Artificial Intelligence in Ecommerce Could be game changing.

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 specialises in algorithms and machine learning for postive impact, is just one of many expected acquisitions as the potential of such technology becomes a reality.

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.

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.

Other major tech firms such as Facebook, IBM and Yahoo have already publically expressed their focus on developing artificial intelligence as a new source of business.

Many e-commerce businesses are already using forms of AI to better understand their customers, generate new leads and provide an enhanced customer experience.

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.


But how are they doing this? Read on for our comprehensive list.

1. 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.

2. Create customer-centric search

Amir Konigsberg is the current CEO of Twiggle, a business that enables e-commerce search engines to think the way humans do. Watch any recent interviews with Amir and he will tell you that consumers often abandon e-commerce experiences because the product results displayed are often irrelevant. To tackle this problem, Twiggle utilises natural language processing to narrow, contextualise 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 their website states, their software is ‘artificial intelligence with a vision’. They enable 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, organises and visually searches content by labelling 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, colour, 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 e-commerce websites create innovative visual search capabilities. As well as finding matching products, AI is enabling shoppers to discover complementary products whether it is size, colour, 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.

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. 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 e-commerce 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 e-commerce 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 e-commerce 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 e-commerce 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 e-commerce 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 e-commerce 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 e-commerce 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: SiriGoogle 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 e-commerce 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 e-commerce 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 refridgerator 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 e-commerce 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 behaviour, and offer relevant and helpful recommendations to individual consumers. This level of intelligence is vital in delivering a personalised shopping experience for the consumer.

Starbucks has been heavily involved with this process, utilising AI to analyse all the data it has gathered on its consumers and delivering more personalised suggestions. For instance, Starbucks recently launched ‘My Starbucks Barista’, which utilises 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 personalised messages and recommendations for their customers.

The dynamic sector that is e-commerce, has revolutionised the way a consumer shops in our mobile world. The desire of many e-commerce 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 behaviour 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 e-commerce retailers to help customers find the best solution. For example, Amazon makes recommendations to users depending on their activities on the site and any past purchases. Netflix makes TV and movie recommendations based on a user’s interaction with categories e.g. drama, comedy and action. Whilst eBay hand-collects user feedback about products to recommend products to users who have exhibited similar behaviours. And this continues to evolve with several permutations and combinations in place. AI is already being put to good use in providing personalised recommendations to subscribers based on their preferences and we expect this to develop quickly within the next year.

11. Introduce virtual personal shoppers

We discussed the concept of virtual assistants in #8, but AI is also enabling brands to create purposely-built ‘shoppers’ to assist their customers online.

There are many perks of in-store shopping that both brands and customers love. For instance, the customer has the opportunity to directly engage in conversation with a shop assistant. They may ask the customer about a specific item in a particular colour or size. These perks are limited online as customers have to go through the time-consuming (and sometimes frustrating) process of ticking boxes or entering keywords. With this in mind, e-commerce must find innovative new ways to bring the perks of offline experience to the online experience.

Flipkart, the Indian-based e-commerce company, has already made attempts to build human brain-like capabilities in order to sell smarter to more than 45 million of its registered online buyers. In fact, the business launched a messaging service called Ping. Until it was shut down in 2016, Ping served as a shopping assistant. The service embodied artificial intelligence to enable customers to quickly discover the items they were looking for. Flipkart shut the app down after just 10 months to focus on its new ‘user-to-seller’ chat.

In 2016, department store Macy’s, teamed with IBM’s Watson to create a personal mobile AI shopping assistant called ‘Macy’s On Call’. The innovative and cognitive mobile tool, which uses Watson’s Natural Language API, was designed to aid shoppers with information in 10 of Macy’s retail stores around the country, as they navigated through each one.

Amazon’s home assistant, Alexa is perfectly suited in providing the modern shopping experience for consumers. Long gone are the days when you have to rush to the local store because you’re out of milk. You can simply ask Alexa to order you some for the morning. Under the hood, the innovative Alexa will use Amazon and place an order on your behalf, ready for delivery the next morning. A fascinating feature is that Alexa simply needs to verify your voice pattern to process the order. A genuine personal shopper at the command of your voice.

