Machine Learning & Advertising
So much of the digital advertising landscape is changing. In the wake of automation and AI, it’s no surprise that the advertising world is starting to feel the effects of this change. One big change in the industry is machine learning. But what exactly is machine learning, and what could it possibly have anything to do with advertising online?
Let’s dive into what machine learning is and some ideas for advertising that involve machine learning.
What is Machine Learning?
In the context of advertising, machine learning is the process where ad technologies will take in data, analyze that data, and generate conclusions from that data in order to improve a task function. Machine learning can be summarized as the way that advertising technology learns more information to help advertisers make choices.
5 Machine Learning Ideas in Advertising
It is important to understand “What is A/B testing” in order to make an impression in the audience’s mind. The ultimate goal of A/B testing is to reach a level of optimization. This allows businesses to continually improve campaigns in order to capture more leads and increase their conversion rate.
1. A/B Testing of Ad Creatives
In the old days, building ad creative that was effective involve a lot of human work. Now, machine learning technology can essentially do away with A/B testing by identifying which of your ad creatives are actually performing well and scoring elements of the entire buyer’s journey, from the beginning of the funnel all the way down.
2. Analyzing and Optimizing of Campaigns Towards a Goal
In addition to taking on the task of A/B testing, machine learning can help advertisers optimize their campaigns in the context of a goal. Since machine vision makes it possible to collect more data than ever before, you can pinpoint specific data points to make decisions on how to increase conversions, gain clicks, etc.
3. Identifying Contextually Relevant Content
In addition to being well-crafted in a creative context, an ad needs to run on the proper platform with the right targeting methods at the exact right time. Machine learning can improve this process by contextual relevance– analyzing pages that perform better at night with a specific color scheme, during the weekend with specific imagery, etc.
4. Customization / Personalization of Ad Creatives
An ad’s media, typeface, and CTA are all different creative elements that lead to users engaging or losing interest.
Machine learning does not only involve very strictly-measured data. Predictive analytics systems can help develop better creative for advertisers by analyzing visual media in order to find creative choices that resonate the most with consumers.
5. Modification of Programmatic Bidding Algorithms
Machine learning can help with a “bring your own algorithm” approach. Not all impressions in programmatic advertising are worth their cost– still, some are. Machine learning in demand-side platforms can analyze these impressions to make ideal bids and optimizations that once was the task of quick-thinking and experienced buyers.
Gourmet Ads and Programmatic Bidding
Gourmet Ads is proud to have a thumb on the pulse of new innovations in the digital marketing and advertising industries. We take machine learning very seriously, especially through the context of Smart Deals.
Smart Deals are PMPs (Private Marketplaces) that are built with machine learning in the Appnexus Ad Server. These Deals are set using targeted and specific KPIs in real-time. In the past, Gourmet Ads has used historical data to efficiently surface impressions into Deals. Now, we use Smart Deals to automate the process in the Ad Server.
We’re firm believers in automated deals and programmatic advertising. If you’re interested in how Gourmet Ads can predict your campaign’s predicted viewability, video completion rate, and video viewability rate, download our media kit today to see exactly how we work with audiences and data segments.
