Part XII: The Rise of the Machines…
According to an iED survey of marketing professionals, the identification of prospective customers is the leading reason businesses choose to adopt artificial intelligence and machine learning technologies. Whilst automated techniques are unquestionably effective for market analysis and lead generation, 2023 will see AI and ML applications deployed across a range of distinct marketing contexts, with advertisers given greater access to this powerful and ever-evolving toolset.
In the immediate future, AI and ML technologies are likely to have a particularly significant impact on creative materials: how they’re optimised, how they’re displayed, and to whom they’re shown. Advertisers who embrace these solutions early will be establishing a positional advantage for the coming years, as AI implementation moves from the exception to the norm.
Dynamic Creative Optimisation
Dynamic creative optimisation (DCO) takes a programmatic approach to the selection and deployment of audience-specific creative content. Combining first- and third-party datasets with live analytics and real-time testing, DCO-produced ad units are hyper-relevant and ultra-personalised.
Traditionally used primarily for display and image-based ad units, AI will herald a new era for DCO, allowing for powerful analysis of media rich content, as well as contextual cues and dynamic data sources. Beyond this, there will be a proliferation of systems that partially or fully create ad materials automatically, based on NLP and NLG technologies, and without the need for any direct human input.
AI is well established as a method for automating the tedious, repetitive, and time-consuming tasks that the average marketer performs day-to-day. However, an increasing number of forward-thinking businesses are relying on it to manage and optimise their campaigns holistically, with ad performance and spending constantly monitored and altered based on established KPIs.
Whilst granting marketers a great deal more flexibility and freedom to focus on creatives, autonomous solutions demand more refined strategic input at the activation stage, as well as well-honed procedures for spotting issues and amending campaign goals on the fly.
Google Performance Max
Performance Max is the newest addition to Google Ads’ lineup of campaign types. Relying on advanced machine learning technology, Performance Max takes a goal-driven approach to campaign performance, drawing available inventory from across its network to maximise paid performance and hit defined KPIs.
Performance Max layers upon its campaigns a level of dynamic creative optimisation, scanning advertisers’ asset groups (consisting images, videos, headlines, and/or description lines) to find the ideal asset for both the inventory source and the consumer.
It’s fair to say that Google’s innovative new campaign approach has proven somewhat controversial, but if the company’s past results are anything to go by, Performance Max might just be setting the new standard for digital advertising.
Strictly speaking, Evolv AI’s platform is less about advertising than it is about converting. Its proprietary AI platform is used to optimise the customer experience (CX) for website visitors, ensuring ad spend doesn’t just result in clicks that have zero impact on the bottom line, but in measurable results and returns.
Evolv achieves this task through an automated process of discovery, personalisation, modification, and execution of CX strategies at the site level. After establishing a strategy, it displays to your leads small variations, and, based on user activity, creates a clear picture of what works, what doesn’t, when, and why.