In today’s experience economy, awash in data, there’s no reason that marketers shouldn’t be able to deliver personalized brand interactions across every channel and touchpoint.
Acknowledging this new norm, major ad agencies are beginning to offer sophisticated data tools to help clients identify and execute these personalized consumer experiences at scale. At least that’s the promise.
What’s their secret? Artificial intelligence, big data analytics, and optimized actions.
Here’s how ad companies are bringing business intelligence and analytics to their core offerings, empowering clients to create more relevant marketing messages that connect better and deliver more sales.
Take a look:
Omnicom Group uses a “robust people-based identity graph” to profile customers, and predict what kind of information they want to see from a creative and messaging standpoint. For example, an automotive company could pull data and find individuals who are interested in electric vehicles. The identity graph may determine that people who search for electric vehicles tend to share behavioral traits, like caring about the environment and DIY projects. From there, clients can pull a number of actual videos that the audience is viewing across the web, and extract colors, images, and language the videos have in common. This process provides clues about what visuals resonate with that target consumer and aims to improve engagement and conversion rates.
The Interpublic Group of Companies (IPG) is putting an emphasis on “clean, ethically sourced data”, meaning all the consumer consent boxes have been checked — a high priority in the post-GDPR age. The goal is to help companies build trust with consumers, not just by using clean data, but by serving up relevant (and hopefully well-received) marketing messages. In another auto-themed example of using data to inform relevancy, a car company recalling a vehicle could block ads from being served to a consumer who already filled out a recall form. “That has a tremendous amount of impact on a brand’s equity and can make the difference in how people see your brand as being a trusted brand or a brand that makes claims but doesn’t complete them,” says Arun Kumar of IPG.
With the same objective to target consumers on an individual level, Publicis Groupe’s Digitas worked with Lyft to promote its Round Up & Donate program, which allows riders to donate their fare difference to charity. Using a machine learning platform that collects and analyses mobile-data signals (such as the apps people have on their mobile devices), they identified consumers with both rideshare apps and charity apps on their phones — then, they targeted people who were most likely to respond to the campaign’s in-app video ads.
Clearly, there’s a lot of work that’s being done to perfect ad targeting, and ad agencies are pouring tons of money and resources into the data tools necessary to deliver these experiences.
Compliance is still key though. If consumers are served marketing messages without their permission or consent, that could spell trouble – even if those messages are relevant or timely.