Many articles have been written on Artificial Intelligence and its potential in the future of eCommerce and mobile commerce but only a few have actually mentioned how artificial intelligence AI can boost your mobile commerce and eCommerce business.
Since you are looking at this topic, you already know what AI is. So, without repeating what you know let’s get to the primary reason why you are here!
Areas in mobile commerce where you can use AI
Search Engine Functionality
The ease with which an online customer can find a product on your application has become one of the most crucial things in the mobile commerce business.
By processing the natural language of customers using the mobile application, AI applications narrow and contextualize relevant search results for the customer – a feat known as customer-centric search.
It wasn’t long ago when a search for “flower vase” would yield both flower and vase products. Now, search has become much more advanced thanks to AI being able to understand that no, you don’t want any flower related products, just a vase for your flower, thank you.
AI has now become so user-friendly that it displays search results in a visual format that is easily digestible, grouping similar items as necessary.
How does AI improve search engine functionality?
AI tags each item with certain qualities, such as size, color, shape, and category. Those tags enable search engines to deliver relevant results and compare products.
AI can also use these tags to show customers complementary products the way most of us keep seeing other related products when we are looking for something on Amazon. For eg, suggesting mobile covers and screen guards as an add-on when you are looking to buy a smartphone).
Through search engine functionality alone, AI not only directs customers to the products they want much faster, reducing the time of each transaction but also boosts more sales by providing them with relevant items that they would not have thought of getting for themselves in the first place.
Most mobile commerce businesses have started providing you with product suggestions regularly. Your streaming service gives you movie recommendations, your clothing store sends you notifications and emails with outfits you might like and more. All of these are automated with the help of AI.
Machines review troves of data to provide the product recommendations you see: past purchases, search history, third-party data, and relevant demographics for each customer. They analyze what other customers similar to you have bought recently, and look at predicted behavior patterns to guess what you’ll want to buy in the near future.
Yes, retailers know how irritating it can be when you’re repeatedly offered a product you don’t want. They don’t want to drive you away as a potential customer with unsuitable recommendations, which is why getting their AI algorithms right is so important: relevant, high-value recommendations drive conversion rates and shorten the sales cycle.
We’re in an age now where brands need to be personable. Look up any major fast-food company on social media, and you’ll see how they interact in a generally friendly, approachable (sometimes humorous) way with anyone who contacts them. It’s likewise important for online retailers to feel personable to their customers while still providing an individual experience, which is why they’re turning to AI.
Machines review a customer’s location, purchase history, search history, and other data to do more than just make product recommendations. AI can, in fact, alter the web interface that the customer sees. With customizable web interfaces, retailers are able to push out relevant, helpful content at the right time that is specific to the customer, rather than generalized to any potential shopper. The result: increased customer engagement and greater likelihood of a purchase.
E-commerce businesses that can not only collect the right customer data but analyze and use it to drive strategy will remain ahead in the era of personalization. Customer data insights gathered through an AI lens help retailers understand their target customers better and can even drive the discovery of new target groups.
Data insights also support strategic decisions on sales and discounts to offer, and at which times of the year. Even more far-reaching, the insights collected by AI can impact decisions made on what kind of new products to offer, or what kind of products to bring back.
A Device-wide Experience
E-commerce businesses are trying to reach you through your phone, through their websites, through email campaigns, and – the latest development – through tech wearables. AI aggregates results across all of these devices to provide a complete picture to companies on their customers and how they’re using technology, assisting them in targeting customers.
In the future, you may see a scenario like this: you’re on your laptop browsing an online retailer’s website for a tent when you get a notification on your phone that there’s a new sale – 50% off all camping gear! This provides a more integrated shopping experience that can create added value for the customer by connecting them to what they need quickly.
A key part of shopping, whether online or in-store, is customer service. With online shopping, there isn’t the benefit of salespeople ready to answer your questions or direct you to what you need. We already know that banks are turning to chatbots and virtual assistants to solve this issue, and online retailers are doing the same.
A chatbot can simulate a human conversation by using a trove of natural language data and observed speech patterns. In a time where customer service must be 24/7, chatbots never rest and can handle automated processes such as orders and returns in a split second. Chatbots are also being used to help customers find what they’re looking for and answer any questions, providing more convenience to the customer who no longer needs to send an email or call a support number.
Retailers are using chatbots to target you on social media platforms as well. Brands know you’re often logged in to your social media profile while shopping online. They’ve now started leveraging this – for example, by sending you a Facebook message updating you on your recent order or messaging you about a new sale.
Ideas on how to use AI in your Mobile Commerce business model
To create a customer-centric search
Customers often abandon eCommerce experiences because the product results displayed are often irrelevant.
