AI in Ecommerce: Transformative Tech Reshaping Online Store

ai in ecommerce

Hollywood has shown all kinds of hypothetical situations involving artificial intelligence over the decades. While this is a fun topic to discuss in good company, we want to examine the reality of what’s possible with today’s technology and discuss how these tools allow your retail business to reach new heights using AI in eCommerce.

For online retail, AI eCommerce delivers invaluable capabilities, elevating customer experiences and supercharging critical operations. Integrating the latest innovations promises sizable revenue growth and competitive separation, meaning understanding this matter will be crucial for ongoing success.

Throughout the following article, we’ll cover several aspects of artificial intelligence in eCommerce, discussing topics such as:

·         How AI is reshaping eCommerce.

·         The benefits eCommerce AI provides retailers and customers.

·         Specific use cases of AI in eCommerce.

Amazon has set the bar for AI in eCommerce for many years, but with today’s tools, retailers can access copious, economical options that allow digital storefronts to compete globally and successfully. Because Amazon is familiar to most readers, we’ll reference them a time or two in the sections below. Image from Amazon

How is AI reshaping the eCommerce Industry?

To a degree, AI in eCommerce has played a role in online retail for decades. But today, widely available solutions for almost every operation imaginable can be implemented into new and existing platforms, often in just a few months’ time.

We’ll get into the specifics shortly, but for now, let’s examine a few of the most meaningful capabilities inherent in most solutions: powerful analytics.

Until recently, trends and other useful insights remained buried in pools of data – without explicitly looking for specific trends, such insights would stay hidden, which is arguably the most valuable capability of AI, generally speaking. Image from McKinsey

User behavior leaves behind trails of data that are far too dense for humans to read, parse, and interpret fast enough (or at all) to be able to even begin to test their hypotheses, let alone apply them!

Connected analytics automates analyzing data around established events from different components to assess known associations while uncovering trends that may otherwise go unnoticed.

Data analysis becomes significantly faster by connecting these systems to tools like generative AI that can quickly compile and generate highly visual reports. Via an eCommerce AI strategy, Retailers have the flexibility to apply knowledge and adapt accordingly; they can effectively engage with customers in a more personalized way over longer periods of time.

How AI is Used in eCommerce

When building custom eCommerce solutions, your retail business can connect data from products throughout a tech stack to learn and automate various processes. Many retailers are already using eCommerce AI for:

Precision Demand Forecasting. By analyzing enormous datasets that include past sales, current market conditions, and external forces, machine learning (ML) algorithms accurately predict optimal future inventory volumes, preventing costly under or over-stocking.

Dynamic Pricing. Understanding inventory needs also lends itself to AI eCommerce solutions like AI-connected pricing schemas that can respond in real time to fluctuations in supply, demand, and even competitor actions to sustain competitive pricing.

Hyper-Personalization. Propensity modeling categorizes customers based on common and specific behaviors (i.e., spending and user search history), allowing the delivery of functional, fully customized storefronts, product suggestions, and promotions tailored to micro-segment preferences. This is much like what you see on Amazon’s home page when logged into the site.

Recommendation Accuracy. Historically, Amazon’s product recommendations have accounted for up to 35% of their retail business. Powerful algorithms drive on-site suggestions and filter into other marketing campaigns, such as email, by intuitively analyzing extensive browsing and purchase data to display relevant products primed for conversion. When recommendations work, they lower bounce rates, keeping customers on the site longer.

Operational Efficiency. AI is already helping with tasks like warehouse labor and transportation. Businesses can also capitalize on artificial intelligence in eCommerce for other productivity optimizations. Automating select manual administrative processes – ideally across the organization – via intelligent bots and assistants reduces overhead expenses and liberates human talent for higher-value initiatives.

Many chatbot solutions are rapidly emerging, like this Shopify plugin from LiveChat. Developers can further build custom solutions that fully interface with other systems, securely enabling automation for a wide swathe of customer service tasks.

How AI Has Helped Retailers Improve Online Sales

Many providers of AI eCommerce technology are continually working to improve their platforms, meaning that over time, products and platforms will evolve with more dynamic offerings.

Currently, many providers offer solid standalone AI-driven tools or suites, but only a handful offer truly one-stop shops for AI tools. As such, working with designers, developers, and strategists is vital to identifying the best solutions for your retail business needs.

When getting started, we agree with other experts who agree the following areas are typically the best starting points for boosting eCommerce sales with AI.

Search Infrastructure

Upgrading on-site searches with natural language processing (NLP) and ML allows this feature to grasp query meanings and display relevant results instantly. This is a vast improvement for most services, as most customers (85%) find Google faster and more accurate than embedded search functions on websites across the board.

