E-commerce and the way we shop are changing day by day. The whole shopping experience becomes more intuitive, predictive, and personalized. With mobile commerce growing, we’re now used to shopping anytime and anywhere. Globally, 1.92 billion will shop online in 2019. That’s a quarter of the world’s population.
E-retailers are constantly looking for ways to boost their sales and improve customer satisfaction, especially such practices which are reasonably priced and bring immediate results. We analyzed the most disruptive trends and here are those five that are better not overlooked.
Buyers who discover product in 360-degree photography view are 14% likelier to make a purchase than those who see still images, states 2019 Omnichannel Report. Those who encounter a virtual try-on option are even more likely to buy.
Regular visualization in the online store doesn’t provide the same experience as seeing the product in real life. But viewing products in 3D detail with augmented reality enable customers to flip and turn products, studying them in more details. Interactive product visualization imitates ‘try before you buy’ experience and removes customer hesitation from the buying cycle.
For instance, Tenth Street Hats use 3D visualization on their website and let customers look at the hat at every angle. They also give their shoppers the opportunity to try on accessory available in their online store. E-retailer site requests access to a visitor’s smartphone camera. Once granted, it captures a live shot of the user and technology conducts facial recognition. The result is a hat that “fits” on the customer’s head.
40% of shoppers revealed that they are willing to pay more if they can preview product using AR, claims Retail Perceptions Report. And AR opens up a whole new world of possibilities for making the shopping experience more entertaining and convenient for your customers. Augmented Reality is able to design such experience as dressing in clothes or placing furniture into a person’s home. For example, Chrono24 app helps to virtually try on different watches before ordering one.
A lot of customers initially use apps just for the fun and without the intention to buy anything, but after experiencing a product in AR, they end up purchasing it. Apps and websites with AR features increase customer engagement. It also helps to promote products on social media platforms if the photo with AR filter is entertaining enough to share on Instagram or Twitter.
The costs and time of AR app development depend on a variety of factors:
the number of platforms (Android, iOS, Windows),
local vs. offshore (North American developers charge around $200-250 an hour, offshore specialists charge around $50 an hour),
the complexity of the project, etc.
AI & Machine Learning
Did you know that 48% of shoppers spend more when their experience is personalized? Data-driven algorithms provide such a level of personalization that is hard to beat. For instance, Netflix claims that around 80% of subscribers trust and follow the recommendations based on machine learning.
Understanding data on your e-commerce website visitors opens many new opportunities to increase connections with your customers. You can learn what products they were looking for and what they bought in the end, whether they put an item in their wish list and then waited until it would be discounted, and many other purchase behaviors. All this knowledge enables retailers to offer relevant alternatives and complementary products. Upselling and cross-selling are responsible for an average of 10-30% of e-commerce business revenues, according to Forrester research analysis.
John Lewis added and achieved a 27.9% increase in sales. Its product recommendation tool provides visitors with suggestions by analyzing shopping behavior alongside the relationships between products and product categories.
In times when customers attempt to avoid information overload, sending them directly to the products they want is crucial for e-retail success.
With big data becoming more affordable, it would be a grave oversight not to learn more about your customers by means of machine learning. Use of AI-powered machine learning:
Helps to understand the contextual meaning behind search terms. For example, you can find out that the majority of people typing ‘ski gear’ into the search box, actually looking for warm pants. So, the search results will show pants first, and then all other clothes one might wear skiing.
Predict customer behavior. Knowing a particular visitor profile, the algorithm will show him the desired products or better-priced alternative.
Machine learning technology cost is set individually depending on the project scope and complexity of the project. But there are some ready-made solutions that are economical ways for small e-commerce merchants to gather and utilize the data to enhance their sales and customers loyalty.
LEGO – one of the companies that made good use of chatbots. They created a Ralph the Gift Bot which helps to find the right gift from the variety of LEGO goods. Ralph starts out with simple questions, like location, age of the person you’re buying for, and budget. Then it narrows down the probable suggestions by asking what theme the product must be (adventure, travel, town planning, etc.). Next, the user gets a link that automatically adds the chosen product to the shopping cart on LEGO’s website.
Studies predict that 85% of all customer interactions will be held without the need of a human agent by 2020. E-retail chatbots help shoppers in searching the right item, checking product availability, comparing multiple products, and even in making the payment. Customers can 'communicate' with these machines via text, voice, and pictures.
