E-commerce, or online commerce, is a big thing. In 2018, e-commerce sales worldwide reached $653 billion and the number will keep growing.
The popularity of e-commerce is justified by the fact that the world is digitized and the customers are used to immediate and convenient service that can be performed via the Internet. As well, the rapid development of such technologies as the Internet of Things, AR & VR, and Machine Learning has raised the customers’ expectations. It’s becoming harder to wow the user — so all industries are adapting to the change and retail is no exception.
We all know how it used to be. Ads on TV, in newspapers and magazines, billboards and radio ads. All of them were successful in terms of attracting the customer’s attention. Then time has come when the user did not have to interact with any of these media sources anymore to learn about something new. It all came down to using one single device that allows searching for the information, checking out the similar products, choosing a product and ordering it. Today, the customer is in control — and the retail industry had to adapt to it.
E-commerce is offering the following advantages:
The growth of the e-commerce industry led to the fact that today 96% of the US shoppers make online purchases and 80% of the customers use their mobile device to look up the product reviews, prices or similar products.
But there is more to e-commerce than just a carefully crafted mobile app or website. Successful retailers are making full use of the latest technologies that allow them to stay atop the competition and make the customers talk about their brand and products.
To win the customers’ hearts, the biggest international brands are already offering their customers unique experience in correspondence to the products and nature of the brand.
The AR boom probably started with the Pokemon Go and since then, the technology became widespread in the gaming industry. However, retail also makes use of it and at times, in a very smart and unexpected way.
One of the best examples of using AR in e-commerce is an app by Ikea. It helps you see how the Ikea items will look in your room by simply dragging the virtual objects over your room on the mobile screen.
This is a really smart strategy that significantly boosted Ikea’s sales and customer engagement. Furniture is normally massive and it would be hard to carry an item home to see whether it would fit. The app by Ikea offers a perfect opportunity to “try” a piece of furniture in real life and see whether it would fit within one’s interior — and all that can be done with zero effort and in no time.
Another great example of an AR e-commerce app is an app by Lacoste. The company offered its customers a chance to “try on” different shoes in augmented reality without visiting a brick-and-mortar store. The app appealed greatly to the young audience and was a huge success for the company.
Chatbots have become priceless helpers for the companies all over the world and there is a reason for that. They immediately provide users with the required information, add to personalization and save user’s time significantly.
Shopping bots, in general, have the following functions:
If you are yet unfamiliar with the bots, it’s recommended that you start with a really simple one that would perform one or two functions. Then, once you see what the users want, you can extend the bot’s functionality and make it more complex and advanced.
Machine learning is a great tool that is capable of many awesome things. One of them is face recognition and that’s a treasure box for the beauty brands.
Sephora app is a perfect example of using Machine Learning to increase product sales and brand recognition. The app can recognize the user’s face and apply a chosen make-up on it. Thus, the user can “try” different Sephora products without visiting the store and immediately order them from the same app.
ML can also be used to create smart virtual assistants. H&M, for example, offers a “personal stylist”, which is powered by machine learning and advice on the best clothing items for the user.
Such an approach contributes to customer-centric strategy and creates a fun and deeply personal experience for the user.
This one is related to the ML and we are going to describe a real case study from the Dashbouquet projects.
What we are currently working on is a group of applications that would interact with a user through a webcam. The camera detects people and certain points on the body. For example, it detects eyes, so that it will know where to put on the glasses. The second part of the algorithm is gesture detection. If there is a hand movement, like waving, something is happening on the screen. And specifically, the program can detect spread arms like the “plane” pose. The system also identifies age and gender.
As an outcome of such an interaction, the users get a promo code or a photo to share with their network.
The technological stack for our app includes: Javascript and React for code, Python, OpenCV, and Tensorflow for detection and recognition, and algorithms for physics and interaction with the objects are pure mathematics.
This technological solution can be used in e-commerce to create interactions for various gestures and show specific content based on age and gender.
First introduced in 2014, Amazon Alexa became a popular virtual assistant for thousands of people and now Amazon plans to use it for a brand-new shopping experience.
The official website states that shoppers will be able to place orders, check the order and cart statuses and look for the products via the interaction with Alexa by voice.
Voice shopping is considered the next big thing in the e-commerce industry. While not many people use it yet, the voice shopping market is estimated to hit $40 billion by 2020.
With the rising popularity of mobile, mobile payments will become one of the leading payment methods within the e-commerce sector and are estimated to reach $148 billion by 2021. In addition to mobile, more customers will also be using Apple Pay and Google Wallet and some e-commerce stores started allowing payment with cryptocurrency.
Retailers spend lots of time, money and resources on product stocking and, with the help of AI, they can significantly improve this process.
The processing of Big Data can help the retailers analyze and, therefore, forecast the possible customer behavior in terms of buying and adjust the stocking process correspondingly. I.e. if the analysis shows regular high demand for a certain product in a certain time period, a retailer can adjust the product ordering correspondingly and estimate the amount of the product beforehand.
Social media is a great place to engage with the customers, reach new users and expand one’s audience. However, a modern user does not want to be interrupted during the social media session and thus, the advertisement and shopping have to be as native as possible.
Last year, Instagram introduced new shoppable features: an option to tag products on the photos and an option to add the product to the Stories. These features became a break-through for businesses as they allow seamless and native shopping experience for a strict target audience.
So for the e-commerce businesses social media platforms will become a powerful marketing and sales tool if played right.
The use of cutting-edge technology is not all that one needs to expect a sales boost and inflow of customers. Don’t forget about the basics:
Barriliance states that in 2017, the abandoned cart rate reached almost 79% and poor checkout process is one of the main reasons behind that. It thus makes sense to invest in the development of a high-quality mobile app or a website redesign. And then, once you have a perfectly working e-commerce store, you can think about adding-on the corresponding technological innovations to make your store stand out and communicate your brand’s message clearly.