How Data-Driven AI Can Transform Marketing

Across industries, headwinds are shifting. Recent world events have precipitated massive changes in consumer behavior that are revolutionizing markets and may jeopardize the longevity of entire industries. 

Underlying many of these changes is the issue of consumer trust. Data privacy and transparency have become hot-button issues as the public seemingly grows increasingly wary about how personal information is used and shared. As stricter policies and regulations are put into effect, many Big Tech companies are following suit by placing greater emphasis on privacy, such as the recent Identity for Advertisers update from Apple and the phasing out of third-party cookies by Google.

As a consumer, I understand and appreciate these changes. As the head of revenue for IBM Watson Advertising, I recognize that the advertising ecosystem will also change.

I believe that fierce competition and rapid market change will demand that advertisers continue to create and deliver messages that feel relevant, but not intrusive, to consumers. Further complicating these challenges are the issues in the existing programmatic ecosystem, such as a lack of transparency and sometimes ineffective value exchanges that can frustrate consumers. 

Some of the potential answers to these challenges are being discussed, such as one-off solutions or approaches that try to piece together disparate data sets. But it’s not clear they will help solve the problems.

Instead, I believe there’s a need for a new category of advertising that uses advanced, open technologies to facilitate faster and more informed business decisions based on consumer intent across digital channels. This fresh approach should be privacy-first and effective at scale throughout the full ecosystem.

The value of AI advertising

The notion of integrating AI into advertising strategies might sound like another way of proposing automation. This common misunderstanding could stifle a major opportunity for progress.

I believe that AI’s ability to perform complex mathematical calculations, which can augment our thinking, reasoning processes, sensing, and intuition with data-driven technology, can help accelerate and inform more accurate business decisions at scale—while helping to maintain consumer trust.

Weather as a proof point

When IBM acquired The Weather Company in 2016, one of the goals was to discover what AI could do for the brand and its massive repositories of unique data. Not only did IBM want to create the world’s most accurate forecasts, but we also set a goal of helping brands build trusted connections with consumers.

Four years later, IBM has seen firsthand the potential impacts of AI. Weather targeting is a great example. This involves the rapid and continual processing of complex data inputs to identify weather conditions that drive certain consumer behaviors. With these insights, brands can use geo-location—without cookies or personally identifiable information (PII)—to deliver targeted messages when such conditions are present. As a result, with IBM Watson Advertising Weather Targeting, we’ve seen one leading pharma brand increase the clickthrough rate on their Q1 2020 search campaign by over 300%, and one leading CPG brand increase sales of their air filters by 2.4% during their 2018 campaign.

Another use case is insight into flu and seasonal allergy risk. Latency and inaccurate data reporting can leave brands several steps behind consumers’ needs. But by using AI, IBM can combine weather data, anonymized health information and other data inputs with a privacy-forward approach to help predict spikes in flu or seasonal allergy risk up to 15 days in advance. In fact, IBM Watson Advertising’s Predictive Illness Suite is designed to predict real-time flu risk at an 87% confidence level, one to three weeks in advance of the CDC’s state-level weekly surveillance.

AI also can help brands address over-targeting, a practice that has been seen to render 55% of surveyed consumers apathetic towards brands according to Kantar’s 2019 DIMENSION study. By continuously learning which creative elements are most likely to resonate with an audience and analyzing reactions along with a multitude of other key signals, IBM can help marketers deliver a unique ad unit loaded with the most inviting content to the right audience each time. With this approach, we’ve seen one leading retail brand using our IBM Watson Advertising Accelerator solution increase their Q2 2020 campaign performance by 206% from the start of their campaign to the end.

A new reality for our industry

Over a decade ago, programmatic marketing changed our discipline on a fundamental level. As illustrated in this infographic, the AI Advertising Almanac, AI can have a similar effect on the industry to help us meet the needs of an ever-changing landscape.

In response, IBM Watson Advertising is building a suite of open solutions that can function in a cookie-less world for marketers, publishers and tech companies. I invite industry minds who are also passionate about using creativity and tech to help solve big problems to reach out and get involved.


All client examples cited or described are presented as illustrations of the manner in which some clients have used IBM products and the results they may have achieved. Actual environmental costs and performance characteristics will vary depending on individual client configurations and conditions. Generally expected results cannot be provided as each client’s results will depend entirely on the client’s systems and services ordered.