Mobile apps that use artificial intelligence allow customers to get more personalized shopping experiences, while businesses get leads that are more likely to convert.

A few examples of mobile apps that use artificial intelligence brilliantly.

Example 1: Starbucks uses AI and predictive analytics

By collecting data, AI can use mobile app intelligence to generate more personalized product recommendations.

With more than 20 million regular users on its US app, Starbucks collects a lot of user data every day.

This means more personalization leading to more user convenience and thus bringing in higher sales.

Here are a few things the Starbucks mobile app can do:

This is how Starbucks very smartly engages, entices, and rewards customers for using their app.

Intelligent mobile applications also offer data-driven predictions and suggestions that can benefit users and improve their health.

Example 2: Urbandroid smart alarm clock and sleep guide

The smart wake-up feature of the app awakes the user at an ‘optimal time’ based on the individual’s sleep cycle.

It also provides a sleep tracker that monitors sleep patterns, heart rate, breathing, etc.

Its advanced AI-powered sound classification also detects snoring, sleep talking, sleep movements, etc and provides daily insights.

Users can improve their sleep quality using the suggestion provided by the app.

Watch the video here to understand how artificial intelligence understands sleep patterns, generates data-driven solutions.

If you think you’ve never interacted with conversational AI, think again. Google Assistant, Siri, Alexa are all audio chatbots that have helped you in a way or another.

Conversational AI could be a chatbot on an app or website, a voice assistant on a phone, or any other voice-enabled device.

Techniques and algorithms used in conversational AI

AI Chatbots

A chatbot, or chatterbot, is a computer program that simulates human conversation through text or voice interactions over the Internet.

Chatbots can have varying levels of complexity based on the natural language processing (NLP) engine it uses. For instance, an AI voice assistant bot will use a speech-recognition engine.

Another important thing to consider when you look for a chatbot is to choose if you want structured or unstructured conversations.

Security and privacy concerns are the main challenges of implementing conversational AI. Artificial intelligence and chatbots can’t understand emotions, communicate in native languages or dialects.

Chatbot virtual assistants are used to handle simple tasks to search and retrieve data in both business-to-consumer (B2C) and business-to-business (B2B) eCommerce industries.

With AI chatbots, virtual assistants, and conversational AI, businesses improve customer service.

A conversational chatbot can retrieve essential information on order status, payment status etc and so, can be very helpful for human customer service executives in answering repetitive requests as well.

An AI-powered eCommerce platform like ewiz commerce can offer a structured conversation chatbot that is often used by medium to small eCommerce companies.

Example 1: Tommy Hilfiger chatbot

A good example of what AI chatbots can do is the Tommy Hilfiger eCommerce mobile app:

They employed a chatbot, named TMY. The eCommerce AI chatbot provides product recommendations and advice on style besides providing customer support.

The conversational AI chatbot asks a series of questions about customers' preferences to gather information about them. It then makes outfit suggestions based on the data gathered, which are constantly refined.

You can watch a video of the review for the Tommy Hilfiger chatbot here.

Example 2: IBM Watson® Assistant

IBM Watson Assistant is a cloud-based AI chatbot that automates customer interactions using a natural language interface. It also transfers clients to human agents when needed.

Customer service chatbots are low-cost chatbots used by eCommerce retailers. Here, the AI takes care of routine tasks like tracking orders, answering customer queries, etc while retail employees can focus on other important tasks.

You can watch a video of how it works here.

Automated chatbots or AI chatbots help reduce customer service costs to the company, while customers get 24/7 customer support and a faster response time.

Visual search involves using images from the real world (screenshots, images from the Internet, or photos) as the input source for searches instead of text.

With visual search, you can take a photo of a product you’re interested in. An AI tool will then identify and match it to similar products. Visual search AI helps find items based on size, shape, color, fabric, and even brand logos or designs.

Consumers are no longer required to go shopping to see items they want to buy. For instance, they may be inspired by a friend's new dress or a work colleague's new laptop bag. With an image, AI makes it possible for consumers to find similar items through online stores.

While some retailers have created their own visual recognition tools, Google Lens and Pinterest open up a world of possibilities to customers snapping, searching, and buying anything, anywhere.

