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How Artificial Intelligence is Building The Future of eCommerce

How Artificial Intelligence is Building The Future of eCommerce

eCommerce won’t be the same after this year’s events.

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While the whole planet was frozen by the coronavirus pandemic, offline stores found they couldn’t compete with even the smallest online stores when people’s lifestyles were limited by their homes or neighborhoods.

But those who have just started online sales this year will quickly find out what to do to sell efficiently on the internet. This is why the overall competition will rise.

Wondering how you can gain a foothold at this moment? Take a look at modern technologies – artificial intelligence (AI), machine learning (ML), and big data analysis.

There are numerous applications, services, and programs created on these technologies, but not all of them are equally applicable to online retailers. And they’re quite expensive to implement.

So before you go adopting some fancy new technology, let’s have a look at ways AI can improve eCommerce growth, increase conversion rates, and improve the customer experience.

What is AI?

AI technologies help computers complete tasks humans would otherwise accomplish by successfully training computers in various abilities and by helping them learn from experience.

The whole idea of AI began in 1956, so it’s already an old and reliable technology with a strong mathematical and software base. There are a lot of different AI technologies being developed:

  • Deep learning
  • Natural language processing
  • Machine learning
  • Fraud detection
  • Neural networks
  • Cognitive computing
  • Computer vision
  • IoT-based technologies
  • And so on
Machine Learning Tops AI Dollars

Image Source: Statista

It’s been a long time since modern business settled on the internet, so AI has a lot of work to do with all the bytes of behavioral, financial, and marketing data that businesses have stored. And even if two out of five AI startups aren’t AI-based at all, you can still find AI-based solutions to intensify your sales growth.

The biggest negative of AI technologies is that they’re totally dependent on the data you feed them. If there’s not enough data or it’s of poor quality, you won’t get much use out of it. And it takes time to integrate this technology into your data ecosystem.

Where and why should you use AI in an eCommerce business?

As I mentioned, AI can’t work without volumes of data. That’s why before implementing AI, your data quality matters. AI motivates businesses to bring together departments – sales, marketing, advertising, customer service, even logistics – into a single data structure where data quality is the number one priority.

When all business data is stored and collected correctly – no data loss, no looping, no format disorders, all connections logically bounded and AI technology used for processing this data – you’ll get high-quality analytics with enough power to solve hard business problems, improve processes, and strengthen the customer experience.

Here’s a brief list of benefits you can obtain by implementing AI in your business:

  • Smartly assist customers with their search thanks to conversational commerce. Using AI, you can improve the search logic on your website and create a chatbot assistant that helps your customers place orders anywhere and anytime.
  • Make only personalized offers. By tracking all touchpoints and saving all products your customers have seen and all prices they’ve reacted to, you can determine the specific blend of goods and offers each customer wants. 
  • Stop guessing your customer’s path and predict it instead. Make your customer journey as smooth as possible with AI-powered recommendations. When you can predict your customers’ behavior, you get a competitive advantage due to flexible margins and the possibility to estimate your future marketing plan performance.
  • Reduce human errors in supply chain planning and adjustment. Make your inventory and goods available at any time in the volume your customers need by means of AI. This optimization is possible both online and in-store and can give you real-time 100% transparent warehouse stock levels.
  • Detect problems before they hit you. Get notifications of anomalies or suspicious transactions, vendor activities, fraud, and shrinkage while you still have time to get involved in the situation and find out what’s happening. 
  • Pump up your offline points of sale. If your AI collects information from sensors like video cameras, you get the magical ability to track your customers inside your physical stores. You can find out where people go, where they stop, and if they’re new or returning customers. You can also attract customers by making the best online offers available in stores.

To solidify your knowledge, let’s review a few examples of AI implemented in eCommerce.

Examples of how AI helps in eCommerce

Improve personalized targeting with predictive AI-based analytics

AI-powered sales targeting is one of the most popular applications of predictive analytics. It’s used for automatically determining customers who want to buy now and sending them personalized offers.

From a technical point of view, it’s looking for customers among your target audience who have the same set of features as a typical “ready to buy” group of existing customers.

This task is impossible for a human but doable for an AI algorithm. 

You can create many to-do lists of automated reactions for defined types of customers:

  • Churning customers
  • Seasonal purchasers
  • Customers who have given feedback
  • Wholesale customers

AI experiments can result in a growth in sales, minimize deal closure times, and automate the whole sales process.

AI bots to deal with customer overflow

You need a bot to follow up with a massive number of leads after a successful advertising campaign. AI bots are most useful when they can react properly and in a timely manner to any message from your potential customers.

The most pleasant (and maybe unpleasant) thing is that you’re in total control of the way your bots talk with leads. For customers, chatting with a bot is like chatting with a company representative, which means it’s quite risky for the company’s credibility.

Your bot has to:

  • Make initial contact with customers
  • Answer FAQs based on simple scripts
  • Schedule a meeting or a day to get back in contact if a lead can’t reply immediately

Even the simplest AI bots work better than no answer at all, increasing conversions. Bots can reply by email with answers based on trigger words or respond via a chat window on your website or by Facebook Messenger.

AI visual search and image recognition and their creative applications in eCommerce

Visual search can provide exclusive customer experience and enable numerous experiments. If you’ve ever used the Pinterest Lens for visual search, you know what I’m talking about. The technology hidden inside is AI.

Retailers like Asos and Target also use AI technology for virtual fitting rooms. Choose a photo and category of goods you’re looking for and the algorithm will give you a best-fit match.

AI Visual Search And Image Recogniton

Image Source: Pinterest

You can build thousands of ad campaigns with visual search or image recognition or augmented reality. And doing so will make your brand outstanding and memorable.

What’s next?

Advertising will never get you more than 400% ROAS, goods won’t sell themselves without detailed descriptions, photos, and video content, and customer service will never only give refunds without needing to handle complaints. Avoiding new technologies that can help your business optimize expenses and multiply revenue leads nowhere.

Let AI technologies help you adapt your business to the new era of immersive digital consumption.

Guest author: Margaret Kashuba is the Chief Marketing Officer of OWOX BI, a marketing analytics service that consolidates data from disparate systems, evaluates the performance of advertising campaigns, and quickly builds the reports you need. OWOX developed an easy to use a product that allows marketers to get any reports without SQL syntax with the help of a report builder.

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