The term “people-based marketing” was coined one year ago at AdWeek. A year in, this much is certain: Successful people-based marketing depends on recognizing, in real time, that “Jane” who researched your brand on her smartphone is the same Jane who comparison-shopped on her laptop and is now browsing on her tablet or in your store. These are the big challenges facing advertisers and publishers today: customer recognition, speed, and scale.
Cross-channel identity is everything: It’s what allows you to deliver content and messaging that is timely, relevant, and personalized—earning loyal readers and converting shoppers into buyers.
Recognizing your customers depends on collecting enough data to solve the identity puzzle, and piecing together the necessary information fast enough to know them in real time. Achieving recognition, speed, and scale is difficult. Unless you’re Amazon, achieving all three while maintaining control of your data assets is borderline impossible. This is due to a multitude of reasons, not least of which is the very technologies publishers and advertisers depend on to collect their online and offline data.
Slow and Disconnected Technologies
The process of recognizing the consumer is complicated by the large and ever-growing suite of technologies that publishers and advertisers rely on to support the aggregation, onboarding, management, and deployment of customer data.
According to recent research from Signal and the Winterberry Group, brands employ upwards of 12 different tools to collect and manage their data. And some big brands use as many as 30 or more. These tools include:
- Ad-serving analytics
- Campaign management
- Data management platform (DMP)
- Data onboarding
- Demand-side platform (DSP) or supply-side platform (SSP)
- Email service provider
- Social media tools
- Web analytics
- Website content and personalization
Integrating these technologies is difficult. Each has its own language, its own way of identifying individuals, and they typically don’t talk to each other. This makes it tough to recognize today’s multiscreen consumers and reach them with the kind of timely, personalized content they have come to expect.
For example, onboarding offline data from your CRM system for more accurate online targeting is traditionally a cumbersome batch process that can take as many as five days, or longer, a timeframe that’s far too lengthy when you’re trying to engage people using your your web site or mobile app right now.
Even if they resolve sluggish data-matching and disconnected technologies, publishers and advertisers still struggle with the issue of scale. And that’s where data sharing comes in.
Scaling Your First-Party Data with Trusted Partners
Most brands lack the sheer volume of data necessary to consistently recognize their customers across all their devices and channels. In recent years companies looking to scale their first-party data turned to Facebook or Google, but working with these “walled gardens” means surrendering their customer data while getting only narrow campaign-centric metrics in return. Brands don’t receive the customer insights they need to close the loop on their analytics or develop rich profiles of their customers.
An emerging alternative to walled gardens is data sharing. Publishers and/or advertisers can form a cooperative identity network with trusted partners to share anonymized data in a secure and privacy-compliant way. Data sharing allows companies to work together to better match the scale of mega-retailers like Amazon and Wal-Mart, giving them a more complete picture of their customers without having to surrender control of their assets to a walled garden.
How does this work? Say Brand A has interacted with Jane on her mobile device and work computer, while Brand B has done business with her in a brick-and-mortar store and on her home computer. Brand A and Brand B pool their knowledge, sharing anonymized data related to Jane, and as a result they are now better able to identify her across her various channels. Pairing identity with each brand’s proprietary knowledge of Jane’s buying habits and interests, Brands A and B are now both better able to provide timely, personalized messaging and offers to her, improving Jane’s experience.
Streamlined for Fast Execution
The good news for marketers is that Signal integrates first-party data collection, cross-channel identity resolution, data onboarding and activation capabilities into a single platform for targeting and media activation. With one data taxonomy and zero hand-offs between vendors, Signal simplifies and streamlines all of these processes to collapse the execution from as much as five business days to a matter of mere minutes.
All of this happens in real time. How fast is that, exactly?
- The Signal platform offers cross-channel data collection, recognition and distribution to DSPs/SSPs in just 50 milliseconds.
- Signal can onboard 1 million records in less than 30 minutes
Other point solutions simply aren’t built to collectively address these challenges; they can’t be customized to keep up with always-on consumers.
And marketers can rest assured that Signal’s platform was built with privacy by design, enabling brands to safely and securely share first-party data while always adhering to privacy best practices.
Today’s consumers move quickly, and you can’t afford to wait for days to match cross-channel data. Fortunately, you don’t have to wait any longer. And you don’t have to give up your data to an Internet giant to reach authenticated customers at scale.
Download our ebook, First-Party Data: The Marketer’s Secret Weapon, to learn how Signal empowers brands and publishers to leverage their own data for real-time, people-based marketing.