Those devices are going to take a big role in our day-to-day life, as home devices such as locks, thermostats, cameras and almost anything you can imagine will be available with out-of-the-box connectivity, at an affordable price.
How is it going to affect consumer shopping habits? At first, they will use it buy the very basic necessities: a well-known product that does not require any research or price comparison. Companies like Procter & Gamble (P&G), Johnson & Johnson (J&J) and Avon (AVP), which sale household bare necessities, will find it much easier to push their products via IoT devices. But, after a while, shoppers will be ready to adopt shopping by voice to even high price tag products, such as furniture and appliances. Manufacturers will also become more sophisticated by connecting it to AI services (such as IBM Watson), which can even identify specific sentiments in a voice and act accordingly.
But, after a while, shoppers will be ready to adopt shopping by voice to even high price tag products.
There are two basic requirements for shoppers to purchase products with their voice:
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They need to have an IoT device
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They must have an account with the entity that controls the device
While having the device is a no-brainer, having an account is the only option to being identified by the device for personalization, payments, shipping and tracking. It is the only way that the entire interaction can be completed using voice commands exclusively to order a product.
In this scenario, whoever controls the device will have the power to decide which products to sale or push. Other merchants might find themselves without any presence in this space and may lose ground and market share.
Voice devices—which are powered by voice recognition software and chat bots—are not perfect and there is still long way to go until they will entirely replace browser and keystrokes. But, they are getting better and eventually, will combined with visual outputs such as Amazon show, or be embedded in every TV screen or appliances with displays.
It is very much similar to the issue that most merchant have with mobile apps. Shoppers are very unlikely to download the app of niche product merchant, unless they see immediate value to it. And, even if they have downloaded it once in the past, they will still prefer to use the browser.
In the meantime, merchants can choose to take advantage of existing search by embedding voice technology into their online store, providing an alternative to using voice commands in a mobile device or desktop, by way of a Natural Language Processing (NLP) engine.
This technology is not a complete solution, because it still requires shoppers to use the display to confirm the accuracy of search results, and keyboard/mouse, or mobile gestures to complete the transaction. However, it does have few important benefits:
1. Allowing shopper to have similar experience to their household IoT device.
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Voice interaction is more natural for humans than typing, and it reflect a greater level of engagement to the brand. For example, most users will politely wait for Siri to say the last word, even though they’re aware they’re speaking with a robot.
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Increasing mobile conversions. While mobile accounts for roughly 45% of U.S. shopper traffic, the conversion rate is less than half of desktops. Many shoppers starting their journey on a mobile device, with the actual purchase being completed from their desktop. But many others will never go back to the same place where they left off. The main reason is the limited mobile screen size and less convenient order submission.
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It is much easier to perform Long Tail Search using voice commands and shorten the time needed to get the most relevant products. For example, instead of search for running shoes, and then going through the tedious process of filtering by brand, size and color, just to find that this product is out of stock, a shopper (after prompted by the voice interface) can just say the following phrase: “I want to buy blue Nike running shoes, size 11.” Or even, “do you have a body scrub cream for under $20?” A great NLP search engine will find the relevant products and filter the results with the pre-defined filters, such as brand, color and out-of-stock products.
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Adding the benefit of a front-facing sales person to the shopping experience. We tend to think that every visitor in an online store is looking for something and has a perfect idea of what they are looking for. In reality, many visits in an online store are very much like someone walking at the mall and wandering around stores, without any clue of what they are looking for. Using a voice interface is a great way to interact with those shoppers and pitch to them products based on a clustering algorithm. In fact, it’s even a better application for this type of interaction over a brick and mortar store. In a traditional face- to-face interaction, the salesperson can only have the very basic impression of the shopper, such as, gender, age and overall look. In an online store, the power of the internet allows us to know much more about a random visit and pitch more relevant products.
Celebros, Inc. is a global leader in e-commerce site-search, merchandizing and navigation conversion technologies for online retailers. Celebros prides itself on providing multi-language Natural Language Processing (NLP) solutions with advanced machine learning, excellent service and customized solutions to fit the specific customer needs, using a SaaS business model for ecommerce site search.
Examples of Celebros’ Speech-to-Text Site Search
Voice Search in a Fashion shop
Example search phrase:
I WANT TO BUY A RED CASUAL DRESS SIZE SMALL
Voice Search in a Sports Fan Shop
Example search phrase:
I WANT TO PURCHASE AARON RODGERS JERSEY SIZE LARGE
Example search phrase:
DO YOU HAVE BODY LOTION FOR LESS THAN $20?
Voice Search in a General B2B Supply a Shop
Example search phrase:
I NEED TO MOP THE FLOOR
Example search phrase:
I WANT TO BUY DARK CHOCOLATE RASPBERRIES CANDY
