More and more agencies and brands are relying on machine learning these days to analyze mountains of data and provide insights they can use to better inform advertising campaigns. Using ML, artificial intelligence tools can recognize patterns in data gleaned from existing campaigns to see how ads are impacting customer engagement, purchase intent and conversion rates.
Rather than guess at what approach will work best to reach target audiences, brands can generate predictive models using ML and AI to identify optimal creative, content, placements and more to boost the effectiveness, accuracy and efficiency of their ad campaigns. Here, eight members of Forbes Agency Council explore the best ways to streamline ad creation and refine marketing strategies by leveraging ML ad tools.
1. Be Granular And Downstream With Your Data Inputs
Machine learning is still only as good as the data fed into it. The more granular and downstream the data you put into them, the more accurate these tools can be. Work to tie back signals indicating higher-revenue, closed customers or higher-scored leads to their sources—that will ensure the machine learning starts making audience, creative and ad decisions that are truly the best for your business. – Brian Walker, Statwax
2. Automate The Testing Of New And Remarketing Ad Campaigns
Marketers can leverage the built-in machine learning provided by the likes of Google and Facebook to rapidly test the effectiveness of ad creatives. The elimination of this manual process allows creative teams to remain focused on the creation of fresh ad designs based on what these technologies indicate are the best-performing ads. This can also be applied to new and remarketing ad campaigns. – Bernard May, National Positions
3. Identify Specific Demographics To Create Custom Audiences
Savvy marketers are able to create custom audiences through the use of machine learning ad tools. Being able to identify specific demographics through the use of this technology enables you to meet potential customers where they are in the sales funnel. Creating custom ads for custom audiences increases your reach and revenue, which ultimately improves your bottom line while staying on budget. – Adam Binder, Creative Click Media
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4. Gather Audience Insights To Target More Relevant Prospects
Gathering audience insights through these tools can allow you to target groups of prospects that are more relevant and adjust ads as needed to accompany an A/B testing strategy. Responsive search ads have also changed the game, adapting to a customer’s search intent and other factors to make ads as relevant as possible to individual consumers, leading to better results. – Michelle Abdow, Market Mentors, LLC
5. Learn From User Behavior Data In Your Brand’s Native App
The behavior exhibited by users within a brand’s native app is one of the most overlooked machine learning opportunities in marketing. Understanding a customer’s behaviors within a brand’s app can be incredibly valuable when it comes to ad campaign creation. Basically, the more you know about what a customer’s intent is, the more relevant the advertising can be. – Roger Hurni, Off Madison Ave
6. Optimize Ads Using The ML Tools Offered By Major Ad Platforms
Most of the major ad platforms, including Google, Facebook and TikTok, offer tools that utilize multiple creatives to find and optimize the best-performing ads. While these tools are not perfect, they allow you to quickly leverage machine learning to optimize ads and determine the best-performing combinations of ad copy, images and videos. – Brian Meert, AdvertiseMint
7. Try Out Different Types Of Creatives Beyond Traditional A/B Testing
Testing two creatives doesn’t always help you move the needle as fast as you need to. By being able to randomize headlines, body copy, images, video and other descriptions, you will be able to see what pulls the best and provides the most cost-effective result. – Christopher Tompkins, The Go! Agency
8. Ensure Ad Copy Relevance In Real Time With Responsive Search Ads
Responsive search ads not only facilitate evergreen, multivariate testing and target more efficiently, but they also adapt to a consumer’s search landscape in real time. Responsive search ads automatically generate different ad copy based on search intent and other factors to ensure ads are as relevant as possible. – Donna Robinson, Collective Measures