After the recent acquisition of [x+1], Bridget Bidlack joined the Rocket Fuel team to help build toward our vision—a landmark Marketing That Learns™ platform that learns from first- and third-party data to make marketing conversations progressively more relevant. A seasoned ad-tech veteran, Bridget oversees product management of Rocket Fuel’s Origin platform and works on product positioning and defining and executing an aggressive enterprise product roadmap.
Nobody knows that technology can control the consumer journey better than Bridget does. By customizing campaigns to the individual, and managing lifelong relationships with consumers, marketers can be more efficient and effective than ever before. Here is Bridget’s full Q&A with Adweek after being named of the publication’s “12 Stars of Ad Tech Who Are Building the Future of the Industry Right Now.” She outlines which trends will shape the future of marketing, and how–no matter what–Big Data and predictive modeling will dominate the conversation.
Q: What are four major trends we are seeing in ad tech?
A: Rise of cross-device targeting: Marketers want to focus on targeting audiences without having to use multiple vendors. With the recent evolution of cross-device tracking, many vendors now offer the ability to reach audiences across desktop, laptops, tablets, phones, game consoles, and more. This holistic approach will continue to evolve—and soon, marketers won’t be thinking about whether they are reaching audiences through a device ID or a cookie. Instead, they’ll be focusing on the ideal audience and the appropriate creative treatment to reach them. To do this, they’ll factor in several elements, including:
- Real-time context: This includes delivering the appropriate ad size and interactive elements to match the device type and screen size.
- Time of day: This ensures that the right message is delivered depending on whether it’s business hours or non-business hours (people have different behaviors during these timeframes).
- Location: The offer should be different depending on whether a person is at home, work, commuting, shopping, or on vacation.
Redefinition of programmatic beyond RTB: Open RTB allowed marketers to dabble in programmatic. Now marketers and agencies are expanding programmatic beyond RTB and into their direct/guaranteed buys. Doing so gives marketers the convenience of operating out of one system, standardizing campaigns across what would be traditional direct buys, private deals/private marketplaces and Open RTB with holistic campaign management—shared budgets, tactics, pacing, and frequency across their entire campaign. This allows marketers to negotiate deals directly with publishers in a programmatic way. This complete campaign view is also one of the primary reasons for the exponential growth projections for mobile programmatic and programmatic direct.
The Rise of Mobile Programmatic: We’ve all seen the projections that programmatic mobile spend in the U.S. will surpass desktop next year. The reason is that finally we have systems in place to capitalize on the contextual richness of mobile data. For all the talk about the consumer journey, mobile is the only medium where we take that journey with the customer; it’s an unprecedented view of who the customer is (and where!), which means that systems can decide, with great precision, if this consumer is the most likely prospect from the most desired audience. Programmatic is also permeating digital video, and as spend continues to grow in this area, so will the proportion of programmatic buys across devices.
Smarter data collection and normalization: Using many different platforms means many platforms have to tag sites for data collection and attribution recognition. This continues to be a battle between marketers and IT teams. Marketers often face long queues to get tags implemented with their IT teams, then once implemented, problems arise which are often difficult and time-consuming to troubleshoot. This can lead to campaign delays or campaigns that run without accurate data collection and reporting. Some marketers have adopted tag-management systems, which solves the operational headaches. Some tag-management systems are adding DMP-like features and vise versa (DMP are adding tag management-type features). The goal of the TMS/DMP hybrid is to take advantage of the operational efficiency by passing data into a platform that can then make it actionable for targeting and reporting.
Q: What do you consider the most exciting opportunities in the space?
A: There has been a lot of recent advancement in the interoperability between platforms. This is important for agencies and marketers that often use different platforms for different parts of their business. They often need one source of truth where everything comes together—whether that’s for centralized data collection, audience management, or attribution. Many of the agencies and marketers I’ve talked to lately aspire to have a true universal frequency across all their campaigns. Using a DMP that is truly real time allows users to centralize this data; however, many of the buying platforms are still years away from being able to ingest this data in order to make it actionable in real time.
The evolution of persistent ID’s has been a game-changer for the industry. Through persistent ID’s, systems can match a customer or prospect using device ID’s, offline data, cookies, online registration information, household data, and more, across a marketer’s CRM key and partner identifiers. This means that when a brand is interacting with someone, they can recognize the same person wherever they are, and on any device and browser.
Often, brands have enormous amounts of data about their customers through loyalty programs, website browsing, and shopping behavior. This first-party data can now combine with online and offline third-party data. The desired segment is created, and the audience can be reached through traditional offline and online channels. Additionally, more data sources than ever are now available for “look-alike”/”act-alike” modeling and performance optimization, which brings deeper and more powerful insights to the marketer. Because the persistent ID is also matched to some of the largest publishers in the industry, marketers can manage their audiences and make them actionable against publishers that have traditionally had “walled gardens,” a block that prevented a marketer from using his or her first-party data unless they did a one-off integration with the publisher.
All of this is bringing disparate marketing silos together so that brands can have progressively relevant conversations with customers and prospects across all channels. Marketers are taking an audience-centric view without worrying about the nuance of where and how they are reaching their audiences. Instead, they can focus on the interactions along the entire customer journey.
Q: What are you most excited about working on and why should other people be excited to?
A: At [x+1], I was head of product management. At Rocket Fuel, I’m head of platform product management and am tasked with converging the [x+1] and Rocket Fuel platforms while also bringing something to market that is way better than our individual platforms. Traditionally, [x+1] has been really strong at giving transparency and control to our customers. Rocket Fuel has been, and continues to be very strong in getting great results by automating tasks by letting machine learning do the work. My challenge is to build a platform that does both, plus more.
I’ve been through acquisitions at other companies and have seen some convergence plans go badly. I’ve also been fortunate enough to see some go extremely well. I don’t underestimate the challenge of this task, but do feel confident that Rocket Fuel is equipped to bring a state-of-the-art marketing platform to the industry.
So, why should people care that I’m working on one of the most exciting endeavors of my career? Because the end state will be truly different—and better—for marketers. Think about it for a moment: This will be a platform that takes signals from all channels, then layers artificial intelligence on top of it to optimize a marketer’s goals. The data he or she knows about a prospect or customer through their browsing behavior on a website, loyalty program, a call made to a call center, searches for his or her product, interaction with a paid ad, and more, will inform their next interaction with that customer or prospect across paid, owned, and earned channels.
Models should use real-time signals along with first- -and third-party data to ensure that all of the data you know about a customer or prospect is leveraged to deliver the optimal experience for that customer or prospect. And it should be easy. Siloed marketing is challenging enough on its own, let alone trying to coordinate with another team or different platforms. Bringing the silos together can be a significant organizational and technical challenge and often a barrier to orchestrating a true omni-channel marketing strategy. Access to a platform that makes this easy is crucial to attaining organizational alignment for an omni-channel marketing strategy and a successful execution.