For the better part of two decades, marketing and advertising technology investment has been centred on audience precision and media efficiency. While these efforts yielded significant results, most of the easily achievable improvements have been made. Now, attention is shifting to the next frontier — creative intelligence.

While studies show that creative quality is a strong contributor to advertising effectiveness across key metrics, most teams operate with surprisingly little visibility into what makes one creative execution outperform another. As a result, organisations invest heavily in production without knowing which approaches will succeed. This disconnect creates a clear opportunity for investment in creative intelligence to deliver improved business performance and competitive advantages for marketing and advertising teams.

To better understand this opportunity and the evolving creative intelligence landscape, we partnered with Winterberry Group, a growth consultancy specialising in the intersecting disciplines of marketing, advertising, technology, data and analytics. In a comprehensive whitepaper leveraging a combination of quantitative industry surveying, expert interviews, secondary research and market modelling, the team assessed how creative intelligence is being applied across the content lifecycle, how adoption is occurring across industries and organisation types, what primary use cases are driving demand and what the outlook is for future growth.

This blog will cover:

• What creative intelligence means and why it matters now
• Where creative intelligence delivers the biggest impact
• Recommended next steps for getting started

What is creative intelligence?

Creative intelligence refers to understanding why customers engage with pieces of creative content. It goes beyond measuring whether a campaign worked to answer why it worked — identifying the creative elements and choices that drive engagement and results.

While there are historical forms of creative testing and measurement (A/B testing, focus groups, click-tracking) that are widely used today, the next evolution in creative intelligence has only recently become accessible.

Technological advances now allow teams to deconstruct advertising assets automatically, catalog thousands of creative decisions (for example, colour palette, logo placement, copy clarity etc.) and correlating those decisions with performance outcomes. This evolution is also driven by advanced integration between creative and media technology.

The business case is straightforward. Research shows that 40-50% of creative assets produced never get activated in campaigns. Creative intelligence helps organisations eliminate a substantial amount of this wasted production effort, while fine-tuning assets that are activated for optimal results. By unlocking predictive, in-flight and post-campaign insights, teams can ensure their creative and media dollars are allocated in the most efficient and effective way.

This value proposition is resonating with businesses across industries and resulting in significant investment. In the US alone, creative spend powered by creative intelligence is projected to reach US$11.47 billion by 2028, growing at approximately 23% annually.

Where creative intelligence delivers impact.

The application of creative intelligence spans the entire campaign lifecycle, but three areas stand out for immediate return on investment.

1. Eliminating production waste through pre-testing.

Before committing production budgets, marketers can now evaluate creative concepts against historical performance patterns and platform-specific best practices. Predictive scoring assesses work-in-process assets across a variety of dimensions, including audience attention patterns, channel constraints and brand compliance.

This upfront evaluation prevents costly mistakes. For example, when analysis indicates that copy exceeds optimal length for display advertising or that a proposed asset’s colours or environments are not in compliance with brand standards, teams can adjust before investing in final production. The result is a higher percentage of assets being used and better performance from those that go live.

With access to historical asset- and attribute-level insights for paid campaigns via GenStudio for Performance Marketing and for owned channels via Adobe Content Analytics, teams can begin the creative process with a clear view of what works creatively and where resources should be invested.

GenStudio for Performance Marketing also enables additional pre-testing by allowing teams to quickly assess content against their brand, persona and channel guidelines before activation. Together, these capabilities help organisations create more effective content more efficiently and earlier in the creative cycle.

2. Scaling personalisation economically.

Personalisation has long promised better results but faced practical barriers around production volume and cost. Creative intelligence platforms address this through modular assembly, combining proven components into audience-specific variations without manual design work for each permutation.

During campaign execution, systems automatically select creative variants based on real-time signals, including audience segment, device type and prior engagement behaviour. This enables the level of personalisation audiences expect — without proportional increases in production workload.

GenStudio for Performance Marketing recognises this need with its Adobe Real-Time CDP integration. Marketers can build content that starts with full customer context, messaging preferences, buyer segment, journey stage and behavioural data — to tailor ad creative and copy by audience segment. With high-quality variants at the ready, creative activation systems can quickly serve the right piece of content to each individual.

3. Measuring creative contribution to outcomes.

Perhaps the most strategically important application involves quantifying creative's actual contribution to results. By tracking which specific creative elements appeared in high-performing campaigns and controlling for media and audience variables, organisations can finally answer questions such as:

• Do authentic customer testimonials outperform stlylised lifestyle imagery?

• Which emotional tones drive consideration versus immediate purchase?

These insights inform not only optimisation within active campaigns but also broader strategic decisions about creative investment and approach. For instance, when organisations can demonstrate that creative quality contributed X percentage points to conversion rate improvement or Y dollars to incremental revenue, creative budgets become easier to justify and teams gain clearer direction about what to prioritise.

Adobe Content Analytics enables teams to easily answer these questions by pairing the analysis of creative and behavioural data across owned digital channels. This provides a holistic view of the customer journey through a content lens, allowing organisations to identify the most effective assets, attributes and placements that drive results. Not only does this help demonstrate value for in-flight or completed campaigns, but it also allows creative teams to optimise future campaign assets based on high-performing, ROI-driving attributes.

Getting started and scaling your creative intelligence practice.

Creative intelligence represents a fundamental shift in how marketing organisations approach advertising effectiveness. For organisations getting started in their creative intelligence journey, the recommended next steps are:

1. Assess current creative workflow inefficiencies: Identify where your organisation experiences the most pain — production bottlenecks, high asset abandonment rates or difficulty scaling personalisation.
2. Start with measurement to build the business case: Establish baseline creative performance measurement across current campaigns to document which approaches are working and where improvement opportunities exist.
3. Pilot pre-testing on high-volume channels: Paid social and programmatic display offer controlled environments for testing predictive creative scoring.
4. Integrate creative and media planning earlier: Break down silos between creative development and media activation teams through joint planning sessions.
5. Build cross-functional capabilities: Invest in training team members who understand both creative strategy and data analysis. Creative intelligence augments human judgement — it doesn't replace it.

For marketing and advertising leaders navigating budget pressure while facing demands for better performance, creative intelligence offers a path forward. By transforming creative from a fixed cost into a measurable, optimisable driver of results, organisations can finally close the loop to understand not just who saw their content and where, but why that content succeeded or failed.

Sam Garfield serves as the Head of Digital Strategy, Communications, Media and Travel at Adobe, where he provides thought leadership and works with CMT companies on digital transformation efforts. In his previous role, he was the strategic lead responsible for setting the vision, strategy and focus of AARP Services’ data infrastructure and analytics offering. Prior to that, Sam spent 16 years at Discovery Inc., focusing on financial systems, process improvement and data analytics. He was the Vice President of Data Strategy and Advanced Audience Platforms, providing leadership on the data strategy and roadmap for Engage, Discovery’s advanced TV product. He has received bachelor’s and master’s degrees in Business Administration from the University of Maryland.

Zack Ackerman is a Data Strategy Manager in Adobe’s Digital Strategy Group, where he advises clients across industries on their digital transformation efforts for customer experience and content supply chain. Prior to Adobe, Zack spent four years in corporate and investment strategy for travel, hospitality and healthcare brands. He received his bachelor's degree from the University of Virginia and his master's degree from Virginia Commonwealth University.

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