For most marketers, the thought of becoming a data scientist seems a little out of left field. After all, our jobs are about being creative, building brands and driving revenues by providing our target audiences with what they need and want. We think of brilliant marketers as being the ones who come up with that campaign or tagline or idea that encapsulates what our customers want, and encourages them to come on a journey with us. We don’t always understand the full scope of the role.
But in reality, data has always been central to a marketer’s job. At its simplest, any marketer monitors whether sales go up or down after a campaign. Even Roman street food sellers undoubtedly assessed whether the benefit of hiring a promoter to shout about their wares on the street had a positive or negative impact on their sales!
“We are now all data citizens and each of us within the team needs to access and be able to draw insight. AI and machine learning offer a way to transform many of these tasks and see better and quicker insights, while exponentially expanding the scope and variety of analysis and information available to us all.”
More data. More opportunities
Today, however, we generate and collate more data than ever before, making the process of reviewing and analyzing it more complex. A twenty-first century marketer has data about much more than just which stores sell the most product. They can analyze which products are most popular by time of day/week/month, or whether outside factors such as weather or traffic patterns drive or depress sales. They have access to data on the immediate impact of specific advertisements and channels, (with services like Google Lens leading to ever more granular data). The modern marketer can access competitors’ data for comparison purposes and to inform product decision-making or see if a different way of listing a product online has an impact on sales. These datasets are just the tip of the iceberg of what’s available – data sources are endless, as are the ways to use them.
AI allows any user to answer questions and make decisions based on a significant amount of data. While humans may try to manually collect and analyze this data, the sheer volume of sources makes it almost impossible to do so well and quickly. We are now all data citizens and each of us within the team needs to access and be able to draw insight. AI and machine learning offer a way to transform many of these tasks and see better and quicker insights, while exponentially expanding the scope and variety of analysis and information available to us all.
As our Chief Technology Officer, Oren Raboy said recently in a blog post, making technology directly accessible to business users is key to helping to scale AI across enterprises. This applies as much to marketing as it does to any other business function. A no-code solution allows marketers to leverage technology by using their data in new and better ways to support use cases from pricing strategies to content creation. And it does so with speed more quickly and at a lower cost.
AI drives sales and enhances customer experiences
The potential use cases of leveraging AI in a marketing function is huge. We’re already seeing AI contribute to enhancing customer experiences, identifying new markets and sales opportunities, uncovering competitor insights, tailoring advertising, and creating better content. But as CMOs, a different tool for each need isn’t going to work. We need something our entire team can leverage, and it needs to be user friendly and collaborative.
As consumers, we see AI utilized in Amazon chatbots, pre-filled forms when purchasing online, tailored special offers when swiping a loyalty card, advertisements based on browsing history, or speedy loan applications.
These all reflect the findings of Salesforce’s State of Marketing Report 2021, which highlights that marketers include creating a cohesive customer journey, improving marketing ROI and attribution and engaging with customers in real time as three of their five top priorities. However, the same report also discusses that while marketers have more data than ever before, and 75% plan to use more data sources in 2022, this additional data doesn’t necessarily lead to improved customer insights.
Ensuring that it does is where AI becomes a game changer. Marketers still need to assess the potential use cases, data availability and usability, trustworthiness, data enrichment opportunities and how to train AI systems to deliver the desired outcomes. However, using traditional approaches – all of these tasks are solely the preserve of technology specialists who have to first be educated on the marketer’s world and processes. As marketers, we need to find the way to take ownership of this process.
With the right tools, AI has the power to turn any business user into an effective data expert. Not only should these tools be user-friendly and intuitive, but must allow for flexibility and tailoring in a way that the marketer’s own creativity and requirements become the only barrier to the value that can be derived. The only question is when and how? And finding a partner that you trust.