Home Data-Driven Thinking We Need To Evolve The Creative Model

We Need To Evolve The Creative Model

SHARE:

“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Dave Grzelak, chief strategy officer at The Shipyard.

In the expanding universe of programmatic media, there are more ways than ever to reach a target audience, with even greater precision.

But to fully leverage the technology at our disposal, we need to evolve the creative model. Even the people who respond enthusiastically to a brand can be very different from each other and must be marketed to individually.

A creative model must allow marketers to target individuals within their highest performing audiences, so they can be served particular stories most likely to result in ongoing engagement. This means considerably more than just learning which ads a person responds to and using AI for optimization. It requires thoughtful, human-led development of creative messaging that builds on our learnings across micro-audiences. Despite all of the advances in data tech, creating a true, emotional connection requires human insight.

For example, some people are motivated to buy an electric car for its low carbon footprint, others for the social status, and still others for the fuel savings. Some people respond to emotional messaging, others to more demonstrative explanation of benefits. Obviously, the electric carmaker would be foolish to not speak to all these segments, on their own terms, in the language they want to hear.

Similarly, many skincare consumers are traditionally motivated by product images and benefit overviews. But the creative model could adapt to a segment that responds to new age messaging and is intrigued by astrology or alternative medicine. To develop and maintain relevance with those who require different messaging, it sometimes requires different imagery, but other times it’s about creating a whole different narrative arc, using different music and sounds.

This is what I mean by micro-campaigns. They are simply hypertargeted chapters of a brand story that employ unique storytelling for each identified microsegment.

This is different from dynamic creative optimization, which focuses more on using the right template and the right copy line to the right audience. This also represents a big shift from the old model most marketers still use, in which the creative process yields one big idea that gets shoehorned into every piece of creative audiences see.

You know how it works: The media plan is developed, perhaps involving some segmentation. Fingers are crossed that it works. The data rolls in, hundreds and thousands of data points that help optimize by audience and channel.

But do all of those shiny new insights feed the ongoing brand planning or creative strategy? Can they account for and serve niche audiences, and are they serving up more personalized messages for them as a result? If not, you are losing attention from at least some of your audience even as you attract new eyes and ears.

The new model: iterative, adaptive and human

How do brands determine which ideas and storytelling archetypes are most effective for micro-segments before committing too much marketing budget on them? Creative experimentation, followed by purposeful story development.

Once the initial data is aggregated, strategists and creatives need to discuss the interesting opportunities that rise to the top. From higher-response groups, multiple audience segments should be identified, based on lifestyle, interests, shopping behavior and other data points.

This is the moment in the brand planning process that a slate of micro-campaigns can be fully fleshed out through creative strategy. For instance, perhaps you’ve identified an audience segment who is influenced by health concerns. For them, it makes sense to focus creative strategy to demonstrate a product’s safety features. For an audience influenced by environmental awareness, the creative strategy would make more sense focusing on the brand’s commitment to sustainable practices.

It is also possible to layer in contextual references, so that each micro-campaign becomes part of the conversation the consumer is already engaged in across multiple channels and tactics. This goes beyond copy-line changes to include unique messaging strategies that achieve relevance across multiple micro-segments and media.

Survival of the most flexible

Ultimately, brands will need micro-campaigns for an audience’s individual segments to survive because they not only drive engagement, but also because consumers now expect personal connections. No matter how creative or apparently successful that one big idea is, ads will be tuned out – or worse, a brand is deemed out-of-touch and annoying – by anyone who doesn’t find the communication relevant.

Marketing today must focus on more than a big idea targeted to wide audiences, using AI-driven learnings to optimize creative performance. That leaves way too many people behind.

Follow The Shipyard (@TheShipyardCrew) and AdExchanger (@adexchanger) on Twitter.

Must Read

Netflix Touts New Measurement Capabilities As It Struggles With “Modest” Engagement Growth

Netflix’s revenue grew 12% YOY to $12.9 billion in Q3, which it maintains is in line with its forecast. Its ads business, however, is lagging slightly compared with expectations, causing Netflix to tweak its forecast for the rest of the year.

Apple Publishes Its Plan To Wipe Out Web Tracking

Apple is coming for identity resolution. WebKit’s latest tracking crackdown targets the infrastructure behind post-cookie IDs – and switching to a first-party setup won’t necessarily spare vendors.

AI Slop Sites Are On The Rise. Is Ad Tech Ready For Its New MFA Challenge?

Advertising supply chain intelligence company DecryptAds uncovered more than 2,100 AI-generated recipe sites that are monetized with programmatic ads and feature fabricated author profiles.

Privacy! Commerce! Connected TV! Read all about it. Subscribe to AdExchanger Newsletters

How Australian Home Lender Lendi Measures The Invisible Work Of AI

Most brands and businesses are trying to figure out how to improve their metrics when it comes to AI – and also what those metrics even are.

AI Startup Minerva Built An Agentic CDP, But Don’t Call It That

Minerva wants to turn fragmented customer data into something marketers can use, with AI agents doing the work behind the scenes.

VideoAmp Bets On AI To Connect Ad Planning And Measurement

VideoAmp is competing in the measurement space by sharpening its focus on TV audience data, ad performance and, of course, AI. The company is also making strategic hires and promoting from within.