The growth of Social Media in the past decade has been swift and unprecedented. Companies of every kind now engage with customers on various platforms to create communities of like-minded fans and followers, and get a competitive advantage. Meanwhile, the vast amount of data that brands now have about audiences and their behaviors has opened up new opportunities for forward thinking Marketers.
Marketing teams understand that in order to effectively target consumers, they have to know who their consumers are, what their consumers are consuming, how they are consuming it and how their product fits in the mix. With recent developments in artificial intelligence and machine learning these consumer insights have become easier to access than ever.
One area which holds great promise is the field of Computer Vision. This branch of artificial intelligence mimics human perception of visual data and can quickly identify, classify, and categorize said data. These algorithms can understand and describe the elements within an image or video and convert them into accurate insights using machine learning techniques. This methodology has a broad range of uses across several industries.
In Food Processing for example, Computer Vision can identify which flavors and colors are selling best based on images captured from a supermarket shelf. In Logistics, Computer Vision is transforming the way companies transport, store and deliver merchandise. And in Medicine, Doctors are using Computer Vision to identify, diagnose, and treat diseases by being able to read, analyze and understand thousands of x-rays in fractions of a second.
Computer Vision and Social Media
Pictures and Videos are crucial elements in Brand Communication and this requirement has only increased with the rise of social media. According to one study, the majority of people, over 65 percent, describe themselves as visual learners , meaning they extract more information from what they see rather than what they read.
Major product breakthroughs in Computer Vision for Marketing arrived around 2017, a time when organic reach was plummeting and Marketers were struggling to get attention. Social Media had become huge and unwieldy. Consumers were sharing millions of images every second, live-stream went mainstream, and content was being produced like never before.
Any Marketer spending hours combing through social media to find ideas worth posting, at some point would begin to ask , how exactly are images and video clips ultimately selected for posting? What makes certain visual posts engaging for the audience? And how can I be sure if my post is going to take off?
Knowing what works is tough, and relies on educated guessing, which is most often, unreliable. Computer Vision promises to remove the human bias and guesswork involved making those creative decisions.
Here is how…
Computer Vision tools like the one we leverage for our clients at HelloScribe can ingest real-time image and video data along with metadata such as user reactions (likes, shares) and hashtags, and cross reference against a dataset of 35,000 brands,each with 3 years worth of Social Media image and video data. It then assigns a quality score which answers the question; what post will drive the most engagement?’
This approach offers a number of unique advantages. Key among them the fact that ‘Marketers can now create an experience customized to how their customers prefer to engage with brands in their category. By using AI to make more informed decisions, they can tap into a centralized repository of AI-derived knowledge, instead of relying on their own experience, bias, or memory to decide what content will work best for each channel.
How Successful Marketers use Computer Vision
There are several companies reaping the benefits of Social Media AI. And one of them is Coca Cola. A recent case study outlined how they use Computer Vision to analyse social media and understand where, when and how their customers like to consume their products, and which products are more popular in different markets. With over 90% of their new consumers making purchase decisions based on social media content, understanding how these millions of customers are discussing and interacting with their brands on platforms like Facebook, Twitter and Instagram is a key part of their strategy.
Coca-Cola analysed engagement with over 120,000 pieces of social content to understand the demographics and behavior of its customers and those discussing the products. Using Computer Vision to process these social media posts, as well as deeps analysis of social engagement metrics, Coca-Cola began using those insights to stay on that of the soft drinks market with better, more timely content, that gets higher engagement, and higher levels of brand loyalty.
The Advice Track
The goal of all social media marketing is conversion of one kind or another. And conversion comes down to knowing your market. Where they focus their attention. What message they want to hear? And what new information they need in order to act.
Having the answers to these questions enables you to know your consumers better and build a deeper, more profitable relationship over the long term. This is what Computer Vision enables. To see whether this technology is right for your company, speak with one of our experts.