Example 1: Google Lens

Google Lens is an image recognition technology developed by Google. It maps images to information present online.

With it, you can get more detailed information about objects in your images, get insights and reviews on destinations, restaurants, menu highlights, scan images to translate text, and more. You can also get fashion ideas based on screenshots or pictures of clothing that you spot.

It is basically an image search variant to the text-based google search we have been accustomed to using.

If you have a phone with a camera and good internet speed, you can use google lens to find more information about anything and everything that you see around you.

It’s a great app for curious kids (and adults alike) who often ask a lot of questions about their surroundings.

Example 2: Pinterest

Pinterest is a visual discovery engine for finding creative ideas for cooking, DIY, graphic designs, illustrations, web designs, education, home and style inspiration, and more. You can find images for anything and everything on Pinterest.

They introduced the concept of ‘pins’ that can be images, videos or products. If you like something on the app, you can just pin it and come back for it later.

The app also lets you use your camera to search for inspiration on Pinterest if you’re on your mobile device. You can find ideas related to your photos or what’s right in front of you in real life. You can also shop for products on the app.

Example 3: Farfetch’s visual search feature

Farfetch is an online fashion retailer whose mobile commerce app has great visual search functionality.

Here’s how Farfetch uses artificial intelligence in its mobile fashion app:

Voice search enables eCommerce customers to look for information by speaking into a microphone.

Voice search uses AI in speech recognition and can be 3x faster than typing.

Computer vision and linguistics is used to recognize the voice command and distinguish each word based on phonemes.

Voice search can help the elderly, visually impaired, or even people in a hurry who don’t have the time to type out a query.

Speak 2 Software offers voice-enabled smart speakers to assisted living centers for seniors.

The ability to use voice search can benefit seniors who may have difficulty navigating a computer or using a mouse, indicating that voice search is capable of bridging the digital divide.

By optimizing your mobile commerce website for voice search, you can get better visibility online. And since many people find typing on a mobile device uncomfortable, using a voice search is a great way to optimize your eCommerce business for voice search.

Example 1: Siri, the AI-powered virtual assistant

Siri is a built-in, voice-controlled personal assistant available for Apple users.

Siri uses Artificial Intelligence and Natural Language Processing to function. You can use Siri to make calls, send text messages, answer questions, and offer recommendations based on voice search or by using buttons.

The 3 main components include a conversational interface, personal context awareness, and service delegation. It delegates requests to several Internet services, moreover, Siri can adapt to users’ language, searches, and preferences.

You can activate the voice assistant by saying “Hey Siri” into your Apple device.

If you have a phone with a camera and good internet speed, you can use google lens to find more information about anything and everything that you see around you.

It’s a great app for curious kids (and adults alike) who often ask a lot of questions about their surroundings.

Example 2: Google Assistant

Google’s Voice assistant, called Google Assistant, lets you search for your query on Google using your mobile phone or computer with a voice command.

Unlike Siri, Google offers voice commands, voice searching, and voice-activated device control that works on any Android device and smart speakers. You just need to select the microphone icon in the Google bar and speak out loud to get the results.

The system not only understands 60 different languages but can also deliver localized search results based on the language you speak.

To activate Google Assistant, you can say "OK Google" or "Hey Google" into your smart device.

Example 3: Amazon Voice Search - Alexa

A good example of a company using voice search is the eCommerce giant Amazon:

Amazon Voice Search uses speech recognition to understand and answer voice search queries. This technology also converts speech to text using deep learning for accurate results.

By leveraging content on the website like product descriptions and customer reviews, Amazon is also using AI to answer customer queries with voice search.

AI can generate suggestions based on past purchases and searches, which means buyers can find products quickly and easily using AI-based recommendations.

How do AI-based product recommendations work?

Enterprise data collected from the company and the customer is fed into an ML algorithm that identifies the information within it and establishes accurate correlations.

The system can then match the product listings to the customer information to generate intelligent recommendations based on the user’s search query.

How does personalizing product recommendations with AI help?

Based on a user's browsing history and interactions with a website, personalized product recommendations deliver content that corresponds to the customer’s interests.

The AI takes into account a user’s GPS location to suggest products based on the current weather, time, or even the route to work.

