The Potential of Image Analytics to Transform the Customer Experience
- Read original article here
Image analytics has the potential to completely transform retail, both online and in person. It consists of categorizing photos based on...
Image analytics has the potential to completely transform retail, both online and in person. It consists of categorizing photos based on characteristics or items in the photo. Image recognition software plays an important role in image analytics, helping to identify things like faces, pets, objects, and colors.
AI (artificial intelligence), VR (virtual reality), AR (augmented reality), and numerous other emerging technologies rely on image analytics to deliver a great user experience. In retail, this technology can improve the customer experience significantly by transforming marketing, security, and satisfaction.
One of the most widely valuable applications for image analytics in retail is image-based search. This makes it far easier for customers to find the product they are looking for. Image analytics can be used toidentify the characteristics of items in the photo. This data can be used for search tagging in addition to the text name of the product or its description.
For example, a customer may be searching for blue running shoes. Image analytics will identify all the pictures of shoes in the online store’s product lineup. Within those pictures, it can pick out the photos containing the color blue. Image recognition software can even tell running shoes apart from other types of shoes. A customer may not know this process is going on in the background, but they will notice better search results.
Additionally, if a customer is looking for a specific product, they could even search using an image. Google already offers this feature. For example, if a customer already has a pair of blue running shoes and wants new ones, they can copy a photo of the shoes into a search box. Image analysis tools would recognize that the photo showed a pair of blue running shoes and try to find products with similar features.
The counterfeit retail market has exploded in recent years as e-commerce has made it easier for knock-off items to sell. Not only is this harmful for businesses, but it also leads to unhappy customers who think they have been sold a substandard product.
In reality, they’ve mistakenly purchased a fake product that doesn’t represent the business’s true standards. Luckily, every counterfeit product has visual inaccuracies or errors, which can be used to identify fake items.
With image analytics, businesses can track down online stores selling counterfeit copies of their products. Identifying these counterfeit retailers helps protect customers, as well. It is not uncommon for knock-off retailers to open fake online stores designed to steal customers’ data, which poses a serious cybersecurity risk. Businesses themselves can implement cybersecurity strategies, such aswell-designed password requirements, which protect customers and their information.
Customers lose this protection if they are tricked into shopping at a fake retailer, though. By applying image analytics to tracking down counterfeit retailers, businesses can ensure their customers are getting the best products possible and shopping securely.
Image analytics can be used to improve the customer experience before they even land on a business’s website. In fact, the applications of image analytics in retail are so valuable that the image recognition market is expected togrow by $4.5 billion through 2026, with a 20% compound annual growth rate.
Images are invaluable in market research today. When people buy a new product they like, for example, they are likely to post a photo of it on one of their social media accounts. Similarly, photos that attract a significant amount of engagement online can say a lot about what a certain audience is interested in. This doesn’t just boost a business’s social media presence. It also offers insights into what’s connecting with customers.
Businesses can implement image analytics in their marketing research to identify relevant trends based on photos their audience shares online. Photos can show how real customers are talking about and even using products. This data can be used to inform product design as well as marketing strategies.
Creating a promotional photo that is optimized for image analytics can also help increase online engagement, since Google and other major search algorithms use image analytics to improve their user experience.
Augmented reality is a particularly popular application for image analytics when it comes to customer experiences. With AR, customers can see how a shirt might look on them or how a new sofa might fit in their living room. This improves customer satisfaction and can also reduce return and exchange rates since customers have a better idea of what to expect from a product.
Numerous major companies are already utilizing AR to improve their customer experience. IKEA, for example,has a mobile appthat allows customers to place a life-size digital version of furniture pieces in their real-world rooms. Image recognition software detects the size of the room and other objects inside it and scales the 3D image of the furniture piece accordingly.
The customer experience is growing increasingly influenced by digital technologies. Image analytics is among the most valuable of these technologies. Its versatility offers an excellent return on investment for businesses in any industry. With a quality image analytics usage strategy, businesses can gain a greater understanding of their audience, improve their products, protect customers from fraud, and create cutting-edge shopping experiences.
