Unless you have been burrowed deep underground for the last couple of years, you’ve most likely heard of artificial intelligence (AI). But how can we use artificial intelligence in eCommerce?
In this article, we share powerful and practical ways that retail businesses are using AI in the world of online shopping.
AI is beginning to embed itself into all aspects of our lives. From the growing number of self-checkout cash registers to advanced security checks at the airport; artificial intelligence is just about everywhere.
It’s widely anticipated that AI is set to go into turbo drive in the next couple of years with giants such as Google and Microsoft already investing heavily into new AI initiatives.
Google’s recent £400m purchase of start-up DeepMind, the artificial intelligence company that specializes in algorithms and machine learning for positive impact, is just one of many expected acquisitions as the potential of such technology becomes a reality.
Other major tech firms such as Facebook, IBM and Yahoo have already publicly expressed their focus on developing artificial intelligence as a new source of business.
If you search for AI online, you will stumble across hundreds of articles that predict a marketplace dominated by the use of artificial intelligence.
In fact, a recent study by Business Insider suggests that as much as 85% of customer interactions will be managed without a human by as soon as 2020.
Many eCommerce businesses are already using forms of AI to better understand their customers, generate new leads and provide an enhanced customer experience.
But how are they doing this? Read on for our comprehensive list.
1. Create customer-centric search.
Amir Konigsberg is the current CEO of Twiggle, a business that enables ecommerce search engines to think the way humans do. Watch any recent interviews with Amir and he will tell you that consumers often abandon eCommerce experiences because the product results displayed are often irrelevant.
To tackle this problem, Twiggle utilizes natural language processing to narrow, contextualize and ultimately improve search results for online shoppers.
Another business that is trying to improve e-commerce search is US-based tech start-up Clarifai. Clarifai’s early work has been focused on the visual elements of search and, as its website states, the software is ‘artificial intelligence with a vision’.
The company enables developers to build smarter apps that ‘see the world like you do’, empowering businesses to develop a customer-centric experience through advanced image and video recognition.
Leveraging machine learning, the AI software automatically tags, organizes and visually searches content by labeling features of the image or video.
Read more about their Custom Training, which allows you to build bespoke models where you can teach AI to understand any concept, whether it’s a logo, product, aesthetic, or Pokemon.
You can then use these new models, in conjunction with existing pre-built models (e.g. general, color, food, wedding, travel etc.) to browse or search media assets using keyword tags or visual similarity.
The AI technology gives businesses a competitive edge and is available to developers or businesses of any size or budget. A great example is Pinterest’s recent update of its Chrome extension, which enables users to select an item in any photograph online, and then ask Pinterest to surface similar items using image recognition software.
It’s not just Pinterest introducing new search experiences with AI.
Shoppers are rapidly waving goodbye to impulse control as new software platforms that drive eCommerce websites create innovative visual search capabilities.
As well as finding matching products, AI is enabling shoppers to discover complementary products whether it is size, color, shape, fabric or even brand. The visual capabilities of such software are truly outstanding.
By first obtaining visual cues from the uploaded imagery, the software can successfully assist the customer in finding the product they desire. The consumer no longer needs to be shopping to see something they would like to purchase.
For example, they may take a liking to a friend’s new dress or a work colleagues new pair of gym Nike’s. If there is a visual, then AI enables consumers to easily find similar items through e-commerce stores.
2. Retarget potential customers.
According to Conversica, at least 33% of marketing leads are not followed up by the sales team. This means that pre-qualified potential buyers interested in your product or service, fall through the inevitable cracks.
Furthermore, many businesses are overloaded with unmanageable customer data that they do little or nothing with. This is an incredible goldmine of intelligence that could be used to enhance the sales cycle.
For instance, if we take a deeper look at the retail industry, facial recognition is already being used to capture shoplifters by scanning their faces on CCTV cameras.
But how can AI be used to enhance a customer’s shopping experience?
Well, some businesses are now using facial recognition to capture customer dwell times in the physical store.
This means that if a customer spends a notable amount of time next to a specific product e.g. an iPod, then this information will be stored for use upon their next visit
As AI develops, we anticipate special offers on customer’s computer screens based on their in-store dwell time. In other words, omni-channel retailers are starting to make progress in their ability to remarket to customers.