For instance, a person traveling to Alaska will receive recommendations for snowsuits, whereas a person in Miami may receive recommendations for beachwear.

Based on a user's browsing history and interactions with a website, behavior-based recommendations can deliver content that corresponds to the customer’s interests.

For instance, a person who enjoys drinking artisan coffee would get recommendations about a new cold-brew place that has opened up near his house.

AI algorithms can make recommendations based on a user’s search history and cookies to improve product discovery on multiple channels, which ultimately increases sales.

For instance, if a person searches for leather boots, they will get similar ads for boots on their browsers, social media platforms, or even gaming apps.

Example 1: Amazon’s product recommendation engine

Amazon’s AI-powered product recommendation is an effective sales and marketing strategy. It has shown proven results in engaging customers and increasing revenue.

Amazon uses item-to-item collaborative filtering, which can match and interpret massive datasets, providing highly relevant recommendations in real-time.

Each customer's homepage is customized to reflect their interests and previous purchases. Amazon also uses AI to optimize its product pages and checkout page.

Amazon produces hyper-personalized product recommendations offering on-site suggestions to visitors like “Your recommendation”, “frequently bought together”, “bestsellers”, “curated for you”, “products you might like,” “frequently bought together,” or “customers also bought”, and so on.

It also provides offsite recommendations as a follow-up activity after customers purchase a product based on their shopping behaviors, shopping history, preferences, and so on.

Amazon’s AI recommendation engine fuels 35% of customer purchases, or an estimated $50 billion in incremental sales.

As a result of the Amazon recommendation algorithm, each customer receives a customized shopping experience, helping Amazon increase gross revenue from each order.

Example 2: Alibaba’s AI ecosystem

The biggest tech company in China, Jack Ma's Alibaba is the world's largest e-commerce platform that sells more than Amazon and eBay combined.

Here’s how Alibaba uses artificial intelligence and machine learning to boost eCommerce sales. China is currently beating the USA with its machine learning and deep learning technologies.

Here’s how AI product recommendations work on Tmall.

A few incredible ways Alibaba uses artificial intelligence and machine learning

Apart from AI-powered product recommendation engines, Alibaba uses AI and deep learning in much bigger projects, around both eCommerce in China.

It is the main contributor to China’s leadership in AI across the globe, helping China beat the USA in the field as well.

On October 22, 2021, Alibaba Cloud, introduced a voice AI for business meetings, alongside a new version of its cloud computer.

The AI-powered meeting assistant, named Tingwu, can convert speech to text in real-time, create meeting summaries and post-conference to-do lists in real-time with up to 98%* accuracy.

It can distinguish up to 10 voices and identify speakers in the transcript. It understands English, Mandarin, and 14 other Chinese dialects. Tingwu AI can also autocorrect or refine notes based on the context of a meeting.

This year on October 19, 2021, Alibaba released a server chip to boost data centers’ performance and contend against US competitors like Amazon.

Its 60 billion transistors contribute to a 20% increase in performance rate and 50% boost in energy efficiency. This is higher than any other server processor in the market in 2021.

This AI-powered chatbot can understand more than 90 percent of customers’ queries according to Alibaba and serves more than 3.5 million users a day.

More than 200 robots in automated warehouses can process 1 million shipments each day.

Alibaba uses smart logistics and cloud computing to optimize its supply chain, build products and drive personalized recommendations. It has also turned many of its physical shops into "smart stores” (video).

On June 25, 2021, Alibaba DAMO Academy (the R&D branch of Alibaba) announced M6. Alibaba claims it to be better and bigger than the best AI training models present in the world, beating Google and Microsoft.

M6 is the first 10-trillion-parameter large language model — 50x GPT-3’s size, which serves as the standard to measure the rate of progress for large AI models.

According to the academy, M6 has achieved ultimate low carbon, high efficiency in AI models using 512 graphic processing units (GPU) to train 10 trillion parameter neural networks within ten days.

So it is safe to say that AI-driven product recommendations are not just a luxury but a necessity for eCommerce companies of all shapes and sizes in this day and age.

Real-time inventory management systems can help you track and manage customer orders and transactions. You can use demand forecasting algorithms and automate inventory management processes at your online and offline stores.

