It’s time to address the elephant in the room. Marketers are trying to keep up with online audiences by super-sizing campaigns and chasing cheaper media buys, but without any confidence that these tactics are driving more effectiveness. Every marketer is asking: “How am I going to improve effectiveness to offset media inflation and CPM increases?” The approaches of the past won’t lead us to the future.
The answer seems easy. Study after study shows that creative effectiveness is responsible for the lion’s share of sales lift – far greater than media decisions. Nielsen found that strong creative was responsible for 86% of sales lift in digital ads and that across all creative, the quality of the creative contributed to 65% of digital ad sales lift. The recent MAGNA Media Study, says that creative quality drives 56% of impact on purchase intent, while Google says 70%. Solving for creative effectiveness is without a doubt the most impactful way to combat the rising costs of media, and 80% of marketers deem creative quality key to marketing effectiveness.
Successful ads should capture viewers’ attention, foster engagement and, ultimately, generate purchase intent. Quality of content is crucial to achieving these goals, and in turn, accurate performance insights are vital to ensuring ads contain the key hallmarks of quality. Up to now, data was only used to enhance the efficiency not the efficacy of the campaign. However, with the increasing requirement for large-scale campaigns, many marketers are focusing only on scale and efficiency metrics, and overlooking the need for data on effectiveness to identify how to develop quality campaigns that have the right impact; more specifically, creative data.
Updating the focus
Given the limited tools and resources to measure creative effectiveness thus far, marketers have had little choice but to focus on the data available and pump out scaled content, hoping for good campaign results.
But, technologies are now able to generate truly effective creative content, and the industry must pivot towards the data that can inform strategies to drive performance. Those who refuse to update their approach risk hindering their own results. To do this, marketers need to understand where the gap between current established data types and successful execution lies.
Used early on in a campaign’s development, this data is acquired through pre-tests aiming to gauge how a small pool of respondents reacts to advertisements ahead of a wider launch, allowing marketing teams to trial creative to generate better results. However, these types of insights can be restricted by pre-determined audience opinions or general affinity for the brand in question, meaning assessment isn’t necessarily objective or thorough.
Maximising accuracy can also be problematic. Misunderstandings from a lack of clear communication on questionnaires may lead to irrelevant information being gathered as data, and insufficient diversity or unconscious biases may taint the insights. The method still gives marketers a useful idea of likely audience engagement. However, its flaws do mean that advertisers need other ways of obtaining more accurate information.
Media data mostly comes either from public information collected from users’ social media channels or collated by analytics tools. The details gathered across digital platforms can then be quantified using standard metrics such as engagement, impressions, reach, share of voice, and conversions – the industry’s default for tracking and optimising performance against core KPIs.
The retrospective nature of this data is hugely debilitating; learnings are only identified after the campaign has been launched, too late to improve creative efficiency and impact. Insights offer no information on which creative elements of a campaign will drive marketing performance during the design process, making it impossible to optimise the investment. Marketers risk having to test several costly approaches before landing on a successful path.
Offering a complete view of granular ad impact, creative data drills into the DNA of each message, assessing the effect of every element within an ad; such as Call-To-Action (CTA), setting of the ad (indoors or outdoors), the eye gaze of featured talent, colour saturation, scene pacing, and dialogue. Creative data isn’t temporally restricted like pre-testing and media data; it can be collected in real-time, enabling inflight optimisation. It informs marketers on effective elements during the creative process and enables them to drive campaign performance at every step of the way.
The process can involve significant initial investment, but using smart AI tools to drive large-scale yet accurate assessment will ultimately provide worthwhile efficiency gains.
Pivoting to value-creation with Creative Effectiveness
To deliver creative data – the actionable insights to optimise future campaigns en masse – AI-based tools can be used to study creative elements in brands’ entire marketing portfolios, providing an overview of all past campaigns. But, AI can’t strategise like humans can, lacking the ability to interpret contextual elements and nuances.
This is where marketers can flex their human muscles to drive campaign performance. For example, a mattress brand could receive the following insight from data: “Partial human body parts are driving a 20% lift in your brand.” To an AI tool, the solution for a future campaign could simply be placing disjointed human body parts on a mattress, potentially resulting in something out of a horror movie.
To a team of human strategists, who contextualise those data points, it is more likely to mean that ads featuring hands, elbows, and knees pushing down on the mattress are driving the lift for the brand. This could then be applied to other creative designs in ways that demonstrate the firmness of the mattress, which is the element responsible for the brand lift.
The interplay between AI data and human thought eliminates time-consuming guesswork and inefficient costly content. This can impact the business’s entire creative strategy and be applied to future marketing efforts, turning non-working money into working money, and driving performance, efficiency, and ROI.
Data is a fundamental requirement for advertising to continue succeeding as much as it is growing. With marketers under pressure to scale content when delivering campaigns across multiple platforms, they must prioritise quality which will also bring value to the quantity achieved. Creative data fuels effective marketing campaigns, enabling marketers to deliver quality content instead of a less effective version with avoidable flaws. AI is simply the tool at our disposal to harness its potential, filling the data gap that separates us from creative effectiveness.