Digital Advertisers Bought More Varieties of Data in 2016
There's an incomprehensible amount of audience data flowing around the digital ad market, and a new report suggests advertisers are investing more money to layer data onto their ad buys. They're selective about it, though.
In 2016, for example, CPG and retail brands sought after consumer profile data about urban families. Compared to other types of advertisers, more automotive, telco, retail and finance advertisers bought audience data showing what brands people own or are interested in. And half of the data representing b-to-b audiences was bought by electronics and computer brands.
According to Eyeota's 2016 Annual Index Report, there was a 66% overall increase in the use of audience data for digital ad campaigns in 2016 compared with 2015, based on the digital data firm's view of the global market.
Financial services advertisers were the most data-hungry vertical in 2016 globally. Finance advertisers bought nearly 2 times as much data compared with the 2016 average, up from around 1.3 times in 2015. Insurance brands, for example, doubled their audience data investments in 2016 compared with the previous year. The financial sector's advertisers want to reach audience segments representing people with money: high-income families, young and urban professionals, people living "luxury lifestyles" and audiences who have exhibited an intent to buy financial services products.
Growth in data spending and use represents the volume and density of data employed to target digital ad campaigns, said Kevin Tan, co-founder and CEO of Eyeota. The number of data types advertisers are buying to craft customized targeted audiences is on the rise, he said, noting they are "using a combination of [demographic segments] and other segments around interest or intent."
The top five audience-data-buying advertiser verticals were finance, electronics and computers, retail, automotive and travel, according to the report, which analyzed data spending by 2,400 brands in more than 60 countries.
Retail advertisers tracked by Eyeota bought less digital data in 2015 than the average, but boosted spending to 1.6 times the average in 2016. They wanted to target consumers based on their intent to buy, aiming ads based on data showing interests in technology, food, fashion, home and garden products and apparel.
Digital data spending by food and beverage advertisers grew by 3.6 times in 2016 compared with the previous year, and luxury vehicle advertisers more than doubled their spending on data informing audience targeting last year, noted the report.
More advertisers appear to be targeting audiences based on brand affinity, or data showing what brands they like, own, or aspire to own. This type of data typically is derived from a variety of places, such as search data or behavioral data showing visits to brand websites, for example. According to the report, advertisers spent 2.5 times as much on brand affinity-based audience segments in 2016, with auto, telco, retail and finance advertisers leading the way.
Demographic data is still king, though. Eyeota reported that 26% of the audience data purchased by advertisers represents basic demographic data showing gender, financial status or ethnicity. Sociodemographic profile data in categories such as "liberal opinions" or "financially savvy families" represented 18% of data demand. Sixteen percent of demand was for interest-based data showing the types of things that appeal to groups of consumers -- like music, fashion or gambling.
Eyeota builds targetable consumer segments for ad exchanges based on data it gathers from 30,000 publisher partners and data providers such as Experian, Kantar Media, MasterCard and Sharethis. Eyeota got its start in Asian and European markets and expanded into the U.S. last year; it says it tracks data on 3.5 billion unique users each month.
The report, said Eyeota Director of Insights and Analytics Jessie De Luca, reflects the amount of revenue generated from the ad-related data flowing through the company's system. Partner data, she said, "floods through our pipes so we can have access to their data…. We check all of our trends with their trends."