Using AI in inventory management, you can avoid lost sales due to out-of-stock inventory, overstocking, and clear out old stock that takes up additional space and company capital. Artificial intelligence also eliminates the need to manually update your database, leading to fewer errors.

Any good B2B or B2B eCommerce company, at its core, is a company that sells high-quality products (that are not damaged) that are safely delivered to the customer on time.

And so, good inventory management can help improve customer satisfaction, customer loyalty, and ROI.

Now let's look at a few examples to understand how Coca-Cola and Shell used AI-powered inventory planning to deliver a seamless experience to their customers.

Example 1: Coca-Cola’s AI-driven inventory placement

Coca-Cola used Salesforce to develop an app that increased inventory efficiency.

Instead of having a large staff checking stock levels of coolers, Salesforce's AI technology, called Einstein, can see the stock level by taking a picture.

Here’s how Coca-Cola began implementing AI suggestions:

Coca-Cola used Salesforce to develop an app that increased inventory efficiency.

Instead of having a large staff checking stock levels of coolers, Salesforce's AI technology, called Einstein, can see the stock level by taking a picture.

AI helped them calculate how a certain product will perform at a specific location. The technology can:

The company places less inventory of its Monster energy drink in vending machines at hospitals with emergency rooms since its AI tool recognizes that people rarely buy energy drinks there.

The AI tool also allocated two rows of Minute Maid lemonade beverages for the vending machine of a sports and entertainment stadium in Sacramento where visitors typically drink a lot of lemonade.

In addition to a 15% increase in vending machine transactions, Coca-Cola saw an 18% decline in restocking visits because it stocked the right products in the right locations.

Using the Freestyle mobile app, consumers can order their drinks ahead of time, pay via their app, and then collect their drinks at a nearby fountain. This provides Coca-Cola with valuable insight into the preferences of their consumers.

The Coca-Cola company introduced AI-powered touchscreen soda fountains in 2009 that allowed consumers to mix and match flavors from more than 100 different beverages called Freestyle.

Consumer insights are also used to generate geo-targeted marketing campaigns.

In order to use the mobile app, consumers need to register with their social media account.

Coca-Cola then analyzes their social media content to generate insights about its products' popularity in different areas based on the demographic and consumer behavior data collected by the app.

AI helps them analyze the social media content of consumers via mobile app interactions, creating insights on where, when, and how their products are consumed.

Through Facebook Messenger, Facebook users can chat with the "vending bot". Based on location data, tone of the conversation, and the consumer's Facebook activity, the bot customizes its dialect and attitude based on the user's personal preferences.

The chatbot adapts its dialect and attitude to each user based on location data, creating a personalized interactive experience.

Example 2: Shell’s immaculate inventory planning

Shell is a leader in oil exploration and production in the United States. But had an inefficient inventory planning system, resulting in a lack of flexibility in its operations.

When they switched to AI for inventory management, BestPracticeAI evaluates the results as follows:

If you want to improve inventory management in your eCommerce business, here are a few AI-based inventory and warehouse management systems you can use.

Top 3 Inventory Management Tools that use Artificial intelligence

Amazon’s Intellify helps improve your inventory health by taking the guesswork out of your inventory management system.

It offers API or batch integration to simplify interaction with your existing enterprise resource management (ERP), business intelligence (BI) systems, and inventory systems.

Pluto7 claims to accurately forecast demand weeks and months in advance.

It is a software as a service (SaaS) that uses machine learning to provide the most accurate inventory forecasts for small and midsize businesses.

IBM Sterling Inventory Control Tower is an AI-powered inventory control system that tracks and monitors your end-to-end supply chain network.

It provides insights on inventory location, identifies impact, predicts disruptions, and recommends actionable workflows to mitigate the effects. It also offers smart integrations to connect existing inventory solutions and ERP systems.

Some companies allow you to access your inventory and order management software from your mobile devices.

While most functionalities would be limited to desktop users, you would still be able to track orders, view inventory, or make changes using your dashboard.

When a customer searches for something on your search bar it means that they know exactly what they want. This means they might as well buy that product if they find it on your online store!

Would you let them go or help them find it ASAP?

Online retailers must optimize their internal site search if they don’t want to lose customers.

Artificial intelligence can help you optimize your site search function to offer your online customers more accurate and faster search results.

