Streaming platforms are setting the standard for organizations looking to up their personalization game

Several years ago, The New York Times published an article shining a light on a major challenge that is also a stark reality for the advertising industry: people hate ads. This blanket statement is often believed by many leaders across industries who struggle with how to market and advertise their products and services to a population that, when given the option, will click ‘skip ad’ faster than they can blink.

But what if this widely accepted phenomenon is actually rooted in misunderstanding? Operating in the media and advertising industry for 22 years and being a regular digital buyer myself, it is my experience that consumers don’t hate ads – they hate ads that are not personalized.

Taking this one step further, today’s shoppers want to see ads as a tool to help them make conscious product and brand decisions.

For example, a buyer in the market for their first electric vehicle might consider themselves as an environmentalist and strongly believe their personal choices make a difference on a macro level. For others, it might be about the style, performance, and the technology, wanting to capitalize on the status symbol of being an early adopter of EVs. It’s hard for a generic “one-size-fits-all” ad to influence these contrasting personas.

What does this all mean? Consumers are constantly looking for solutions that will ultimately result in a purchase aligning to their personal aspirations, and ads are the tool that will get them there. To ensure this process is successful, organizations must prioritize experiences that cater to customers’ wants and needs.

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Streaming platforms pave the path to personalization

To break the repetitive cycle of advertising, enterprises will need to acquire a deeper understanding of their individual customers and commit to serving each one’s particular shopping needs.

This process is already in motion for several organizations – where the ads of the future have begun taking shape.

Consider that 82% of U.S. households with a television have at least one internet-connected device or platform, signifying that it would be wise for the brands to gravitate towards over-the-top (OTT) and connected TV (CTV) advertising for a more personalized reach.

Streaming platforms have started migrating to more personalized advertising methods. In some cases, ad placement can be altered within the programming to appeal to a specific viewer’s preference. For example, if a character is drinking a beverage in a scene, the type of beverage can be changed depending on the consumer. One viewer’s preference may render a soda, while another may show a sports or energy drink.

These creative advertising technologies can also personalize experiences by geographies. A prime example can be found in the restaurant industry. A chain that is popular in the United States may not exist or have relevance in Europe. With this technology, a film streaming in the U.S. can show a restaurant relevant to that geography, while the same movie streaming in Europe will show viewers similar restaurants that are popular there.

This level of technological impact is massive – shifting from individual personalization to mass personalization based on location, demographics, profession, and beyond. Increased sophistication with multiple levels of precision targeting has ushered in a deeper level of consumer understanding.

Migration is underway

While this technology has a promising future, organizations are still in the early stages of adoption – and the opportunity for growth and expansion is deeply rooted in the behavioral change of consumers. Just over a decade ago, there was no option to consume content via handheld devices. But modern consumers can watch content from their phones, tablets, and other devices across a dozen streaming apps.

These apps offer more opportunities to identify and analyze audiences, resulting in the continued advancement of advertising technology that is developed to capture a wealth of data. And while many organizations rely on first-party consumer data, third-party data and consumer graphs are an additional weapon in the arsenal to increase the accuracy of ad targeting. As the consumption patterns of viewers continue to expand and evolve, so will the methods of analyzing individual preferences.

Today, for example, content publishers and media houses have developed their own consumer graphs that assign anonymous identifiers to each household. Consumer graphs link and map all possible digital devices in the household consuming content through its platforms and thus enables the publishers to have a trail of consumers’ digital footprint for more accurate targeting.

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Data roadblocks to mass personalization

The road to picture-perfect personalization is long, and not without its challenges. Data accessibility and quality is one major roadblock that stands in the way of individualized advertising. Consumers themselves are multidimensional, and because of the link that exists across one individual’s online presence, ads that seem relevant might be far from it. For example, a consumer using the same device for work and leisure may signal that they want ads for something job-related, which in reality is not relevant to their personal shopper preferences. To fully understand the consumer identity – and differentiate between browsing for professional life and personal life – next level qualifications and additional data points make all the difference.

Fragmented data can alter consumer profiles, and in certain cases result in what is referred to as a household grab. This occurs when two members of the same family or household, each with their own preferences and digital identity, access social media through devices under the same network. In this situation, it is easy for the data to assume these preferences are part of one profile, leading to irrelevant ads for both consumers. In the future, this lack of identity by connecting multiple sources will be alleviated by artificial intelligence (AI) and machine learning (ML), which have the potential to offer data collection and data identity matching.

Another key to migration is upholding consumer privacy. Data collection can be a slippery slope, and technology’s role is to help organizations identify a target audience without violating their privacy. Data collection should be limited to items that reflect a consumer’s interest in buying a specific item. Anything beyond runs the risk of breaching consumer privacy, which can result in a loss of trust from customers and stakeholders.

Ad fatigue is an issue that spans industries and geographies – with many organizations fighting to break through the noise. Improving ad relevancy through targeted technology has the potential to dramatically reduce ad fatigue and improve user experiences.

Organizations should be focused on the quality of the data they are collecting, as well as prioritizing data collection that respects consumer privacy. If they do, it will become evident that people actually don’t hate ads, they want ads that enable them to make conscious product and brand decisions aligning with their personalized dreams and aspirations.