You may also have heard of ‘Mona’, the virtual shopping assistant developed by former Amazon employees. The impressive and friendly assistant helps to simplify mobile shopping and provides customers with the best and most relevant deals and products that are tailored to your preferences. In fact, the more time and effort that you put into interacting with Mona, the better she’ll get to know you.

Sentient Technologies, the world’s most funded AI company, is also leveraging AI systems to deliver in-the-moment personalisation, increasing engagement and revenue per shopper for retailers. The business believes that AI will take a bigger role in making decisions, creating pre-emptive solutions, and delivering insights, and as a result, society will become much more efficient. Sentient are enabling people to see and buy things they weren’t even aware existed or even knew they wanted. The introduction of virtual personal shoppers are a true example of how AI, for the e-commerce industry, is completely disrupting traditional customer engagement techniques.

12. Work with intelligent agents

New intelligent agent negotiation systems have become a popular tool used in e-commerce, following the development of artificial intelligence and agent technology. There are 3 main functions performed by the automated agent: matching buyers and sellers; facilitating transactions; and providing institutional infrastructure. The agents are completely automated and have full control over their actions. They have their own communication language and not only react to their environment, but are also capable of using their initiative such as generating their own targets. It’s AI at its utmost brilliance, and finally they are useful for e-commerce.

13. Build an ‘assortment intelligence’ tool

Customers are forcing retailers to change their pricing strategies. Therefore, it is imperative that multichannel retailers apply flexibility when it comes to their price structuring, in order for them to retain customers.

Retailers are turning to assortment intelligence, a tool that facilitates an unprecedented level of 24/7 visibility and valuable insights into competitors’ product assortments. Businesses can monitor their competitors’ product mix, which would be segmented by product and brand as well as the percentage of overlap. This intelligent tool then provides businesses with the ability to quickly adjust their own product-mix and pricing with high accuracy. An impressive competitive advantage that provides complete visibility into what products are being offered in the market. The intelligent software puts retailers in a strong position to make specific assortment and planning decisions, and track the business impact of those actions.

14. Bridge the gap between personalisation and privacy

Whenever it comes to discussing the topic of personalisation, there is often a trade off with concerns to user privacy. User privacy has been a hot topic in recent years with its importance considered stronger than ever. Brands are actively striving to take transparency, security and honesty to an entire new level. However, to achieve this, brands cannot afford to abandon user personalisation, given its critical role in any successful e-commerce venture.

So, how can e-commerce retailers tackle this problem? Many brands believe the answer lies with artificial intelligence.

Users are a little more comfortable with sharing their details on the promise they are getting something truly valuable in return. For example, if you give Google Now access to your account, it will sync your calendar, emails and search habits. Each morning, it will greet you with a small briefing of what you currently have on your plate and will let you know if you’re going to be late to the office due to a train cancellation. Amazon’s Alexa applies the same magical approach for daily life. The modern shopping assistant puts your day-to day-routine first and even helps with daily house chores. Most recently, Amazon added the required intelligence for Alexa to buy on your behalf.

So what’s the end result?

More consumers know about Amazon Alexa-based products including Echo and Dot and a strong percentage of them make use of the software on a daily basis. The AI enables retailers to provide outstanding experiences throughout a user’s day even if they are not physically browsing the e-commerce store. For such experience, users are happy to share their precious details. A fine example of how AI is bridging the gap between user personalisation and privacy.

15. Generate sales through wearable technology

We’re all aware of the important role that mobile plays in e-commerce sales. In fact, according to Shopify, 2016 saw mobile overtake other channels as the primary source of e-commerce traffic. As products such as the Apple Watch, FitBit and other forms of wearable technology enter the e-commerce market, the implications for e-commerce retailers are plenty.

So why is wearable technology useful for e-commerce platforms? Because wearables have the impressive ability to collect data beyond just what e-commerce platforms do today.

Some wearable technology can see what products you view, define your taste, and can instantly recommend personalised products. If you start to add in physical data such as vital statistics, measurements and pupil dilation rate, the level to which recommendations could be tailored is truly incredible.