Personalization of search results in eCommerce

Online eCommerce stores cannot simply stop at offering a site search bar. Online shoppers want a high-quality search experience, or you will risk losing them.

Every user would see unique search results when they use an AI-powered Mobile Commerce platform

Optimizing your site search can give you a competitive edge compared to other eCommerce websites. Even giant B2B eCommerce companies like Alibaba use AI in eCommerce to better understand customer behavior and use different AI algorithms to better their customer experience.

Improved search accuracy is nothing but an improvement in the customer journey. When you do this well, it can result in a better customer experience, higher conversion rates, and organic brand promotion.

Face recognition identifies or verifies a person's identity based on their face. There are dozens of applications of facial recognition in our daily lives.

Through facial recognition, we can unlock smartphones, order food from Cali Burger, or use a point-of-sale (POS) machine equipped with cameras to make payments. These POS machines link an image of a face to a digital payment system or bank account.

4 Distinctive uses of implementing Facial Recognition in Mobile Commerce

Cart abandonment rates across all industries average 69.57% and mobile abandonment rates are even higher at 85.65%.

Any interruption in the shopping process leads to a potential buyer rethinking their decision. However, face payment technology reduces the chances of these transactions falling through due to interruptions and delays.

Many eCommerce sites have already adopted facial recognition technology. Over 500+ stores in China allow customers to pay using software like 'Smile-to-Pay'.

This software by Alipay is a financial label by Alibaba, and is about the size of an Apple iPad!

Wedome bakery based in Beijing, China incorporates this specialized facial recognition point of sale system to run a seamless transaction process.

Facial recognition technology allows eCommerce stores to accept online transactions, eliminating the need for cash, wallets, and even mobile phones.

While most eCommerce sites offer secure payment options, scammers still find ways to defraud the payment system somehow. Facial recognition technology also helps retailers spot shoplifters in a physical store.

Using facial payment technology, however, eCommerce sites can secure payments.

When using real-time identity verification when users make payments, facial recognition reduces the probability of a fraudulent transaction.

The majority of online accounts require users to keep track of their passwords. Face recognition technology, however, makes it possible to access online accounts without remembering passwords.

Clearly, there are various implementations of facial recognition to enhance customer experiences. This shows that using facial recognition is always a good idea.

Example 1: MasterCard identity-check

A MasterCard Identity Check Mobile app uses fingerprints and facial recognition to verify online payments, circumventing the need for passwords.

A U.S. trial found that 86% of respondents found the app easier to use than passwords. According to MasterCard, the app is available in 14 countries and has recently expanded to Mexico and Brazil.

Example 2: Ubamarket app’s smart facial recognition

Ubamarket is a UK-based tech company that provides shopping apps for retail stores. It allows users to scan items as they shop, earn loyalty points automatically, and check out without standing in a queue.

The app's most recent addition is facial recognition, which detects the age of shoppers when they pay for products like alcohol, which has a legal age limit.

However, people aren't always comfortable with this technology as it raises a lot of privacy concerns.

So if you’re planning to implement this into your mobile commerce app or eCommerce website, you may have to wait or provide alternate options like a fingerprint scanner or the plain-old cash and card payment options as well.

Emotion detection and recognition technology is similar to facial recognition but is more intense. Emotion AI combines the knowledge of artificial intelligence (AI) and psychology to detect emotions.

Why use AI emotion detection?

An advanced M-Commerce site or app that uses AI for emotion detection can understand customer behavior and feed it to an algorithm that detects how you interact with a product.

Emotional AI allows businesses to capture the emotional reactions of customers in real-time by:

This ultimately leads to an improved understanding of what customers like. You can then use it to get a sense of whether or not you must recommend similar products or move on to something else.

Marketing depends heavily on emotions to influence customer behavior. Customers are more likely to remain loyal to brands if they relate them to positive emotions rather than negative ones.

Using a system that incorporates cognitive and emotive reasoning has helped eCommerce businesses in improving customer satisfaction.

Example 1: Walgreens’ cooler screens

In order to track shopper behavior, Walgreens uses digital cooler screens. This system uses cameras, motion sensors, and face recognition software to target advertisements on the screens in real-time.

