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Artificial intelligence (AI) has become a catchall phrase for automating both mundane, repetitive tasks as well as machine-generated insights from enormous data sets. But AI is increasingly moving into the creative sphere as programmable systems influence marketing’s creative functions.
The result is what marketing, advertising, technology, data and analytics consultancy Winterberry Group has deemed “creative intelligence.” Creative intelligence encompasses data-driven insights into creative choices within advertising and how those choices boost marketing’s effectiveness. These insights form a triad with media intelligence (the where, when, and how of interactions with marketing material) and audience intelligence (the behavioral, preference, and motivational data that guides targeting, prospect/customer activation, and optimalization).
“Creative intelligence enables marketers to mix and match awareness, consideration, and performance objectives while measuring impact with fewer human capital resources,” according to authors of Creative Intelligence: Adopting & Operationalizing Creative Intelligence, a new report from Winterberry Group. In doing so, creative intelligence allows marketers to add measurability and return on investment calculations to many individual aspects of the creative process.
“CI takes creative — often labeled as ‘non-working’ media — and translates it to ‘working’ media because important engagement metrics are derived from their deployment and analysis,” Michael Harrison, CEO of Winterberry Group, said via a statement accompanying the report. “These metrics may include ad-level performance metrics, sentiment analysis, and increasingly audience reaction and attention-based metrics.”
Per Winterberry, creative intelligence solutions encompass, automate or enhance six core functions:
* Creative asset ingestion and normalization: This takes in and standardizes creative mediums such as images, video, copy, audio and design files, allowing them to be analyzed;
* Creative data conversion: This process extracts metadata, tags and features from creative assets, allowing them to be organized into structured taxonomies;
* Pre-test: This offers an activation test environment for draft creative output with either real or synthetic audiences;
* Creative performance analytics: This analyzes the creative assets’ impact on the marketing materials in conjunction with campaign, engagement and conversion data, resulting in optimization recommendations;
* Activation and optimization. These turn insights gleaned from creative intelligence into either real-time or post-campaign analysis; and,
* Measurement: This sums up performance and potentially offers further campaign/effort optimization or guidance for multi-media marketing integration.
Creative optimization is gaining the attention of media agency professionals. Nearly one-third (31%) listed it as a top priority for improving advertising effectiveness, followed by personalization of audience and creative data (23%), measurement and performance tracking (15%) pretesting of concepts or messaging (13%), insights generation and application (10%) and paid media activation (8%).
As is often the case with technological innovations, the nonprofit community lags the commercial sector. The top six verticals that are furthest along in adopting creative intelligence are the consumer packaged goods sector (21%); retail (20%); automotive (14%); financial services (9%) and the technology and commercial/marketplaces sectors, at 7% each.
The report’s authors offer insight into why certain sectors might be more willing to test creative intelligence. “As with other AI-driven capabilities, regulated industries are lagging relative to these early adopters,” they wrote. “Interviews suggest that adoption in these sectors is proceeding cautiously, with an emphasis on controlled testing and compliance assurance.”
The field is still young, and marketers are hammering out which data, measurements and metrics will be most useful. When asked which type of creative data they would most anticipate using to drive creative intelligence during the next 18 months, no one source of input jumped out. Roughly one-sixth of agency employees surveyed mentioned creative element performance data, attention metrics or sentiment analysis from audience reactions and comments. Another 13% cited social engagement metrics or emotional response data, with the rest of the respondents mentioning clickthrough and conversion data by creative variant, brand lift and recall metrics, A/B testing across creative components, or copy/messaging effectiveness scores.
The research drew on a survey of more than 120 creative and media agencies across the United States and U.K., complemented by in-depth interviews with marketers, agencies, and technology providers. A full copy of the study is available here: https://winterberrygroup.com/creative-intelligence-adopting-operationalizing-creative-intelligence
