“Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media.
Today’s column is written by Jacob Beck, programmatic media specialist at DWA Media, a Merkle company.
Already, the AI ecosystem has grown crowded, especially as it relates to managing programmatic spend.
Demand-side platforms (DSPs), supply-side platforms, dynamic creative providers and others are all working together to bring AI into the mainstream of programmatic, where it promises to make advertising more relevant for both consumers and brands.
Companies, particularly those in the B2B space, are only beginning to grasp the scope and scale of how AI can influence their marketing programs. B2B adoption of AI is paramount, as there is a level of complexity within the marketing world that exists outside the scope of human manageability. The importance of AI exists in its scale.
For B2B marketers to fully tap into the power of AI for their efforts, marketers must first understand the power that lies within their data. Some B2B marketers today aren’t even using a data management platform, putting them at a serious disadvantage in enhancing their programs. Data is key to advanced learning over time, and AI models are only as good as the data that is put into them.
Below is just a sampling of partners that are delivering tangible, AI-driven results for B2B marketers and their programmatic campaigns. While the technology remains the same for B2C versus B2B campaigns, B2B marketers need to have a long-term mindset when approaching these AI solutions. The goal shouldn’t be to see immediate performance but rather precision in targeting and messaging that will eventually lead to higher ROI.
IBM Watson: Made famous by its Jeopardy victory in 2011, Watson is deep in the trenches with marketers these days, using advanced neural networks to find the right audiences for brands. The system, which is trained over time, analyzes relevant data sets and scores users based on the probability of taking a particular action.
For B2B marketers, tapping into Watson is as simple as providing a known audience via first-party data, such as a list of recent marketing qualified leads, and outlining the desired action the brand wishes to drive, such as a download of a new e-book. IBM Watson was a managed service technology but now allows marketers to run campaigns using its technology in the DSP of their choice.
Dataxu: Via its Open AI for Ads platform, dataxu partners with Oracle and PlacedIQ to dynamically inform bidding models and add scale and efficiency to first-party data by layering real-time optimization onto prospecting line items. In real time, its technology models each cookie to determine whether to bid based on a conversion goal. It takes a standard look-alike targeting strategy and makes it “look-a-live,” as we at DWA call it, due to its real-time modeling attributes. Modeling this real-time audience using an audience comprised of top company purchasers in the past six months will provide scale and recency to inform the bidding model.
The Trade Desk: The Trade Desk’s AutoAllocator directs spend to better-performing ad groups first, then allocates remaining budget to lower-performing groups. The system lets marketers set priorities and goal CPAs to help influence where money will shift. B2B advertisers tend to rely on third-party data for scale, so using that targeting, in conjunction with AutoAllocator, allows for budgets to be spent efficiently and effectively.
Google: Not surprisingly, Google employs AI on both sides of the equation. On the demand side, DV 360, previously known as DoubleClick Bid Manager, delivers automated bid strategies to maximize for various KPIs, including CPA for more acquisition-driven B2B advertisers. On the supply side, Google AdSense’s Auto Ads uses machine learning to determine not just which ad creative to serve and when but also the type and location of ads. This may lead to more ads for B2B advertisers serving in-view and above-the-fold ads, based on their parameters.
Programmatic, B2B and AI converge
B2B marketers must be prepared to manage expectations and recognize limitations around AI. The realm of AI isn’t as scary as many might think. Today’s AI doesn’t necessarily operate in a black box. Marketers are able to load in their data and see how models use it for decisioning. But B2B marketers must remember that AI-driven initiatives are long-tail efforts. It could take a few weeks to see results. Marketers must set up their campaigns and give the machines the time they need to learn and function.
As with all campaigns, common sense applies with AI. Marketers must set these platforms up for success by defining their KPIs in advance, sticking to them and planning for proper measurement. Marketers must plan for ongoing human-based monitoring to optimize performance.
The machines aren’t here to take marketers’ jobs – they’re here to help marketers do their jobs better. By approaching AI like any other partnership, B2B marketers can ensure they get the most from these ever-evolving tools.