The power of artificial intelligence and automation can transform the majority of businesses, spanning a number of industries.
However, according to a recent survey commissioned by Adgorithms, AI adoption in marketing is being hindered by marketer’s understanding of AI, with 40% thinking they are already using the technology.
There is an inherent lack of understanding of AI-driven marketing and the rate of its adoption to date. This lack of understanding is punctuated by the 40% of participants who said they thought they had already adopted AI-driven marketing.
This reflects a belief that their targeting capabilities and automation meant that AI was operating behind the scenes.
Still more confusion was revealed by marketers’ varying levels of ability to delineate between targeted campaign efforts and true contextual marketing (relevant, personalised advertising and marketing based on insights gathered from relationships, and historical and situational context with customers).
The latter represents tremendous opportunity to deepen and personalize customer relationships, but also represents considerable complexity, which is precisely what stunts marketers’ evolution.
It is also what AI-driven marketing automates and simplifies.
“We believe the results of this study confirm many of the trends we’re witnessing in the marketplace, but we were surprised by the root causes of common marketing challenges,” said Amy Inlow, CMO of Albert.
“The common denominators driving these challenges were marketers’ willful lack of knowledge about the tools they’re working with and the tools available to them. As a result, they continue to be plagued by technological complexities, unreliable insights, and a lack of control.”
Marketers are disproportionately focused on early stages of the customer life cycle
When asked what objectives marketers were looking to accomplish with their marketing programs, they were more likely to respond with upper-funnel objectives, such as driving customer acquisition (61% of marketers) or awareness (53% of marketers).
Marketers were far less likely to say they focused their marketing efforts in later stages, where context comes even more heavily into play.
Marketers perceive technological and data complexities as inherent to marketing programs aimed at deepening and personalising customer relationships
The complexities that marketers cited as inevitable to meeting their objectives stemmed from technology and data, and were said to result in the following difficulties and/or inefficiencies:
Over-reliance on vendors/agencies for driving marketing strategy (37%); difficulty understanding the relative contribution of marketing channels to conversions (35%); difficulty translating customer insights into actionable marketing outcomes (34%); difficulty collecting, integrating and managing marketing data (32%); and difficulty operating fast enough to keep up with rapid pace of interactions and data collection (32%).
>See also: Using AI to transform e-commerce
Marketers have low expectations of their current approaches with 81% of participants said they expected efficiency gains of 10% or less using current tools and processes for marketing optimisation.
Marketers exhibit varying levels of understanding of AI-driven marketing, but are extremely attracted to the benefits it promises.
94% of participating marketers said a tool that provides continuous, autonomous optimisation across channels would be appealing to them, while 91% said a tool that enables their teams to review, analyse, and act upon customer and marketing data in a continuous and real-time fashion would be valuable for their organisation.
Marketers aren’t reluctant to adopting AI-driven marketing because they’re satisfied with their current approach
Only 6% of participants stated they believed their current tools and approaches were working sufficiently well.
Otherwise, the reasons they offered for their disinterest in an adopting AI-driven marketing solution included: Their belief that it would cost too much (48%); difficulty finding a vendor that fits their needs (35%); they hadn’t heard or know enough about it (35%); or their assumptions about the difficulty of integrating the technology into their current tools and processes (29%).