Leveraging artificial intelligence (AI) is now commonplace in marketing. Tools, platforms, and services put sophisticated audience targeting and segmentation tools at marketers’ fingertips, making it easier than ever to connect your products and services to customers.
As organizations grow more sophisticated in their adoption of AI, they can start to look beyond core uses cases and solutions such as the basic targeted Advertising tools offered by Google and Facebook. Today, consistently finding new applications of data and smart algorithms is essential to building and maintaining a competitive advantage.
It’s important because if you’re simply using AI to do the same as everyone else then your results won’t differentiate you from your competitors in the eyes of potential customers. On top of this, core AI marketing tools (such as Adwords or Facebook Advertising) are often described as "pay-to-win" – put simply, companies with bigger marketing budgets will generally get better results and take potential customers from smaller businesses. This is because they can afford to bid higher for the most important keywords.
Thinking smarter about alternative and emerging use cases for AI in marketing (or any business function) can help mitigate this. Here are a few ideas for getting ahead of the curve and ensuring your AI-driven marketing strategy is always evolving to become more efficient.
AI enables highly personalized design, meaning individual elements of advertising materials and marketing campaigns can be automatically tailored to specific audiences or even individuals. Individual elements of marketing campaigns – down to the style of design or the color schemes used – can be determined by algorithms to ensure they have the best likelihood of grabbing your audience's attention and prompting further engagement. Algorithms can then assess the performance of different combinations of design elements and audiences and determine where tweaks could bring better results.
For example, it may be possible to determine that younger potential customers engage more readily with very visual adverts and marketing materials, whereas older ones prefer more text or in-depth details about products and services. Advertising creatives then only need to put together one version of their assets, which can then be tailored by AI algorithms and automatically distributed to the correct Customer segments. Advertisers are already using tools such as Persado that use natural language algorithms to create customized wording for sales copy.
AI helps us to recognize and categorize Customer segments by their behavioral patterns, at scale. It can then optimize performance by monitoring how well different content performs against individual segments.
Computer vision technology gives computer software the ability to “see” – meaning they can understand visual information. One opportunity for marketers here is to scan the millions of images that are uploaded to social media platforms every day in order to better understand how and where products or services are being used. This gives marketers new ways of assessing factors such as market penetration and brand awareness. It can also be used to identify influencers who already have an association with your brand, leading to more authentic engagements.
Another powerful use case is trend analysis.