According to Juniper Research, implementing chatbots help businesses to save a lot of money because, in some terms, they become more cost-effective than hiring staff. Chatbots can:
provide customers with immediate responses to their questions and save their valuable time;
give fast solutions to retail websites visitors at any time of the day;
take initiative to welcome the customer to the website, and offer assistance and suggest queries the user might have had but didn’t ask.
But chatbot won’t be effective if it doesn’t recognize conversational search terms and understands colloquial ‘natural search language’. Chatbots work well when the business predicts a variety of questions and scripts all possible answers. If a business applies machine learning, then the bot can answer up to 80% of routine customer service questions. In that case, interactions that website visitors are having with chatbot improve customer engagement and all-in-all user experience.
There are a lot of easy-to-use and cost-effective options to build bots. E-retailer can buy a ready solution or even try it for free. If there is no chatbot that fits their business, they can create a bot with the help of a self-service platform or craft it from scratch. The cost of creating a bot within an existing framework depends on the number of messages and the number of bots. The price starts at around $10-15 a month.
After implementing voice-enabled search to their websites in several European counties, outdoor gear retailer, The North Face recorded a 35% increase in search conversion rate and a 24% rise in revenue from search. According to the Gartner study, online retailers who earlier adopted their websites to support visual and voice search features will increase e-commerce revenue by 30% in 2021. And Comscore supposes that, already, next year, half of all queries will be voice searches.
Currently, voice search is mostly used for non-commerce related searches. Yet, there are some people so far who use Amazon's Alexa and Google Assistant to look for business and product information, and their popularity is increasing tremendously. It’s especially important for regional services and products. As revealed by Search Engine Watch, mobile voice-related queries are three times likelier to be local-based than text.
How can someone optimize a retail website for voice search? Collect and compile questions that your customers ask about your business and analyze them. Present its information in a natural and conversational form. Enable product descriptions and other site content answers potential customers’ questions.
A retailer can implement voice search in the e-commerce mobile website or in the app as Walmart has. You just press the voice speaker button, tell what you want to find, and an algorithm answers your query.
One-time voice search optimization for a small website can cost a retailer around $200-300, but it will only help your website to rank highly in search engine results. By adding a voice search feature to the retail app, you provide your customers with a more natural, faster and entertaining shopping experience. But the price of adding voice search to the mobile app may vary.
Visual search is an even more essential function for online shopping sites. Human brain receives 90% of information from the eyes and can identify images within 13 milliseconds. It makes visual search one of the most in-demand digital solutions in retail. And only 8% of e-retailers implemented image search into their website.
How does it work? Visual search allows shoppers to upload a real-world photo or screenshot. Technology starts to identify multiple shapes and outlines contained within a single image. Search provides relevant products, and customers immediately find what they are looking for.
It’s particularly useful for unusual items that are hard to describe. That way, e-commerce business owners empower their customers throughout their buying journey and significantly improve their shopping experience. Our client, fabric retailer Duralee, came across a problem when a potential customer had a picture of the desired pattern but couldn’t put it in words to search through the website. Now, AI-powered search can analyze the photo of the paisley designed rug and provide the website visitor with relevant products. The customer does not have to struggle with typing in the name of the Persian pattern.
Major online retailers are already benefiting from this feature. H&M and eBay allow shoppers to upload a photo and provide them with similar goods. Amazon and Pinterest have functions that let you snap photos, and site search engines find matching items in their databases. In 2017, ASOS added Style Match to let its app users upload a photo of a fashion influencer and search through clothing or accessories that are similar to any featured in the photo. Option let customers narrow down their search quickly and easily, instead of checking all 85,000 products currently available.
The cost of the visual search depends on whether the retailers use pre-built solutions or desire a custom model.
The Bottom Line
As technology develops and shoppers’ needs shifting at a rapid pace, it’s crucial to embrace some of those advanced practices. AI gets smarter and cheaper, so small businesses can try such technologically-related features as machine learning, visual search, and chatbots. There is a variety of pre-made formulas that small e-merchants can implement as of today. Augmented reality and voice search are pricier options and may require an extra budget. But being an early adopter here can help set business owners up for success in the future.