Amazon Go already promises to revolutionise a customer’s shopping experience by making it cashless. Their customers no longer need to take out their wallet with wearables; it’s the key to a checkout-less shopping experience. AI integration will be at the core of any further development as retailers enhance the experience with customer data. Forward thinking e-commerce retailers will undoubtedly want to build new partnerships with the best AI technology to stay in touch with their growing customer global customer base.

16. Improve dialogue systems

Amazon have started to apply AI to widely known issues with dialogue systems, such as speech recognition, natural language understanding and question answering. For example, by applying a class of machine learning algorithms known as ‘deep learning’, Amazon can effectively convert speech (spoken by customers) to text with accurate results.

Amazon are also tackling the problem of answering questions automatically using AI by leveraging content within website pages such as product descriptions and customer reviews. For example, a customer may ask “how many USB ports are there on this specific laptop?”. More complex questions would include “does this camera work indoors?” or “which TV out of these two has better image quality?”. AI is providing new opportunities for e-commerce retailers to engage with customers.

17. Tackle fake reviews

Any experienced online retailer will be able tell you of at least one painful story about receiving fake reviews for their brand.

Consumers are flooded with an abundance of advertising every day, which can become overwhelming and this will often delay their decision making. This is where word of mouth has become invaluable. If a customer’s friend has purchased your product and had a positive experience, then the customer will end up buying the product too. In fact, according Dimensional Research’s recent study, a staggering 90 percent of respondents who recalled reading online reviews claimed that positive online reviews influenced buying decisions. More importantly 86 percent said that buying decisions were influenced by negative online reviews.

What if these reviews are fake? AI can be used to manage this problem, and here’s how.

In terms of creating fake reviews, it is well known as ‘astroturfing’ and it’s widespread across many sites and services including Amazon. By definition, astroturfing is the practice of creating or disseminating a false or deceptive review that a reasonable customer would believe to be a trusted and neutral, third-party testimonial.

Customer reviews have become the cornerstone of trust in the online shopping world. Where users cannot physically see what the products are like before they buy them, the ratings and reviews of users who have supposedly bought them before can make or break a product. Some e-commerce retailers are using artificial intelligence to fight astroturfing by putting more emphasis on verified and helpful reviews.

Amazon uses AI to combat fake product reviews and inflation of their popular star ratings. Built in-house, their AI machine-learning system ensures that the prominence and weight of verified customer purchase reviews are boosted. There is also preference to those reviews that are marked as helpful by other users as well as the newer and more up-to-date critiques on its site. The business is continuously reviewing several review characteristics such as ratings to detect fake reviews. They are critical to the company as they help to build customer trust in Amazon.

18. Combat counterfeit products

As with fake reviews (#17 in the list above), attributes such as product, brand and category are also useful to spot counterfeit products.

When browsing through large online marketplaces, it can be difficult for the everyday consumer to identify a counterfeit product from a third-party seller. When the consumer buys a product that looks legitimate but performs poorly, it can leave a sour taste and negatively impact the consumer’s perception of the brand.

So how can e-commerce retailers tackle counterfeit products?

Chicago start-up 3PM Marketplace Solutions adds a layer of protection for brands by adopting machine learning algorithms that spot counterfeits, and help businesses understand how consumers are discovering their products. The tech company then draws on data from multiple online marketplaces and analyses it to determine which products are in fact counterfeit. A fascinating and effective way of using artificial intelligence to tackle the painful problem of counterfeit products.

Rob Dunkel, founder of the tech start-up, recently stated that factors such as the posting rate of an account, what kind of items it sells and even potentially fake reviews on listed items, are all used to point to a counterfeiter. Clients can then submit claims with a marketplace such as eBay or Amazon, to have the shady counterfeit products removed.

19. Localise the customer experience

With the rapid growth of AI in recent years, we are starting to see more industry-focused engines appear. Wayblazer, an AI platform for the travel industry, is a great example of this.

Wayblazer use AI to provide a solution to B2B companies who merchandise hotels, activities, cruises and tours, and to companies who are looking to generate new revenue through hotel bookings. Companies also using AI powered POS Software to boost the Offline Predictions