Artificial intelligence seems to be the biggest topic on everyone's mind.
What once was considered a distant sign of the future, AI is now a staple in so many facets of our lives. From spellcheck to supply chain, AI is transforming the way people communicate, collaborate, and consume -- and there's no greater example than how it's manifesting in marketing and advertising.
A recent Epsilon study, "The State of AI in Marketing," shows marketers are fully bought into AI, but there isn't a full view of ROI. While 94% percent of survey respondents say they are using AI to prepare or execute their marketing strategy, more than half say they face technical challenges, like model accuracy and integration with other tools and systems, when implementing it.
AI adoption alone won't deliver perfect results. While AI can make life easier for marketers and advertisers seeking personalization and engagement at scale, having quality data and identity to fuel that AI is critical to realizing value.
It comes as no surprise that marketers are no longer looking at AI as a nice to have.
In the Epsilon study, all respondents who say they don't use AI for marketing and advertising strategies say they plan to implement it in the next six to 12 months. Additionally, 93% of respondents say they plan to allocate at least 5% of their budget to AI initiatives, with most forecasting a 5% to 10% overall budget for AI.
The reason is clear: They find it supports their goals. AI use can cut costs, improve efficiency, save time, and improve customer experience. Brands can use it for data analysis and insights, to generate content and ads, and for customer service via chatbots, among other things.
While popular, AI implementation still has its pushback. Nearly half of the marketers surveyed say they faced technical challenges like model accuracy and integration with other tools. But others reported data quality issues and a lack of data as hurdles for AI adoption.
Data access and quality are critical components of AI. As brands adopt more AI technology, their data gaps are becoming increasingly clear. Although AI generally improves outcomes across the board, for it to produce accurate, scalable results, it needs a foundation of good data.
The quality of your output is only as good as the input. Without good data, AI becomes less effective. It's like driving a Ferrari in stop-and-go traffic.
When first-party data is cleaned and enriched through a person-based identity solution, it creates a complete view of a brand's customers online and offline. Having that person-based view is a jump-off point for hyper-personalization and engagement at scale.
Brands can use AI to craft relevant, personalized messages at scale because they have a deeper understanding of their customers and then deliver those in real time on the devices people prefer.
New AI vendors are popping up every day. Some of these vendors offer niche services, but most claim to be the end-all-be-all of AI implementation. So, how do brands parse out which partnerships are the real deal?
It's important to understand what challenges you face and what outcomes you ultimately want to see. Implementation challenges are both organizational and technical. In the Epsilon survey, marketers say their top technical challenge was model accuracy, and their top organizational challenge was resistance to change.
Marketers facing doubt from senior leaders should lean on AI efficacy proof points to assuage fears of change, but they should also pick a vendor with a proven track record of data, identity, and AI collectively.
Brands also need to understand their current technical capabilities and gaps. What tools are at their current disposal? How are those integrated within their other marketing systems? Can these tools deliver scalability today?
This is why data quality and management are so important. Brands looking to really transform their marketing need AI built into their martech and adtech, and a tech stack that can work cohesively from a solid source of data.
Some key questions to ask: How does a vendor incorporate data and identity? How are they managing privacy and consumer safety? What technical expertise do they offer if the marketing team lacks the skill to use the solution? What experience do they have actually deploying AI with real brands that drove real results?
AI promises to transform our way of life, especially in traditional marketing and advertising. To use AI to its maximum potential, brands should lay the groundwork to make it possible.
When choosing an AI solution, make sure you're finding a partner that is invested in that foundation, and one that can prove they know how to deliver results at scale.