In order to customize your ads, it uses information such as your age and gender, as well as the current weather conditions.

Example 2: Kellogg’s emotionally impactful ads

Global food manufacturer Kellogg's is using emotion recognition technology to brand and advertise its food products.

When multiple versions of an advertisement are shown to viewers, face recognition software is used to analyze their emotional state. Based on these insights, the company then designs an advertisement that garners the desired level of engagement.

Example 3: Humana’s emotion-based customer service

The health insurance company, Humana, is using AI in emotional recognition (analyzing voice patterns) to help their call-center agents to deliver a better emotional experience to customers.

Agents receive real-time voice emotion analysis in the middle of a call, enabling them to determine if the customer is feeling frustrated, sad, or happy at any given moment.

Furthermore, it offers useful suggestions such as altering their tone of voice, speaking faster, and displaying empathy if needed, in order to turn the call around and provide a better customer experience.

Example 4: Amazon’s customizable computer vision (CV) service

Amazon Rekognition API is a simple, easy-to-use API that can quickly analyze any image or video file that’s stored in Amazon S3. It can identify objects, people, text, scenes, and activities and also detects any inappropriate content as well.

The challenges of using Emotion AI

However, emotional AI is prone to bias as it is subjective; in addition, AI is unaware of cultural differences, which makes it more difficult to forecast emotions accurately.

Various technologies associated with emotion, voice, biofeedback, and neuroscience raise ethical issues relating to privacy. In addition, the question to what extent public places are protected, as opposed to private ones, is speculated under current privacy laws.

And the moral dilemma is whether machines should determine how humans will react, especially without our permission.

AI in sales helps meet customer expectations and increase sales. Don’t believe me? Here are some statistics that show how AI impacts eCommerce businesses:

Most eCommerce businesses already use sales and marketing automation. But now they are moving to a mobile-first approach. This means delivering contextual, personalized, interactive messages on mobile devices.

Mobile marketing and sales automation tools have evolved in response to the evolution of businesses, consumer behavior, and competition.

Ideally, mobile sales and marketing automation platforms will have the same features that other automated platforms offer, but they will be tailored to mobile environments. Ultimately, this can boost productivity and increase resource utilization.

Your online store probably already includes sales and marketing tools. The only thing left is to integrate it with a mobile app on your smartphone.

Example 1: Cisco’s automation success

Cisco implemented marketing and sales automation to:

The automation resulted in:

Example 2: Kellogg’s emotionally impactful ads

Despite generating a massive number of leads from its marketing efforts, McAfee's sales team was concerned that the leads weren't of high enough quality.

Using marketing automation, McAfee implemented a scoring system and created a nurturing program for prospects that delivered the right information at the right time. As a result, the lead quality passed on to the sales team was greatly enhanced.

Through this new automated system:

The concept of dynamic pricing involves selling the same product at different prices based on the current or real-time market conditions.

You can use AI to personalize your pricing based on the current users on your website and their behavior. If your competitor’s store has run out of stock, you could even increase prices on your website.

On the other hand, if your sales have been low, you can improve conversions with lower pricing or discount models.

Dynamic pricing leads to higher eCommerce revenues as their products can be priced based on market trends, sales volume, and competition.

AI-powered eCommerce platforms allow pricing to be dynamically adjusted with the most appropriate prices.

Example 1: Amazon

Amazon's pricing model reflects this as it continuously changes based on market trends, competitor pricing, and customer behavior.

If there’s a sale there would be a huge discount on products, right? But consider product prices on non-sale days, even there Amazon has different prices based on demand or season.

By doing so, Amazon is able to sell more products at a higher profit on its website and app.

Example 2: Uber’s dynamic pricing

Because of Uber's dynamic pricing algorithm, when you request the same trip today the price might be different from what you paid a few days ago.

Its algorithm takes into account factors such as the number of requests for rides, the time of day, events, etc. If the online behavior shows that particular places and times are preferred by consumers, they may ask for more at those times. This leads to higher prices in peak hours.

Using ML, Uber generates a forward-looking forecast of a variety of market conditions and uses a system that is highly sensitive to external factors, including global news events, weather, historic data, holidays, traffic, etc.

The LSTM (long short-term memory) network lets Uber predict future prices based on past data. A deep learning model is used to make predictions before unaccounted events and future market conditions take place.

