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Using AI Technology to Create Smarter Ads

Using AI Technology to Create Smarter Ads.png

Thanks to new technologies such as artificial intelligence (AI) and automation, advertising is no longer a subjective, ambiguous process that can succeed or fail according to the whims of consumer trends and tastes. With AI, marketers can develop "smart ads" that can accurately pinpoint the preferences of designated customer segments, meaning ads can be more highly customized than ever before.

What is a Smart Ad?

Smart ads use cutting-edge technology to take the guesswork out of each stage of the marketing process, from the moment ideas are created and design choices made, to campaign optimization through selective demographic targeting. By using AI-powered machine learning, marketers can now collect, process and analyze massive volumes of data, then harness valuable insights from this data to create a viable set of predictive stratagems. These informed stratagems can be used in every stage of the marketing campaign -- from the first stages of planning to full deployment and subsequent optimization.

Smart Ads vs. Traditional Advertising

In traditional ad campaigns, marketers often have to test market an idea, concept or product to gauge public reaction. Test marketing represents a huge investment of both time and money. In addition, due to rapidly shifting paradigms in public taste and consumer trends it isn't always accurate.

Traditional advertising is based on a reactive approach -- i.e. gauging customer reaction through media ads and commercials. According to recent studies, however, 84 percent of millennials dislike and distrust traditional advertising because they feel it doesn't engage them on a personal level. Likewise, in the UK, the top 50 ad agencies are seeing their lowest profits in seven years.

According to eMarketer, digital media ad spending is slated to reach $113.18 billion by 2020, while mobile ad spending will reach $86.84bn by 2020. Even more importantly, half of all digital ad spending will be used toward video, rich media and in-feed native advertising, which are ideal formats for smart ads. Likewise, industry analysts predict that by 2018 more than 300 million smartphones will have AI/machine-learning capabilities.

These are the reasons that marketers are moving from traditional methods such as A/B market testing, which uses consumers to compare different versions of a web page, to personalization marketing, which uses data collection and analytics to create more customized marketing strategies. These strategies use high-value segmentation to target customers according to the data collected.

With AI and machine learning, personalization marketing has reached a whole new level of effectiveness and accuracy. When used together, these two technologies work in tandem to optimize performance by creating ads that are more highly targeted, customized and relevant to the desired audience demographic.

Four Key Tools for Creating Smart Ads

1. Machine Learning and AI: Artificial Intelligence is a term that's often used interchangeably with machine learning, but the two terms refer to different aspects of big data and smart analytics. Essentially, AI is the broad, overall concept of intelligent behavior in machines, whereas machine learning is a particular application of AI, based on the concept of giving machines access to data and allowing them to process it themselves.

Machine learning is a process of data analysis that uses algorithms to build analytical models. In turn, these models yield informative data that can be processed, analyzed and harnessed into target marketing strategies.

In essence, machine learning enables computers to detect patterns in data that identify consumer trends and preferences, without having to be programmed beforehand to find these specific elements. This is done by coding computers so that they recognize and classify elements -- or pieces of information -- in the same way that humans would.

2. Data: Machine learning culls data from the internet, then processes and analyzes it to generate valuable insights that can be harnessed to create predictive analytics. In turn, this can help marketers make more accurate decisions and create highly-customized strategies for their target marketing campaigns.

Through AI and machine learning, a computer system can recognize images, statistics, and other elements, and associate them with specific consumer segments. By adding a feedback loop to the system, marketers can enable the computer system to recognize when its predictions are correct or incorrect (and if incorrect, why), so that the system can continuously modify and fine-tune its approach to assessing information.

3. Automation: Automation, when used with AI and machine learning, can be applied to a wealth of creative, innovative marketing strategies. One example of this is email marketing automation, which is an automated method of sending emails to a targeted audience segment, based on predefined triggers developed by AI analytics. When these triggers are activated via email automation software, the emails are sent out at regularly scheduled intervals to specific consumer segments -- all with a simple mouse click.

Another example of automation marketing is the automated creation of content -- content that's written by a computer but reads as if it was drafted by a human being. For example, the Associated Press is currently using AI and machine learning to enable computer systems to pull updated statistics and highlights from minor league baseball games and self-write articles about them. These computer-written articles read as if they were written by a human writer, thanks to the help of Wordsmith, a computer platform that feeds the computer with the same word stylings that people would use.

This technology can also enable systems to create online content and advertisements that are entirely self-written by the computer. This not only saves money and time; it also creates content and ads that are customized and targeted to your desired demographic with pinpoint accuracy.

Thanks to developments in natural language processing (NLP), automated technology can also be implemented in ads so that consumers can chat with bots if they have questions about a product. These bots are created with AI elements so that they can accurately mimic human speech patterns.

4. Creative Relevance: Relevance can make or break a marketing campaign. In much the same way as Google prioritizes keywords in websites, ad-rich sites such as Facebook now assign relevance scores to their advertisements. This predictive analytics help gauge the amount of interaction -- both positive and negative -- that the ad will receive. Likewise, while relevance is the heart of an advertising campaign, one could say that creativity is its soul; it's the force that sets the campaign apart and makes it memorable.

Thanks to the highly sensitive receptors in machine learning, a computer system can recognize when a song is happy or sad, or when a story is cheerful or depressing. Relative to marketing, a smart system can also identify when a person is writing a positive or negative review of a product or concept, and can also sense when marketing strategies are being received in a positive or negative way. With AI and machine learning, a system can also create predictive analytics that is even more finely-tuned and accurate than the standard relevance scores such as those currently used by websites. This analytics can also harness visual and graphics preferences -- information that can help marketers exercise their full creativity in producing innovative, relative advertising.

Targeting Your Audience with AI

AI provides tools that have been hitherto unsurpassed in marketing -- tools that can be used from for every stage of the marketing process. As an example, consider the design elements chosen at the very beginning of the creative production stage. These elements include colors, graphics and visual objects that appeal to certain genders, lifestyles and other audience segments. By using AI and machine learning platforms, you can make educated decisions in choosing which creative options will produce the best results in your campaign objectives; and AI can enable you to make these informed decisions before you even invest a penny on actual advertising.

Best of all, AI can provide updated information that is constantly fresh and new. This means that, over time, as your ads show signs of performance deterioration, AI can provide the updated information you need to keep your ads relevant to the ever-changing tastes of your audience.

Marketing should never be stagnant -- and AI keeps your marketing strategies fresh and contemporary to match the changing trends and tastes of consumers. The machine learning that fuels AI regularly picks up new data and insights in a continuous cycle of self-learning and imparts this information to you. This ensures that your marketing campaigns will always perform at peak level.

Benefits of Using Smart Ads

Saving Time: Smart ads can be created much more quickly and easily, thanks to predictive analytics and information provided by the computer's AI platform. This significantly streamlines the ad creating process and mitigates many hours of employee labor. Comparatively speaking, test marketing, A/B testing and other ad campaign strategies can take weeks to complete, plus hours of in-house work in collecting and processing data.

Smarter Resourcing: Smart ads use little or no company resources because all of the informed data and predictive analytics are self-generated by the computer. Employees don't even need to feed info into the system because it recognizes valuable, applicable consumer information on its own and provides it without prompting.

Reducing Marketing Spend: Smart ads not only reduce the amount spent on marketing; they can also help businesses spend their marketing dollars more efficiently for a higher ROI.

Smart ads are rapidly revolutionizing advertising by making marketing more efficient and customized than ever before. In the end, more customized marketing results in a larger consumer base, greater exposure for your product and service, and a highly-targeted advertising audience that will, in turn, be more receptive to your message and brand.

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