NLP Capabilities

Customers and businesses should be rejoicing as we’re nearing an age where there should be little-to-no need for lengthy phone calls to resolve standard to mildly complex customer service issues! Launching intelligent chatbots as an eCommerce AI solution can further answer common questions and autonomously tackle certain tasks, easing support burdens.

Predictive Modeling

Making inventory and pricing processes data-driven through demand forecasting algorithms that combine internal data like past sales with external signals from the broader market helps guide decision-making. This approach of using AI in eCommerce can also work hand-in-hand with product recommendations, too, like avoiding over-recommending a product that could easily oversell and disappoint eager customers.

Recently, this special edition, pink-colored Starbucks and Stanley collaboration cup made headlines, with fans of the brands camping outside Target to purchase one of these items. Like physical storefronts, customers can feel irked when expecting to be able to purchase a highly-advertised item to make sure to plan accordingly. Image from Chicago WGN9

What is an Example of AI in eCommerce? Here are 7

Let’s take a quick look at some specific use cases of concepts and technologies for artificial intelligence in eCommerce.

1) The Hyper-Personalized Shopping Experience Keeps Customers Engaged

Imagine a virtual shop assistant who knows your preferences, like a best friend or spouse who buys clothes you’ll actually wear. AI makes this a reality by incorporating browsing history, purchases, and trends from similar shoppers; eCommerce AI recommends products customers are more likely to love, potentially increasing sales by up to 35%, according to McKinsey.

Combining this with rewards from robust customer loyalty software integration – a highly desirable feature for some 56% of respondents in a recent study – will maximize engagement for more than half of your users, thus increasing spending.

2) A Search Function That Works Keeps Users on Your Site or App

NLP understands what you're searching for, even if you use weird synonyms or misspellings, thanks to an enormous set of training data that simply hasn’t been possible with more traditional arrays used in the last generation’s decision-making models. Vector search further refines results, suggesting similar items based on visual and functional attributes.

Customers who can’t easily find something are more likely to resort to a search engine like Google, where the odds of them purchasing from your store drop dramatically.

Searches can further be empowered with valuable functions like speech-to-text for customers who like (or need) to speak queries, which often take a different form than written queries, even when seeking the same thing. Further, adding computer vision can radically enhance on-site searches, allowing potential customers to share images and find matching items on your site.

3) Flexible Pricing Allows Adaptation on the Fly

Static price tags will still be necessary in many cases, but AI-powered dynamic pricing adjusts prices based on real-time factors like competitor stock and demand, pulling real-time data directly from your warehousing systems. For example, let’s say a competitor runs a sale on a popular item – your AI eCommerce assistant can update your price to remain competitive around acute changes, thus maximizing profits.

4) Chatbots Provide Immense Value

Some customers want help at 3 AM – that’s just how it goes. Regardless of when a customer decides to seek help, chatbots can be at the ready, day or night.

Because chatbots and NLP have diverse applications, consider that some 61% of those responding to a recent survey from Salesforce indicated they prefer self-service for simple issues. These AI-powered assistants answer questions, offer personalized discounts, handle basic issues, and free up human agents for complex problems.

5) Inventory Management Made Easier

AI in eCommerce for warehousing predicts inventory needs with ML, helping prevent costly stockouts and overstocking. Eventually, warehousing robots connected to these systems will be able to autonomously move stock around a facility and assist with inventory auditing using connected computer vision-powered equipment.

Any application of robots is exciting, and these can help augment labor with cost-effective, autonomous solutions.

6) Better Tools To Fight Fraud

AI can be trained to use complex algorithms to recognize instances of brand forgery and other kinds of fraudulent activity faster than older-generation heuristics. By sharing among networks, these security solutions can actively and securely monitor activity on different channels, issue alerts, or even stop malicious behavior in real-time.

Of course, fraud is ever-evolving, but by leveraging ML, AI eCommerce will be better equipped to recognize misdeeds early before causing extensive damage. Similarly, this concept also works for content moderation, where AI can help remove problematic users from stirring up trouble in social components or on-site reviews.

7) Automatic Notifications Can Keep Conversion High

Abandoned carts are a problem for all retailers – eCommerce AI analyzes user behavior and triggers targeted reminders in connected systems, such as email or mobile notifications, ideally bringing customers back to complete their purchases. This simple tactic can significantly boost conversion rates by using mobile notifications or emails to give potential buyers one last nudge.

Building the Future of Online Shopping with Us

We know what a challenge it can be for retail organizations to fully grasp the breadth of potential for AI-powered solutions in eCommerce, as well as effectively fold them into operations. Our business is keen on the changes in the market and skilled at working hand-in-hand with organizations looking to take their offerings to the next level. Looking to start work on a new or existing retail solution or digital storefront? Get in touch!

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