Mobile app development companies can build smarter apps using AI that has the ability to see the world as you do with the help of advanced image and video recognition, empowering businesses to develop a customer-centric experience.
Leveraging machine learning, the AI software automatically tags, organizes, and visually searches content by labeling features of the image or video.
You can 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.
Your customers will soon be bidding adieu to impulse control as new software platforms that drive mobile commerce applications to create innovative visual search capabilities.
As well as finding matching products, AI can help your customers to discover complimentary 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.
To identify and target potential customers
According to Conversica, the sales team misses out on atleast 33% of marketing leads. This means that businesses including yours are missing out on a lot of pre-qualified potential customers who might actually be interested in your product or service.
Furthermore, most businesses have tons of unused 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 with the help of AI.
With the development of AI, customers would get special offers based on their product search, online research, and in-store dwell time. In other words, retailers have begun to make progress in their ability to remarket to customers.
The sales game is up the notch and will keep changing with businesses being able to respond directly to the customers in no time. As has provided businesses with the ability to read the minds of customers. Insight, guys!
To normalize personalization
With the pace of advancement that artificial intelligence and machine learning technologies going through, new deep levels of personalization have started to penetrate the fast-growing mobile commerce world.
Whereas AI-based personalization for eCommerce takes the multi-channel approach. New AI engines, such as Boomtrain, sit on top of the multiple customer touchpoints to help the business analyze how customers are interacting online through mobile applications.
The thing about the AI engine is that be it a mobile application or website, or an email campaign, it continuously keeps monitoring all devices and channels to create a universal customer view. This unified customer view enables mobile commerce businesses to deliver a seamless customer experience across all platforms.
The next time a customer is browsing something on your website, they may receive a push notification on their smartphone about your flash sale for the product that they wanted. They directly make the purchase on their phone, making it easy for both parties.
Implement virtual assistants
With so many customers making purchases online, some of them might need a little help online at times.
After all, what is the use of cloud-based AI software agents?
We’re all familiar with the Jarvis of common men: Siri, Google Assistant and Alexa, and they have made the idea of talking to a phone, laptop or even a home appliance sound less weird by normalizing the idea. But normalizing isn’t enough. The usability of the virtual assistant in real-life scenarios and problems is what’s going to make the best of it or else they will end up becoming boring commodities for the user once they are past the novelty.
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.
You can use it smartly as Amazon uses its Alexa on Amazon’s Echo device where customers can discover local events through BookMyShow, arrange transport to and from the event or different places via Uber or Ola, or even order food from Domino’s, Swiggy or Zomato (and track the order status in real time).
The need of an ‘assortment intelligence’ tool
Retailers now have to keep on changing their pricing strategies. This is why a lot of multichannel retailers have become more and more flexible with their price structuring, in order for them to retain their customers.
The best way to tackle a situation like this is through assortment intelligence, a tool that facilitates an unprecedented level of 24/7 visibility and valuable insights into competitors’ product assortments.
Through the help of AI, it is now possible for you to monitor your competitors’ product combinations, that is segmented by product and brand as well as the percentage of overlap. This intelligent tool will provide you with the ability to quickly adjust your own product combinations and pricing with high accuracy.
This intelligent software can provide your business model with a strong backbone to make specific assortment and planning decisions, and track the business impact of your actions.
Tackle fake reviews using AI
Fake reviews can kill the brand as well as the customer. It’s not only unethical but also immoral.
With so much of advertisements flooding our screens every day, we have all as customers become aware of our decision-making skills and have made ourselves ore resilient towards these advertisements. This is why most customers (including me) prefer the word of mouth review about different products.
If previous customers who had purchased your product had a positive experience, then the next customer will end up buying the product too.
In fact, around 80% to 90% of online shoppers read online reviews and make their decisions to buy based on positive online reviews.
What if these reviews are fake? People will end up believing those reviews make their decisions accordingly.
Creating fake reviews is known as ‘astroturfing’ and is widespread across many mobile commerce applications and services. 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.
You can solve this issue easily with the help of AI and this is how you can do it:
You can fight astroturfing by putting more emphasis on verified and helpful reviews. You can build an in-house AI machine-learning system from Archisys to ensure that the prominence and weight of verified customer purchase reviews are boosted.
There are many more ways in which your mobile commerce and eCommerce business can benefit from AI.
We at Archisys have years of experience in bringing up radical changes within eCommerce and mobile commerce platforms. Being a leading web and mobile app development company, we can let you know more about AI implementation and its various possibilities based on your business model.
We believe that there’s nothing that technology cannot do as long as you have the capability to imagine. Let’s talk more about AI together, shall we?