Digital advertising never stops moving but even with the multitude of sophisticated technology available, there is still much room for improvement. So the challenge for agencies is how to innovate faster and more reliably to gain the edge and stay ahead?
According to a recent study by the World Federation of Advertisers, 89%* of brands don't believe their current agency model is fit for future purposes.” Even more tellingly it goes on to say, “1 in 4 of those surveyed are looking to consolidate media, creative, data and technology."
The assortment of challenges can appear overwhelming, ranging from the increasing complexity of multi-channel campaigns and reporting, to the optimizing of ROI and the measurement of data. Also, as people increasingly choose to look, assess and buy on mobile, great consideration has to be given to this channel to reach target users where they are spending most of their time.
The challenge: How can I respond to clients’ demands for more engaging creative content across multichannel campaigns?
The answer: Faster more cohesive briefing. Creative that cuts through the background noise starts with a clearer brief. AI can help produce a definitive brief against which to produce creative. AI-powered machine learning leads to briefings that define and match the target audience with a campaign’s intended outcomes much faster and more accurately. This leads to shorter briefing and creative development time, and equally importantly, results in an optimum creative brief that can be better measured against performance.
The challenge: How can I optimize my clients’ content?
The answer: Advanced machine learning is fed by data from thousands of past campaigns finding best practices for an ad unit according to industry and/or its own specific campaign objective/s. AI can then produce clearer guidance on the target audience, guiding the creative content towards optimum results. But it doesn’t stop there. Innovations in AI look past mere ‘attention’ on the screen to produce an assessment of the actual engagement between the user and the creative shown. AI provides instantaneous recommendations for visual and copy changes in real-time to enable the campaign manager to test ‘with or without’ the recommendation almost instantly (A-B testing on steroids if you like). The data analytics are also collected from a much wider range of behavioral criteria too.
The challenge: How can I meet clients’ demands for better measurement of data?
The answer: AI redefines measurement, taking it away from mere ‘attention’ into the assessment of ‘engagement’. Where the user’s cursor spends its time, reaction times, etc., are all measured against optimum levels for each activity held in the AI’s ‘brain’. Real-time recommendations may be the removal of a single click requirement or the changing of a color – all proposed and undertaken in microseconds - enabling the campaign manager to test ‘with or without’ the recommendation almost instantly (A-B testing on steroids, if you like). The data analytics are also collected from a much wider range of behavioral criteria too.
Nb – Global advertising tech group, Adludio, proposed that there was not one clear, concise metric to use for measurement. As a result, it developed its comprehensive Composite Attention Score CAS to assess the attention rating of campaign creative prior to go-live, during and post post-flight. The CAS enables the platform’s AI to push fully automated optimization recommendations throughout the campaign process giving clients data-driven insights to maximize campaign performance every step of the way.
The challenge: How can I satisfy needs for more valuable reporting?
The answer: More than just providing an overview dashboard, AI-driven machine learning provides valuable input on how to get more from creative and campaigns. Real-time reporting can be undertaken simply, without the need for data specialists, and decisions can be taken instantly, based on historical data and real-time analysis all within one window.
The challenge: Every brand is looking for a superior Return on ROI
The answer: With AI-driven machine learning technology, the potential upside in profitability speaks for itself. Campaigns may be tweaked, corrected or realigned early on, even on the first day. Driving this potential increase in profitability – and cost savings – is a more identifiable and positive user engagement that encourages a greater pull-through to sales. AI-led insights and a shift towards meaningful attention create a more telling cost per engagement (CPE) and step beyond passive ad impressions. The more attention the user has, the more likely a conversion. Such an approach can significantly improve return on investment to traditional cost per mile, where ad views may not result in any meaningful action.
The challenge: How can I scale up across multiple digital channels?
The answer: AI’s ability to offer optimized insights on users’ behavior, motivations, and preferences extends across multiple channels, making scaling up less complex and swifter, Target groups can be defined according to machine learning with optimized insights feeding back in real-time to provide a consistent experience across multiple channels and touchpoints all from a single platform. With AI assessing data and providing swifter reporting, the result is a unified approach with consistency in branding and messaging across different channels and a more personalized experience for individual users.
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Adludio’s unique AI-driven platform creates optimum campaigns for your client, bringing cutting-edge innovation to digital advertising campaigns and exceeding the challenges of today’s ever-demanding brands. Find out more Adludio.com
