Mediaboss Marketing

Increasingly-sophisticated AI tools are driving a renewed focus on dynamic creative optimisation, as marketers look to further leverage their datasets. To that end, in this contributed article, John Tigg, EVP, global client partnerships at Yieldmo, outlines the five key ingredients for effective use of machine learning in optimising creative formats, alongside notable challenges in the field.

Advertisers spend a lot of time and resources designing the perfect creative to capture the attention of their target audience. Frequently, however, they leave the very last and critically important step - where the creative and the user finally interact - to chance. This is the moment at which the creative format is determined, and its also the vital moment that determines whether an advertisers hard work and planning pays off as a good user experience.

The right creative format amplifies, without altering, the core underlying creative to produce a unique interactive experience. An intelligent creative format drives engagement with customers and improves a variety of key advertiser KPIs, including brand awareness and recall, attention, consideration, shoppability, site visits, and more.

For every opportunity that exists to serve a creative to a user, there are many possible creative format experiences. The final form of the creative format should not be the same in every scenario; it should be a product of the multitude of factors that converge at the moment the user and the creative meet.

The right creative format selection is everything when it comes to a successful user experience, but its also a challenge for advertisers: How does one choose the optimal format for their creative, given that millions of permutations of different intersecting factors define every ad opportunity?

Today, this last mile of optimisation is an interesting problem that machine learning (ML) is well-positioned to help solve. Lets examine why thats the case and what marketers need to know to ensure theyre building or selecting strong tools capable of elevating their creative performance.

Every ad opportunity represents a unique intersection of the advertiser, the context, and the user. Each of these components is defined by a collection of attributes, each of which can have hundreds, thousands, or millions of values. Why so many values? Consider:

The complexity of each ad opportunity positions machine learning (ML) as an ideal solution when it comes to creative format optimisation. Machine learning, a subset of AI, is an exciting field that allows us to make increasingly accurate multivariate predictions about what will happen using large volumes of historical data. It can find patterns in this data, make rapid and accurate decisions, and is effective at overcoming ambiguity and sparsity. Machine learning can uncover unexpected and unspecified truth conditions (features) and can make good predictions under novel circumstances.

These unexpected and unspecified features are especially powerful when comparing ML to the human-driven optimisation we often see in the ad tech industry. Machine learning provides a flexible toolbox for many types of problems, and the problem of choosing the optimal creative format for each ad opportunity is no exception.

To deliver the best format experience for your creative every time your ad serves, there are five critical ingredients that should be present within your dynamic creative optimisation tool, as derived from our whitepaper, "Elevating Creative Performance with Dynamic Format Optimization (DFO) and Artificial Intelligence (AI)".

This might sound obvious, but the first essential ingredient to strong creative format optimisation is ensuring the tool has access to a broad selection of formats that can independently improve advertiser outcomes at serve time.

For a ML model to predict the best format experience, you must have a mechanism to process, transform, and store large volumes of data. The data used to train the model must meet the following criteria:

To model successfully, a tool must start with a clear use case with a well understood and defined problem. In our case, thats determining the best creative format to serve in real time. To build a reliable, consistent, and explainable process for model selection, you must have a process to:

To ensure your models are up to date, you need a robust infrastructure that can automate pipelines and collect, prepare, and score training data. Among other features, this infrastructure should be able to assemble customised models for new campaigns, refresh models at least daily, update models based on recent performance, track versions and monitor models, and provide for a robust experimentation framework (i.e., a/b/c/d tests).

Finally, to deploy predictions into a real-time decisioning system, advertisers should build or look for tools that include the following features:

The right creative format can significantly impact the success of advertising campaigns. By applying machine learning (ML) to the creative format challenge, you can optimise the creative format for each ad opportunity automatically and improve user engagement with your brand by delivering the best creative experience at every unique moment in time, to each individual customer.

Whether you are looking to build your own ML capabilities or leverage an out-of-the-box solution, youll want to ensure your solution covers the above key ingredients. If youre looking to spin up something lighter weight but still capture a lot of value from format optimisation, there are some great options out there:

Most importantly, if you dont know who your exchange partners are, find out. If you dont know what value your exchanges are providing you, ask. If they cant prove their value, replace them with an exchange that is consistently building and innovating to help you succeed.

Finally, keep testing! When budgets get tight, make sure to fight for your testing budgets. No one knows what the next year will hold, but when the industry and economy changes (as it always does), you dont want to be stuck with solutions that have lost their edge.

Original post:
How Marketers Can Elevate Creative Performance with AI-Driven Format Optimisation - ExchangeWire