The face of sales is changing with businesses responding directly to the customer. It is as if businesses are reading the minds of customers and it’s all thanks to the data used with AI.
3. Identify exceptional target prospects.
New AI technology arms e-commerce businesses with the timely intelligence required to solve their business challenges such as lead generation.
Predictive marketing businesses such as Mintigo, provide AI solutions for marketing, sales and CRM systems. Through Mintigo’s software, Getty images has successfully generated significant new leads by capturing the data that shows which businesses have websites featuring images from Getty's competitors.
Watch the video here.
Getty can identify high quality prospects and this gives their sales team a competitive advantage to win new business. Practical sales intelligence is delivered at scale to Getty’s sales team across millions of potential customer records. Without AI and machine learning in place, Getty’s system would not be possible at these volumes.
4. Create a more efficient sales process.
Thankfully, just about all of us have moved on from the days of old sales techniques such as picking up the trusty Yellow Pages and pestering potential clients through cold-calling.
Customer’s lives are now heavily influenced by a variety of different media from TV adverts to social media. In fact, in the past 12 months, even Snapchat has established itself as a viable sales and marketing tool, opening up new opportunities.
If you want to tailor your problem-solving solutions and create a strong sales message that reaches consumers at the right time on the right platform, then integrating AI into your CRM is the way to go.
Many AI systems enable natural language learning and voice input such as Siri or Alexa. This allows a CRM system to answer customer queries, solve their problems and even identify new opportunities for the sales team. Some AI-driven CRM systems can even multitask to handle all these functions and more.
The North Face, a large eCommerce retailer, is a great example of a company stepping up their game by using AI to better understand their consumers. By using IBM’s AI solution called Watson, they enable online shoppers to discover their perfect jacket.
They achieve this by asking the customer questions e.g. “where and when will you be using your jacket?” through voice input AI technology. IBM’s software then scans hundreds of products to find perfect matches based on real-time customer input and its own research e.g. such as weather conditions in the local area.
There is little doubt that AI is already starting to impact e-commerce and has started to evolve the sales process with new data. The changes will ensure that customers will no longer be offered products and services that are inappropriate.
AI is making sweeping changes to the way businesses deal with their customers, gaining faster access to information and harnessing employees’ talent for better use.
5. Create a new level of personalisation across multiple devices.
Personalisation is nothing new for eCommerce and if you frequently use Amazon then you’ll know exactly what we’re referring to. However, with the ever-increasing advances in artificial intelligence and machine learning technologies, new deep levels of personalisation have started to penetrate the fast-growing e-commerce world.
Whereas AI based personalisation for eCommerce takes the multi-channel approach. New AI engines, such as Boomtrain, sit on top of the multiple customer touch points to help the business analyse how customers are interacting online.
Whether it is a mobile application, the website, or an email campaign, the AI engine is continuously monitoring all devices and channels to create a universal customer view. This unified customer view enables eCommerce retailers to deliver a seamless customer experience across all platforms.
The next time a customer is browsing iPhone cases on your website, they may receive a push notification on their mobile, informing them about your flash sale for iPhone cases. They directly make the purchase on their phone, saving a lot of steps for both parties.
6. Provide a personal touch with chatbots.
A tornado of technological advances has changed consumers’ expectations, and commerce is now focused on building experiences for the individual, and not the mass market. For consumers, there are a multitude of touch points and influences that generate purchases.
Many eCommerce retailers are already becoming more sophisticated with their AI capabilities in capturing attention, and one approach widely developing is known as ‘conversational commerce’.
In the eCommerce world, this is the confluence of visual, vocal, written and predictive capabilities. Consumer needs are rapidly evolving to the point that retailers struggle to keep up.
If brands wish to survive then this is one of the priority business strategies that must be executed. The use of artificial intelligence through the application of ‘chatbots’ is just one way to drive the conversation in this next era of conversational commerce.
So, what is a chatbot?
By definition, a chatbot is a specific computer program that is designed to simulate conversation with human users over the Internet.
Chatbots can actively take on some of the important responsibilities that come with running an online business, particularly when it comes to executing tasks for operations and marketing.
Chatbots can automate order processes and are an effective and low-cost way of providing customer service. Customer service via social is starting to establish itself as a requirement as opposed to an option.