Users often abandon apps after initial installations, making it difficult to keep them engaged. App retargeting, on the other hand, enables you to get people to download or engage with your app again by reaching them across multiple channels.

By analyzing past purchases, machine learning can predict future buying patterns and optimize remarketing campaigns.

Let's consider a scenario where Jane uses your application to look for brown leather motorcycle jackets.

When Jane browses the app, her intent is captured. When she becomes distracted, she starts playing a game.

An ad is generated in real-time to target Jane based on her purchasing intent determined by cookies from her search history.

On the other hand, Jane can now see ads for brown leather motorcycle jackets and other similar products on her gaming app too. If she clicks on the ad, she will be taken straight to the app to complete her purchase.

Dynamic pricing leads to higher eCommerce revenues as their products can be priced based on market trends, sales volume, and competition.

AI-powered retargeting platforms analyze real-time user behavior to find out which users are most likely to convert. Based on this information, marketers can target their marketing efforts at the most valuable customers.

Your users engage with your app multiple times until they complete a purchase. And then retargeting ensures that they come and buy from you again.

Omnichannel engagement takes many forms. One way to think about it is to put yourself in the customer’s shoes.

Take, for instance, you have a problem with a mobile device that you pre-ordered from a brand before its official launch date. This means, only the company can solve your problem right now, and nobody else.

So what do you do?

Again, at the outlet, you have to explain yourself to the staff and finally get your device repaired. But after a few days, you see that the same problem persists. Now you have to go back to the chatbot on the website, and explain the whole story again - and the cycle repeats every time you face an issue.

Now if I were to ask you about your experience, what would you say? Did you absolutely love it?

Of course not!

What if you didn't have to explain your problem so many times, to so many people on so many different platforms? This is where omnichannel engagement could have helped you as a customer.

Omnichannel personalization provides a consistent and relevant customer experience across all online platforms where your customer exists.

Using an omnichannel AI approach, every touchpoint of your customer journey across different communication channels would be tracked and saved, including your past purchases and all the problems you have faced so far.

Today, a few companies use virtual assistants to build holistic customer experiences across channels so that they don't have to repeat their stories to different representatives of the company.

Example 1: Pega's intelligent virtual assistant

Pega is an AI system provider that lets you seamlessly move customer conversations across channels and devices without losing context.

Pega Intelligent Virtual Assistant is an artificial intelligence (AI) powered bot that creates an omnichannel dialogue with your customers. It can easily turn applications into smart assistants on any channel – from SMS and email, to Facebook, Alexa and more.

Customers and employees can use it as a banking bot, a mobile service provider bot and the company's internal IT helpdesk bot.

You can watch this video to know more about Pega here.

Example 2: Disney’s omnichannel approach

Disney gives customers the same magical experience online and in the real world with its seamless omnichannel approach to everything.

Be it your pre-booking engagement, your arrival at the airport, check-in at your hotel, or your experience at the Disney theme park, everything seems to be in perfect alignment.

With the ‘My Disney Experience’ website or app, you can book and plan your vacation, select restaurants, select visits to attractions, view a map of all the places you want to go, and more.

The My Disney Experience app helps you find and navigate to attractions using GPS and know the approximate wait times for rides. Your mobile device can also act as a ticket to any planned fast-pass attractions.

Disney's strongest unique selling point is its ‘Magic Wristband’, which is both a fast pass and a photo storage device. Every family gets one band which can be used in so many ways.

This waterproof band can be your hotel room key, your ticket to the parks, or as payment at DisneyWorld. You can also order a custom made version to personalize the design.

The wristband also links to the app, so when you take a picture of any attraction or with a Disney character, the picture will appear on your phone.

Through the integration of multiple channels, such as a website, mobile app, and smart wristband into one unified and integrated experience, Disney demonstrates how you can create a memorable seamless experience.

Ultimately, omnichannel personalization helps you create a seamless customer journey at multiple touchpoints. This allows you to provide a unique experience that can drive more growth and create more customer engagement.

Virtual reality (VR) and augmented reality (AR) simulate the experience of shopping in a physical store through a virtual environment.

