If you have a product to advertise, you want your advertising efforts to bring unquestionable and measurable results. And with the cookieless future fast approaching, it’s vital to test modern technologies now, to keep or improve those results. You don’t want to be left behind.
New deep learning-based AI solutions are much more efficient than standard machine learning AI-based approaches. By helping marketers build a segment of one for a more detailed customer segmentation, this new technology offers more opportunities for advertisers to convert window shoppers to buyers through personal advertising. They are also designed to respect the needs and privacy of internet users with non-intrusive, privacy-compliant advertising.
Here we give you an overview of deep learning, and how it can help your advertising strategy.
What is deep learning?
Deep learning is an evolution of standard machine learning technology. It structures algorithms in three layers, known collectively as the artificial neural network (ANN). A stand-out feature of deep learning is its ability to work with large, complicated, or even unstructured datasets, from which each algorithmic layer can extract more complex features. And because the ANN mimics how a human brain works with information processing and decision making, it can attempt many different things before making a final decision.
- 1st layer – places a user into a specific group
- 2nd layer – defines specific niches or interests
- 3rd layer – assigns the user to the correct stage of the funnel
One further advantage of deep learning, as opposed to standard machine learning, is the algorithms’ ability to identify patterns without pre-set parameters determined by a human operator. This means it can work with human supervision, far more flexibly than legacy solutions.
Deep learning in advertising
The ultimate goal of deep learning is to make online ad experiences more meaningful for users and allow marketers to apply more granular segmentation while keeping privacy intact.
By using more powerful algorithms, it can offer unmatched precision and scale when it comes to targeted advertising.
This technology makes it possible for marketers to model user behavior and intent based on hundreds of anonymized metrics along with cross-platform activity and behavior comparison, and also hidden data, such as time between viewed products or the sequence of pages visited. The algorithm then analyzes this data to interpret exactly what the user was doing and can predict what products they will most likely be interested in.
It – and can – therefore provide potential buyers with deeply personalized results and tailored product offers.
For advertisers, deep learning also addresses the biggest challenge in the online advertising industry – optimizing marketing budget and ad expenditure across platforms. The effective targeting made possible by deep learning means the budget is spent only on users who are truly interested in a brand’s message, which results in more completed views and helps lower the cost per completed view (CPCV).
For example, deep learning helped a company in the fashion sector provide high levels of personalization and engagement with the right audience following its acquisition of a third-party brand. Thanks to deep learning, a three-month video ad campaign had a 4x greater reach, more than 6x higher user engagement (CTR), and 3.9 million completed video views with an average of 80% viewability.
Deep learning and the marketing funnel
The application of deep learning to retargeting campaigns is already well known and very successful. An e-commerce platform in the fashion industry leveraged its power for a remarketing campaign and gained an 18% uplift in return on advertising spend (ROAS), which led to a 66% increase in average order value (AOV) and a 200% increase in revenue.
However, retargeting is not the only string to deep learning’s bow. Not only can deep learning algorithms use first-party data and incorporate privacy to target the entire marketing funnel, but this powerful technology is also capable of accurately assessing what stage of the funnel the user is in, and then determine which name should be shown.
- New to the brand – aspirational content to strengthen their first impression
- Product research stage – informational ad content that tells them more about specific products
- Ready to buy – presented with the right product to lead them to quick conversion
Because deep learning is able to take into account different aspects of the context to select the perfect placement to better fit each opportunity, this allows for the precise and scalable targeting of audiences interested in a brand’s content.
Deep learning was instrumental in helping a company in the automotive sector maximize reach of a geo-targeted CTV and OTT campaign. By identifying the top context categories and targeting high-quality platforms, 96% of measured impressions were viewed and the cost per view was 25% lower than the industry average.
This aspect of deep learning completely revolutionizes the way advertisers can think about marketing campaigns, because the solutions based on this modern technology, helps improve campaigns with different goals. It also changes the meaning of the word ‘conversion’ from basic monetization to continuously building durable brand awareness and maintaining deeper connections with potential customers at every stage of their journey through the funnel.
Make testing new technology part of your plans
Deep learning technology is more effective than standard solutions.
However, if brands want to optimize their campaign outcomes both now, and in the cookieless future, they need to begin reviewing their current processes and investigate the solutions and tools that adtech providers are currently working on.
A partner that can prove the effectiveness of their tools and solutions is the one brands should be trusting.
How RTB House can help you
RTB House’s deep learning-based AI solution has been working hard since 2017. It is an award-winning technology and has recently been awarded The Drum Award for Digital Advertising in the “Best Overall Technology for Programmatic Trading (buy-side).” RTB actively uses deep learning algorithms in 100% of their campaigns, and to date, it has been used in more than 3000 campaigns in over 70 markets for some of the world’s biggest brands, delivering over $ 25 billion in conversion value.
Contact RTB House today to discover how you can future-proof your business by utilizing Deep Learning as part of your digital media campaign.