Connecting the Dots At I-COM Global Summit This Year
Paul MartinApril 19, 2016
If we create about 2.5 quintillion bytes of data daily and so much of that collected data is kept in separate arenas, just think how powerful that data could be if it were combined.
Data is utilized for all sorts of reasons and lives in different silos. How can we better integrate that data together to leverage more value for our clients and ourselves?
This is why Xaxis plans to deep-dive into this topic at this year's I-COM Global Summit which started yesterday in Seville, Spain to discuss themes related to "Making Data Human."
Achieving Business Advantage With Data Marketing and Measurement
In the past, delegates gathered from around the world to discuss, network, and learn about the future of data and the power it holds for us today. Last year at I-COM, Xaxis introduced Xaxis Sync, a product focused on combining TV viewing data with digital media intelligence to help advertisers send messages to second screens that reinforce what consumers were seeing on TV.
This year, we will unveil products to further bridge data silos by facilitating new segments that incorporate survey insights with behavioral and purchase data, then use look-alike modeling to achieve meaningful, targeted scale.
Trying to activate those surveyed customer insight segments to date has been impossible. Now, we can integrate slower moving data segments and support them in new ways by mapping them to faster moving programmatic platforms.
At our I-COM round table, Connecting the Dots: Better Sharing of Insights to Drive Performance, we explored ways of wielding data throughout an organization. For instance, media organizations have a wealth of information infused throughout them—"fast data"—that's used to optimize advertising on programmatic platforms in real-time. However, that data can get lost if not organized efficiently.
Harnessing the Power of Data and Measurement
In programmatic, segments have typically been created by using demographic profiles as proxies for intent, like fashion-forward women ages 25 to 34, retirement-minded Baby Boomers, higher-income Millennials, and so-on.
Meanwhile, market research yields customer insights that, when combined with the right platform data, can build highly effective target groups that cut across gender, age and demographic lines.
There may be a segment called 'fast fashion' for style-conscious consumers, another called 'functional fashion' for people who simply want clothes for work. Overlaid with the right data, we might find that each of those segments spans different ages, genders and even levels of affluence.
Those individuals will welcome messaging that's in line with their actual preferences and behaviors more than ones based on a less precise grouping made from demographic assumptions.
What if we could combine those “fast" and “deep" data to help advertising effectively activate people toward marketing goals and combine the platform data with information gathered separately through surveys as well as and other sentiment-gathering methods?
The result of connecting those dots is sure to be powerful.