popular men’s deodorant brand decided to target men interested in sports. Our analysis showed that it wasn’t men but women who most frequently bought that deodorant. The guy interested in sports has a beer in one hand and the remote in the other, while his wife – in an act of despair – would buy him the deodorant.
The Big Data market is growing at a much faster pace than the entire IT industry. Is this growth supported by actual increases in productivity of companies using the technology?
We are indeed growing much faster than the average for the market. That’s because the saturation of Big Data solutions in the market is still very low – it’s still a very fresh market. Even if we can improve efficiency by a few percentage points, it brings a lot of extra profit and savings. In internet advertising, using Big Data can increase a campaign’s effectiveness two or three-fold.
Are Polish companies open to Big Data?
It depends. Innovation is not always embraced easily and many firms still consider it risky. The Polish economy has many growth drivers. In more developed economies being more competitive is much more important. Our economy still has a way to go before it reaches that stage. It’s like with Maslow’s hierarchy of needs: Big Data is right there at the top, and we are still somewhere in the middle. Highly advanced technological solutions come later.
Is that why the majority of your revenue comes from abroad?
Yes, some 80 percent of our revenue comes from markets outside Poland. Our clients are media houses, advertising agencies and affiliation networks. In our data-consulting segment we work with large B2C businesses: telecoms, banks, insurers and multimedia companies.