This question has become a long-running industry discussion and regular feature on the bill at almost every major event. The fact is, however, that we don’t need to choose between data or creative-led approaches. When these forces are used together – with creative considerations factored in from the start of campaigns, rather than as an afterthought – they can ensure maximum relevance, engagement, and outcomes.
One way for marketers to achieve this is utilising a technology designed to fuel efficient, large-scale creativity using data: dynamic creative optimisation (DCO). But what exactly is DCO and how does it achieve this?
DCO isn’t what you think
Many marketers may feel they already know DCO as the primary tool for retargeting users with previously viewed offers or products, but this narrow application is just a fraction of its capabilities. The full range of DCO uses is often covered by alternative terms such as data-driven, intelligent or responsive messaging; alongside the aliases for its basis of dynamic creative – addressable, programmatic, and agile creative to name a few.
All this falls under the umbrella of DCO. The standard definition is personalised and relevant advertising that’s data-powered and automated by logic, but in simpler terms: DCO is about matching many tailored versions of ad creative to specific audiences.
How does it work?
Given the endless capacity for creative variation, DCO implementation frequently includes processes intended to streamline ad adaption, delivery, and optimisation. Marketers will typically begin by building a master template or framework and determining which elements they want to be changeable, before plugging in their store of creative assets for continuous use; either by uploading them into a digital library or via an instant data feed.
Once initial setup is complete, marketers then establish which data signals to use for their target audiences – from contextual IDs to weather and location information – and create a matrix that enables DCO systems to automatically select ad variations for certain users and situations. Or in other words: a ‘decision tree’ of delivery. For example, new website visitors might see creativity with broader appeal, while past purchasers receive offers for products that tie in with their previous buys, coupled with additional factors such as the weather; think parasols for outdoor picnic tables.
At the optimisation level, algorithms can use decision trees alongside analysis of effectiveness against key metrics to improve results; with knowledge gathered about user preferences and high-performing ad types applied to adjust both in-flight and ongoing campaign activity.
Key brand benefits
The chief advantage of DCO for brand marketers is easier and faster personalisation. Using smart mechanisms throughout campaigns, they can maintain control of creativity generated by humans and user interaction flow, but allow machines to take on the heavy lifting. This boosts efficiency on multiple fronts: configuring myriad ad versions to suit differing tastes and driving results and conversions by hitting the golden trio of right user, time, and place.
Additionally, it’s worth noting that harnessing ML’s capacity for independent learning also helps continually increase targeting precision and impact, as well as giving marketers an ever-clearer picture of audiences that can be used to achieve greater engagement and cut-through.
What about consumers?
By enabling marketers to cater for unique interests, requirements, and contexts, DCO makes advertising experiences better on the consumer side. Users gain tailor-made ads that come as a highly relevant, engaging, and seamless part of cross-channel brand conversations and purchase journeys – rather than unwelcome interruptions. Moreover, because messages are based on data signals from interactions, they receive the positives of personalisation without having to share personal data; allowing more space to get to know and trust brands first.
Ultimately, DCO is the perfect balance of data and creativity. While the traditional view that creative should always be at the heart of campaigns still holds true, adding data-supported accuracy allows marketers to reach much further and strike the right chord for every user. In an age where consumers are increasingly distracted by vast tides of media from countless sources around the web, capitalising on its double strength opens up exciting possibilities for not only rising above the noise, but also delivering messages at mass scale and optimal efficiency without losing the personal, meaningful touch.