ChatGPT might create great content: its value still needs to be measured

Picture of Emma Lo Russo, CEO of Digivizer
Emma Lo Russo, CEO of Digivizer
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by Emma Lo Russo, CEO

In marketing, performance is everything. It determines the returns on your effort and investments, but also measures, analyzes, compares and helps you act on data such as engagement or impressions which are proxies for whether your customers actually care about your brand, its values, and the products or services you seek to sell.

So for me, the appearance and rapid adoption of generative AI starts with brand values, embodied in how brands seek to engage with their customers and audiences.

It’s a slightly different view from the consensus, which is currently anchored in discussions about productivity and profitability at one end of the debate, and the end of the workforce, especially for creative skills, at the other.

Neither is wrong, but neither is uniquely true either, and the choice is not binary in any case. AI in marketing, I suggest, is about understanding how to harness its power to create differentiation. 

And as David Meerman Scott reminds us, that starts with having a marketing strategy that includes AI, so that you understand where AI plays in your marketing efforts.

So what is AI’s role to be in marketing, and where does measurement and accountability come in?

We need to revert to first principles. If every organization replaces its creative team with AI engines, every company will eventually sound the same. Differentiation will disappear, content will either become generic or extreme as brands seek to stand out, and customers will vote with their thumbs. On its own, AI is not the answer.

AI has to continue to support authenticity and relevance. For sure it can speed up the process of creating assets that form the deliverables of a marketing strategy. But the strategy, and how success is defined, must come first. And customer trust must stay core to how you assess its value.

Customers demand differentiation: can AI deliver?

Thought-leadership and opinions invariably build on personal experiences and industry track-records. By definition, no AI engine can match these because AI engines can only distill what already exists to create visions of what might be possible. They may reflect thought-leadership already shared by experts, but clearly that won’t of itself be original thought.

Without this type of context, there won’t be differentiation, and it won’t be what customers want to consume, especially when they are seeking new input into complex business problems.

Accountability will also be important. ChatGPT’s hallucinogenic characters have already led to the first lawsuits, and AI governance remains in its infancy, with many organizations yet to consider who resolves questions of accuracy, legality, authenticity, and brand reputation. 

As generative AI creates new levels of productivity, profitability and even proficiency, people will still be needed to rule on accuracy and accountability.

In the meantime, companies and organizations can focus on what AI does have to offer. In my view, AI is  great for ideation. The Digivizer team uses various AI engines to prompt original thinking, around creative ideas, sources, and content for customers. As such, AI is a new partner at Digivizer, working alongside our experts and teams to help them think in new ways.

But the ultimate measure is whether you have created something of value, in your unique voice and contexts, that holds the trust of your customers and motivates them to take action.  

Content is great when it performs: that means measurement

Which brings me back to measurement. Content produced from the creative and fertile minds of one of our team, and content produced with the support of the algorithmic smarts of AI, both have to perform. The notion of “brilliant content” or “creative content” does not count: what does is how that content delivers outcomes. That requires systematic measurement and analysis of performance, however the content is created.

Measurement generates new inputs to the next iteration of content, so that the right levers are pulled to optimize and maximize content performance. 

Brands have to be clear about the value proposition they have for their customers, and be true to that value, as measured by the reaction of those customers. Differentiation comes from creating a unique position in the marketplace. And if AI is, above all else, regarded as a productivity tool, if it’s used solely in that way, brands will simply get to the point of being indistinguishable from their competitors faster than they otherwise would. 

Brand values are built on trust and authenticity. Brands therefore have to be clear about understanding the role AI has in promoting these values – in exactly the same way that they do today, with marketing programs that are created by humans. 

They can then focus on the benefits and advantages AI can provide, in product design and development as well as the marketing of that product, confident that AI will protect the brand promise and its values.

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