CMO survey shows marketers struggle with data analysis

A survey by a UK public relations company shows despite the vast majority of CMOs using or trialling AI tools, half worry about data quality and integrity.

A 3rd of those surveyed frightened concerning the potential for AI to dilute ‘the human touch’ in accordance with a press release from the corporate. Yet the survey identified advantages of the technology in content creation and idea generation.

Analysis of data continues to be problematic for a lot of CMOs, and the survey findings suggest that while martech helps with content creation and strategic planning, there’s a lag in implementation of analysis tools, and lots of struggle to search out the time to properly consider campaign metrics, which continues to be a more manual task.

Traditional product marketing materials have gotten less effective, and nearly three-quarters said they place thought leadership and webinars as equally essential. Direct engagement continues as central to B2B marketing.

The survey [email submission required] highlights a disconnect between marketing investment and business impact when it comes to ROI. Qualified sales and marketing leads are easier to quantify than customer acquisition costs, with only 30% of CMOs monitoring the latter.

Lead generation, marketing analysis and PR are the predominant activities of most marketing departments, but many also cover sales enablement – the message is that marketers are expected to cover more areas of the business, and levels of overall responsibility are increasing.

Comment: AI and data aren’t silver bullets

There is a disconnect between the usage of generative AI and thought-leadership content creation. Media creation models (LLMs and their image/video equivalents) can only respin existing materials, making any such material produced derivative by definition. Ideation suffers from the identical problem: ideas published to the web and consumed by an AI model shall be surfaced by generative AI, albeit altered by a small randomising factor at the purpose of inference.

This tendency may be combated by the presentation of live events, webinars, and online discussions, and the production of original media: content created by informed humans.

Data analysis of absolute metrics (comparable to qualified leads) stays a straightforward algorithmic challenge for software. Measuring the success of broader campaigns has never been easy, and technology can only quantify representations of a brand’s impact in its digital manifestations – social media presence, search engine (and AI search) results, for instance.

Digital indicators comparable to posts being disseminated, shared and commented on, rankings by search engines like google or the surfacing of default answers by AI searches, are consistently manipulated by platform owners, users, or third-parties using bots or other gamifying technologies.

The commissioning company behind the survey stated that “49% worry about data quality and integrity,” yet: “The findings highlight the importance of developing an outlined AI strategy for marketing […]”

While AI guarantees, to various degrees, to be the magic bullet that may transform marketing, it’s becoming apparent in other sectors (creative arts, software development, customer support, medicine) that the technology is one tool amongst many. AI has specific abilities which may be of use in certain contexts. But like most tools, is best used alongside others.

Marketing functions placing AI and data on the centre of their strategy are akin to deal with builders planning their work around their investment in a fleet of mechanical diggers: useful tools doubtless, but only able to a number of tasks on site and requiring human operators.

(Image source: “silver bullet” by eschipul is licensed under CC BY-SA 2.0.)