Often when consumers are browsing online, they are already logged into social platforms such as Facebook. With this in mind, there is a great opportunity to use messenger functionality to confirm orders or to provide instant online support.
It’s also possible to integrate a chatbot system into a shopping cart.
Once the chatbot system has been integrated with one of your shopping carts, it can work with all the stores based on the platform. The more shopping carts that your chatbot application supports, the more potential customers it has.
Also, specific systems need shopping cart integration to retrieve information such as product details, quantities and shipping terms that chatbots may use to provide accurate answers to customers.
Chatbots provide a valuable customer support solution for eCommerce retailers. We already know there are several strong alternatives such as contact forms, phone calls, and email. However, online chat remains the fastest and, in many cases, the most convenient means for visitors to get answers.
7. Empower store workers.
Whilst online retailers have experimented with chatbots, there has also been some consideration of how to replicate the helpful experience in-store.
Lowe, a home improvement store, is a good example of such implementation. Lowe introduced the first autonomous robot in late 2014, named the LoweBot.
The tall shopping assistant greets customers at the door, guides them around the store, sources relevant product information and even assists employees with inventory management.
This helps Lowe to free up their experienced store workers to engage in more meaningful interactions with customers.
8. Implement virtual assistants.
All of us need a little help online sometimes.
After all, what are cloud-based AI software agents for?
We’re all familiar with the usual suspects: Siri, Google Now and Alexa, and they have successfully introduced us to the idea of talking to a phone, laptop or even a home appliance.
However, the evolution of many of these virtual assistants have already become boring commodities for the user, with limited useful updates in recent months.
The advances for virtual assistants are rooted in natural language processing and the machine’s ability to interpret what people are saying in words or text.
So, what does this mean for ecommerce retailers?
Let’s take a look at Amazon’s virtual assistant, Alexa.
Their virtual assistant, which has recently emerged as one of the most prominent voices in commerce, has been successfully integrated into Amazon’s own products as well as products from other manufacturers.
For instance, by using Alexa on Amazon’s Echo device, customers can discover local gigs for the upcoming weekend through StubHub, arrange transport to and from the event via Uber, or even order pre-event dinner from Domino’s (and track the order status in real time).
The increasingly popular 1-800-Flowers in the US even enables consumers to send flowers to their loved ones via voice.
Virtual assistants are impacting the way customers purchase, and provide a creative opportunity for eCommerce retailers to take advantage of.
9. Integrate with everyday household items.
There are few more interesting examples of AI integration than the partnership between Amazon’s Alexa and LG’s Smart InstaView refrigerators.
LG have experimented with several previous versions of the InstaView refrigerator with enormous touchscreens built into the door. However, this time around, LG has tacked on a virtual assistant and webOS software. It's a place where a virtual assistant has real potential to be especially helpful.
In addition to providing news and weather updates, it can lend a hand with your shopping orders. You’ll never have to run to the shop for milk again. Imagine the possibilities for eCommerce retailers that have direct access to the homes of consumers.
10. Improve recommendations for customers.
Using AI, brands can more intelligently and efficiently scan through petabytes of data to predict customer behavior, and offer relevant and helpful recommendations to individual consumers.
This level of intelligence is vital in delivering a personalized shopping experience for the consumer.
Starbucks has been heavily involved with this process, utilizing AI to analyse all the data it has gathered on its consumers and delivering more personalized suggestions.
For instance, Starbucks recently launched ‘My Starbucks Barista’, which utilizes AI to enable customers to place orders with voice command or messaging.
The algorithm leverages a variety of inputs, including account information, customer preferences, purchase history, third-party data and contextual information.
This allows the coffee giant to create and deliver more personalized messages and recommendations for their customers.
The dynamic sector that is eCommerce, has revolutionized the way a consumer shops in our mobile world. The desire of many eCommerce businesses is to bring the best of an offline shopping experience to the online space, by offering customers a seamless way to discover products they are actively looking for.
There is an important focus in ‘hyper personalisation’, which could only be facilitated by learning genuine consumer behavior and making predictions with gargantuan amounts of data that is collected from user activities on smartphones, tablets and desktops.
The process of recommendation is widely practiced by eCommerce retailers to help customers find the best solution.