Cortex unlocks the full power of the world’s best brands by using AI to discover what inspires consumers to action.
We leverage deep learning to help creative leaders at companies like Marriott, Heineken, Oreo, Toyota, and Oribe find actionable insights into what visual elements drive the success of products and the marketing that promotes them.
Interest in artificial Intelligence’s impact on content marketing is heating up as the technology’s capabilities are beginning to be understood and more broadly implemented by marketers. One of the applications generating the most excitement and investment is AI tools for visuals due to their huge benefits to marketers, as well as their large growth potential. Since investment in the space is expected to grow 300% and there will inevitably be a myriad of options for marketers to choose from moving forward.
Marketers are well aware that leveraging these powerful tools to their advantage will be key to their success in the future, but with so many tools available and every company under the sun claiming to use AI, where does one begin evaluating which solutions are best? This guide will break down the visual marketing landscape, what solutions are out there and where in your workflow they can provide the most leverage, and how to separate real innovative technology from those using AI as a marketing buzzword.
Artificial intelligence in visual marketing it’s the science of quantifying and replicating the processes of human intelligence. It is not a single technology, but rather a collection of technologies such as:
Computer Vision: A computer’s ability to “see” and identify visual objects.
AI solutions consist of some or all of these technologies working together to find patterns and connections within massive data sets (also called Big Data,) and apply these patterns to perform tasks and processes at a speed, scale, and level of efficiency not possible before.
When evaluating working with any marketing technology vendor it is critical to understand where in their stack they have implemented AI tools, the level of automation they provide, and most importantly how those tools will deliver actionable insights and increased results. Within visual marketing, current AI tools are delivering value in the realms of strategy, content creation, and deployment.
Success in visual marketing starts with a strong understanding of your audience, your competition and their efforts to reach the same or similar audience, and what kinds of content best inspires that audience to take action in ways that move the needle for your business. AI tools in this stage of the marketing process are best used for informing your understanding of your audience, competitors, and content positioning. Armed with these insights, you’ll be able to create the most impactful content for your data, not hunches.
Understanding Visuals for your Global brand
Of all the Deep Learning, Social Listening are some of the most common and well understood in the marketing community. Social Listening is different from social monitoring in that monitoring is simply seeing what people are saying about their company, whereas social listening tracks conversations around specific phrases, words, or global brands, and then leveraging that data to find opportunities or create specialized content for specific audiences. These capabilities are a powerful way to interact with audiences in real time, as well as tailor your voice to better connect with them.
Cortex takes this a step further than competitors by baking these insights into your content recommendations. Some of these products allow you to track industries, communities, competitors, and influencers for a more complete picture of your landscape. The most effective ones will give you actionable data about your audience and the other players that can inform your messaging, help you respond to opportunities, and inform what content to make and when.
Tracking and analyzing competitors is one of the areas of strategic planning where Artificial Intelligence has made the biggest improvement. Without Cortex’s ability to scrape and analyze massive data sets any analysis on global brands are either highly subjective and qualitative, or manually grueling. But with AI and deep learning, you can effectively run all the same analysis that you perform for your own pages on competitors as well. This gives savvy marketers a huge advantage by being able to see what is working and integrate the best strategies and techniques into their own strategy.
Data Insight Content Optimization
Once you understand your audience, the landscape, and your competitors strengths and weaknesses, planning the best content to deliver to them becomes the last piece of a social media strategy. Although social media is continuing to trend more visual, getting the right mix of text, photo, and video for your audience can make a big difference in performance.
Beyond that, what is in the photos and videos makes a huge difference in performance. In a study we did for Visit Utah we found that photos with Fir trees performed 53% better than average, while photos of families performed 30% below average.
Going into this level of granularity reveals surprising insights into how to optimize your social content, and is practically impossible to get without deep analysis of large data sets.
With Artificial Intelligence saving time on strategic planning and reporting, marketers can focus more of their efforts on creating high quality content. However content marketing is difficult to scale, especially for smaller teams with limited resources. While AI is not at the point of being able to write there is some content that can be completely automated, and tools to aid marketers in their creative process to make better content at speed and scale.
Some of the most common automated content creators are chatbots and virtual assistants. Chatbots are services performed by AI that take place over chat interfaces. They have become commonplace in e-commerce sites, in customer service, and on messaging platforms like Facebook Messenger. Some examples include:
Although one of the newest applications for AI generating full length publishing content making its way into the mainstream, and from a content scaling standpoint it is one of the most exciting. Machines are already totally automating content such as earnings reports, news headlines, and interview or webinar transcriptions.
For content that can’t be completely automated, here are some tools to help create it quickly and easily tailoring it to specific audiences.
Visual Search: Use photos to search for similar photos to make creating posts easy, or fill out other assets to be more visually appealing.
Predictive Audiences: Advanced customer data that can predict Lifetime Value, probability of purchase, predict likelihood of customers taking action, alerts for high risk of churn, and more. In the context of social, predictive audiences can inform marketers what content audiences need to see at various stages of the sales funnel, and where best to deliver it to them
Content Recommendations: Want to know what colors, objects, keywords, and hashtags inspire your audience to take action? Tools like Foresight look at trends on your page, your competitor's pages, and let you know what types of content resonate with your audience.
If you’ve made it this far you now have a deep understanding of what your audience wants, and you’ve created top notch content for them and are eagerly waiting to get it out there. However, to get the most out of all your hard work, that content needs to be served to your audience at the right time, on the right channel.
Knowing how often to post and when is one of the most hotly debated topics among CMOs, with as “answers” as possibilities. The truth is that cadence and timing are different for every audience, and the only way to know definitively is to look at the data.
Once all the content has been scheduled, the final question for marketers is how to allocate their promotional budget. Instead of dividing it up evenly by post or only promoting certain kinds of content, with machine learning you can look holistically at what posts are the most effective to boost based on content, timing, competition, and audience. Then, the computer will intelligently allocate your visual marketing spend to maximize performance for your budget.
While social media marketers won’t be completely turning over the reins to machines anytime in the near future, social media managers who embrace AI and Machine learning tools have a massive competitive advantage over those who don’t. Most importantly, content marketers can finally apply the same level of scientific rigor to their work as their other business and engineering counterparts and generate huge value for their customers and their company in the process.