When customers browse through your mobile shopping app or site, a virtual shopping assistant helps these customers through the shopping process without needing any human assistance.

Apple’s Siri was the first virtual assistant to be both highly advanced and commercially available. Following Apple's success, other tech giants like Google (Google Assistant), Amazon (Alexa), and Microsoft (Cortana) created their own virtual assistants.

Virtual assistants are increasingly being used in homes, cars, and in conjunction with numerous smart devices, including smartphones and smart speakers. Today, any eCommerce business can create an effective virtual assistant with the help of a good eCommerce platform.

A virtual shopping assistant is a good option for online retailers because they:

Virtual shopping assistants are like diligent salespeople, always eager to assist customers to decide on buying a product, hear out their problems, and recommend solutions. They can provide information on orders, answer questions, and provide product recommendations.

Example 1: Sephora’s virtual shopping assistant

Using Sephora's virtual assistant, customers can find the right products while taking their preferences into account. Once the correct product has been identified, the assistant redirects the customer to Sephora's website so the customer can complete their purchase.

In addition to the Sephora Virtual Assistant, Sephora offers virtual assistants that can help customers book appointments with a Sephora beauty specialist and experiment with different makeup color combinations using augmented reality.

Example 2: LEGO’s virtual assistant, Ralph

During the Christmas holiday season in 2017, LEGO discovered that customers were overwhelmed with too many choices when buying gifts. They also feared giving the wrong gifts to kids.

LEGO, with its creative partners at Edelman, developed and rolled out its first bot for Messenger campaign. To assist and enhance the digital shopping experience, LEGO built a virtual assistant called Ralph for Facebook Messenger.

In addition to Ralph's LEGO movie-inspired voice, he used playful GIFs and emojis to make the stressful shopping experience seem simple, entertaining, and relaxed.

Ralph also asks users a series of questions about the recipient's age, personality, interests, and budget before making accurate suggestions based on the answers. It then offers up gift recommendations, where you’d be transferred to the shopping cart on Lego’s shopping site.

Furthermore, a custom API was developed to provide localized stock updates from the LEGO store in real-time, and customers received a free gift and a free shipping code for each order. Then, a single tap would take the customer to checkout on the website.

Three weeks after Ralph's launch, the company reached more than 2.69 million people with over 50,000 virtual conversations across the UK, US, Canada, Germany, France, and Poland.

LEGO’s approach to Voice and Conversational AI had a great impact on sales and marketing:

Agumented Reality (AR) along with Artificial Intelligence (AI) opens a whole new world of possibilities

AR is a technology that superimposes computer-generated objects (image, text, video) on a user’s view of the real world, thus providing a composite view.

It’s different from Virtual Reality (VR) in which everything that a user sees is computer generated. In Augmented Reality, the technology uses the real world and adds computer-generated graphics to enhance the experience.

AR is expected to become the new human-machine interface, connecting the digital and physical worlds.

In eCommerce and mobile commerce, AR offers many promising applications such as:

As a result, there are fewer returns and cart abandonment rates.

When customers browse through your mobile shopping app or site, a virtual shopping assistant helps these customers through the shopping process without needing any human assistance.

Example 1: L’Oreal’s augmented reality makeup

With AR and live streaming technology, L'Oréal Paris USA brings professional makeup experience into homes with its virtual makeup simulation app.

Makeup Genius by L'Oreal lets you apply preset looks or try specific L'Oreal products in different shades. Each change is applied instantly to your image.

The company also lets customers book a live-streaming appointment with a beauty assistant and go for a digital makeup session. By doing so, they can receive the same personalized service that they would receive in-store.

Additionally, each session's data is recorded and stored to improve future interactions. You can watch it here.

Example 2: IKEA App

The IKEA Place app lets customers visualize furnishings in their space and customize them in real-time. By giving customers this power, retailers can experience a reduction in returns and save on logistics costs.

Example 3: Dulux Visualizer app

With its app, Dulux has attempted to solve a problem that has plagued painting companies for decades - paint testers

The Dulux Visualizer app lets users view individual colors on a wall by pointing their cameras at it. The app reads the edges of walls and applies any color desired by the user.

In addition, Dulux has an in-built tool for ordering paint, with AR's immediacy a nudge to boost sales. You can watch it here.