Leveraging AI to Fill the ‘Creativity Gap’ With Results-Driven Advertising Ideas

Creative design and advertising spend optimization have never been more important at a time when social distancing and periodic lockdowns force consumers to make more online purchases.

Unfortunately, cash-strapped businesses with limited creative resources and budgets face long odds when competing for consumer mindshare against larger, more established brands. In April 2021, Facebook announced an astonishing 46 percent increase in revenue versus a year ago, attributed to a 30 percent increase in the average price per ad, and a 12 percent increase in the number of ads displayed. This means that brands have to work harder, and pay more, to stand out among its 10 million advertisers.

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So how can e-commerce start-ups use AI to level the playing field, and compete for customers’ attention during this critical period? 

If you are drawing a creativity blank, you can leverage AI and machine learning to generate online video ads within minutes, to understand how a particular ad performed and work out which angles resonate with audiences. Here’s some tips and learnings to help you deliver on a tight testing budget and timeframe:

1.  It’s not about variations – it’s about new ideas in advertising

Testing small variations of the same ad will have a small impact and are easy to do.

Testing large variations, or better yet trying totally different ideas, will have a larger impact but is a laborious task. On the plus side, if you do enough variant testing, both approaches are guaranteed to deliver.

Small variations essentially exploit statistical anomalies in what resonates with people, yielding small changes in outcomes that might be magnified over time or as the number of people scales. Google famously tested 41 different colours for search results links, and the shade of blue they settled on earned them an extra $200M a year in advertising revenue.

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For smaller brands, rigorously testing every micro factor in your ads will burn a lot of ad budget and design time and may only deliver a few percentage points of uplift at your scale. That is why testing whole new ad ideas can be so powerful – if each new ad idea is distinct enough to resonate with a whole new group of people, Facebook can easily find others like them so you can scale your spend while improving your ROAS (Return On Ad Spend).

2.  Ads are just noise unless they are meaningful

In the pursuit of new ideas, creative variety and ROAS, it’s crucial to remember that you are still a business trying to find compelling ways to build relationships with your customers. It’s very easy to vary your ads too much and find yourself sounding like a competitor or worse, misrepresenting yourself or undermining your brand.

With machine-generated creative tools, it’s now possible to generate not just mindless variations but to genuinely be creative, with unique, meaningful ideas, at scale. With your brand guidelines and product facts set up and locked, meaningful creation then starts with your copy.

By leveraging AI you can automatically generate new ways of describing your products and pitching your purpose. You can then automatically generate video ads that introduce compelling narrative – a story that grabs attention, lands a benefit and drives towards conversion. All of this can be achieved by slicing and remixing your existing assets and finding new assets that align with your story options.

3.  Collaboration is the name of the game

Getting to any strong creative output is nearly always a collaborative process –any colleague should be able to contribute at any moment to existing collateral, from anywhere in the world.

Creativity is subjective – you won’t like everything a machine generates just like you don’t like everything your agency presents to you, or even your own ideas. One of the reasons machine-generated creative works so well is that it isn’t totally machine generated. Businesses provide the brief and make the edits; it learns from them to get the results that they want.

One key to making this process collaborative is fast generation of copy and video, literally in minutes. Once you have the right AI creative platform in place, you just provide your assets and type in the copy ideas that guide the ads you want to make.

4.  If it is broken, learn from it and fix it

At the end of the day, the most frustrating part of making ads, for both the performance marketers and creative designers, is ads you spend hours creating and campaigns you optimize that don’t work.

The thing is, because testing is the only guaranteed way to consistently improve, it’s a law of nature that your first ads deliver suboptimal performance, leading to a lot of wasted time, wasted resources, spent emotional energy and angry emails unless you continuously learn

Machine-generated creative provides any business with a secret weapon – not only making creation fast and low cost, but also predicting what might work based on what’s worked in the past. This way, you are no longer spending all your time and money making ads for most of them to fail and be paused, never to be seen again.

You generate an advertising in minutes, run it, and if it fails, it fails fast and you learn from it, so it’s no real loss.

Furthermore, you save money on your testing because you don’t need to test every variation. Lastly, every single ad you run just helps you hone in on what really matters for your customers.

 After all, isn’t that what marketing and advertising are all about?