For many in the business and marketing world, computer vision is still a new and somewhat obscure concept. However, it is also one that is rapidly becoming more relevant, particularly with regard to the acquisition, service, and retention of customers.
Leaders and professionals implement Computer Vision in Marketing, Operations, Sales, Retail, Security, and many other areas.
To recap the core concept quickly, we’ll turn to a simple definition from Towards Data Science, which characterizes computer vision as a field of computer science that enables computers to identify and process objects in images and videos the same way that humans do. We would also add that the improvement of augmented reality technology is in some respects extending computer vision into the world — such that computer systems can also recognize real-world objects and images through their own cameras.
It’s all extraordinarily impressive technology, and it can be used for a wide range of purposes.
Nowadays, marketers are assisted by certain automated features that help to make recommendations and narrow down selections for online shoppers. The process can work in different ways, but typically a customer’s search activity produces unseen tags that reflect apparent interest. Those tags can then be used to filter through additional store offerings so that customers can be presented with suggestions they’ll be likely to appreciate.
It is a simple, automated means of improving direct customer engagement.
Now, however, computer vision in marketing is refining this same general concept. Through this technology, a company’s system can actually recognize — look at, in a sense — what customers are observing. Rather than relying on tags, which can be somewhat vague, a computer can identify customers’ selected items and actually look for similar items or appropriate accompaniments. The potential is there to improve customer engagement with even greater accuracy.
Some time ago, The Atlantic posted a thorough, interesting article on what stores do to “follow every step you take.” The idea is to track customers within stores in order to gather data that can effectively shape in-store marketing strategies. By tracking customers — through Bluetooth and Wi-Fi signals, the customers’ own smartphones, etc. — companies can gain insight into which products are being favored, how the store layout might be made more effective, and so on.
And now, computer vision is essentially simplifying this process for marketers and shows how computer vision in marketing is beneficial.
Rather than relying on complex webs of Bluetooth devices and smartphone connections, stores can employ cameras that can “watch” and learn from customers’ activity using Computer Vision.
Customer personalization is something we typically think of as having to do with content marketing and data analytics. In a broader sense, today’s businesses go to great lengths to make sure that their written and shared content is tailored to specific audiences. Ayima Kickstart examines this as an aspect of content SEO — explaining that companies employ “expert writers” to research target audiences and construct content according to that research.
Beyond this, on more of a customer-to-customer basis, a lot of modern businesses are also using various analytical methods to track activity and tailor follow-up recommendations as needed.
Through those practices, consumers are effectively guided toward conversions: They’re found and spoken to strategically within broader audiences and then tracked and catered to via tracking as they browse or otherwise engage with the business. It’s an effective process, but we’re now beginning to see computer vision in marketing simplifying it.
Businesses are beginning to explore the use of everything from cameras on smart speakers to in-store cameras to observe customers and develop recommendations based on personal factors. This doesn’t negate the aforementioned efforts, but it does represent another, more direct way of personalizing sales approaches.
The last benefit of computer vision in marketing that we’ll discuss here — and perhaps the simplest — is its impact on consumer searches. With computer systems better able to recognize and interpret images, consumers now have the option of plugging images into search mechanisms. This means that if a consumer should come across a photo of an intriguing product — or even take that photo personally — it can be used to search for further information. As this practice becomes more common, it will naturally produce benefits for businesses. However, it also gives marketing departments a whole new way to think about image-driven product marketing and social media outreach.
All of these represent significant changes and advancements. And yet they’re also only the beginning! In our article ‘How is Vision Analytics Retransforming Modern Industries?’ We pointed out that the global computer vision market anticipates a 7.6% CAGR between 2020 and 2027.
Due to sharing of visuals among the customers, online marketing using visual datasets has become crucial for marketers. With the help of computer vision, they can gain customer insights, improve the campaigns and ultimately improve their buying behavior.
As Computer Vision is maturing with each passing year, it holds many new opportunities for marketers. That amounts to a prediction of significant growth, which means that computer vision in marketing is going to become even more sophisticated — and produce even more beneficial concepts — over time.