Unlocking Advertising Potential With the Power of Machine Learning

By Ian Sharpe On Mar 13, 2020

Capturing and maintaining consumers’ short attention span is becoming increasingly difficult, especially with the rise of multi-screening. It was recently reported that 72% of people aged 16-24 use social media whilst they watch TV. This demonstrates how ingrained multi-screening behavior has become, particularly for Gen Z consumers.

In today’s market where consumer attention is divided across multiple platforms and formats, only the most engaging and relevant advertising will resonate with audiences. Businesses are beginning to recognize the number of missed opportunities from non-personalized advertising, after seeing more and more traditional ads falling at the wayside.

What’s more, online videos will make up more than 82% of all consumer internet traffic by 2022 – 15 times higher than it was in 2017. With the continued rise in online consumption, more businesses are building Video into their Marketing strategy to build sales, brand awareness, trust, and establish an engaged customer base. The need to retain consumers’ attention and break through the noise with personalized advertising is still at an all-time high.

Getting Personal

Consumers are exposed to an average of 4,000 to 10,000 ads per day, which highlights that they are bombarded by a bewildering array of messaging on a routine basis. As a result, businesses need to consider how they can be heard through the noise, that is, how they can make themselves relevant and worthwhile. It has been reported that 56% of consumers are likely to purchase from a business that addresses them by name, while 58% will do the same if the business suggests products based on past or recent purchases.

Personalization is a powerful tool in developing video ads that create consumer engagement. It effectively allows businesses to target individuals by considering the context of their consumers, such as their location, age, buying habits or favorite brands. This type of targeted advertising also generates higher conversions, with consumers two times more likely to click-through to a video ad featuring an unknown brand if it was tailored to their preferences.

Personalized advertising not only leads to increased sales but also happier consumers. When presented with video ads that are customized to them, consumers feel better connected to a business. There is a reason, after all, that one of the dominant forces in this advertising world is called YouTube. There’s an element of feeling understood and valued, which can create a rich and meaningful relationship with customers, drive retention and encourage long-term loyalty.

Personalization has the potential to deliver five to eight times the return on advertising spend and can enhance Sales by 10% or more. Leveraging personalization for key advertising messages needs to be a vital part of a business’ strategy, especially when used in conjunction with the wider Marketing campaign. This has everything to do with good quality data and the way businesses use it.

Taking Personalization to the Next Level

Now personalized advertising isn’t just desirable, but a requirement from the perspective of businesses and their customers. This requires significant amounts of data to learn about consumers and their buying habits. With a constant stream of news concerning data collection or data misuse, some people are skeptical over the use of their personal data. However, 52% of consumers would willingly share their data in return for relevant product recommendations or personalized advertising experiences. This demonstrates that as long as there are tangible benefits (and permissions) involved, personalized Video Advertising can encourage consumers to act.

Businesses also need to consider if they are using their data to its fullest potential. With the power of revolutionary Machine Learning tools, they can now process more data that will help to better understand consumers at an individual level and serve highly relevant video ads. Gone are the days where businesses could spend what felt like months trawling through endless streams of data, heralding a welcome advancement in Machine Learning to help boost customer engagement in just a fraction of the time.

Machine Learning tools are trained to find patterns from historical data, including online shopping behavior, to predict the best outcome and what product the consumer wants to buy next. The resulting video ads are tailored to each individual and every new outcome produces feedback for the model to improve its future performance. As Machine Learning technologies continue to evolve, businesses will find new applications to further optimize operations and promote video ad innovation.

Transforming the Advertising Landscape

Consumers are inundated with content and the only way for businesses to effectively stand out is to offer personalized video advertising content. The biggest advantage of personalized ads is that they allow businesses to effectively target existing and prospective consumers, boosting the level of engagement by appealing to their likes, needs, interest and other buying preferences. It also enhances conversions, with personalized ads performing 128% better in terms of click-through rate.

However, in order to succeed with personalization, businesses must leverage data holistically to build a better understanding of individual consumers and their buying behavior. Machine Learning can do the majority of the heavy lifting, not to mention helping businesses save on costs. It can often be the difference between successful personalized advertising and video ads that fail to meet the grade.