With so much data created in the form of site visits, clicks, purchases and other activities, the value of interpreting and leveraging that data has become the key to success.
That’s where Artificial Intelligence comes in.
AI’s ability to not only examine massive amounts of data but to separate significant events from background noise has created new opportunities for deeper customer relationships. On top of that, the real-time processing speed that powers AI algorithms helps retailers take advantage of often small windows of opportunity. Together, these capabilities are pushing AI to the forefront of innovation all over the retail landscape and transforming the way brands interact with consumers.
Let’s look at just some of the areas where AI is changing the way ecommerce and retail works.
As an expected feature, the ability to search for a particular product or category of products doesn’t impress anyone but AI is taking things to the next level.
In addition to serving its basic purpose of directing customers to where they want to go, AI-powered search now makes it easier than ever to expand search results with products, based on metrics like color, style, brand and even size. In an age when every step on the customer journey is personalized and based on behavioral and other data, even search results can be optimized for individual customers.
This personalization is the foundation of the value that AI brings to all applications but especially to retail and ecommerce.
The benefits of more refined search results are clear. In addition to getting exactly what they were looking for, customers get a look at similar or complementary products that they might not otherwise find on their own. Even when this doesn’t lead to a purchase, it makes a better impression on customers by giving them more of the kinds of options they’re looking for.
With AI, there’s no need to rely on keyword tags alone to organize search results. With the comprehensive data it collects, AI can instantly evaluate the relevance of results to search queries and broaden the range of displayed options.
Meeting both modern customer expectations and business needs in terms of sales is easier when search results are optimized every time for every customer. Just as with site content, there is no one-size-fits-all option when it comes to product searches.
Along with search bars, recommendations are the other standard feature that helps direct customers and users to what they’re looking for. This goes beyond conventional ecommerce platforms to sites like online video streaming services that depend on recommendations to make it easier for viewers to find content that suits their preferences, thus keeping them watching and renewing their subscriptions.
Advanced, precise recommendations are only possible through the use of AI. By processing massive amounts of data and drawing informed conclusions about the most likely choices of customers with certain characteristics or tags based on behavioral and demographic profiles, AI can produce the relevant recommendations in real time and at scale like nothing else can. This is key to delivering the kind of personalized shopping, viewing or browsing experience that keeps engagement and satisfaction high.
No matter how automated, easy to navigate and streamlined online interactions may become, customers will always need or want to talk to a human for various reasons. There will always be questions, problems and other situations that can’t be fully handled by selecting from a list of options and hitting “send”. It’s becoming increasingly important for brands to let customers know that someone is always on standby to help if needed.
These days, that someone is increasingly likely to be an automated, AI-generated chatbot, capable of a broad range of interactions and a very strong substitute for their human counterparts. Chatbots are a cornerstone of the modern concept of “conversational commerce”, where ongoing dialogues between brands and consumers can take many forms and cross over multiple platforms, from social media posts to email campaigns to live chat.
Using AI, chatbots can very closely simulate the human component of typical conversations that take place in the context of customer support and common troubleshooting situations. By aggregating and analyzing huge numbers of recorded chat sessions, chatbots can not only deliver the proper response to a question, but can diagnose the problem and select the appropriate response in most cases.
The reduced costs of customer support made possible by chatbots has put better service within reach of more brands, promoting its rapid spread throughout ecommerce. While other contact channels like email will always be available, look for chatbots to become the go-to solution for addressing customer needs as its functionality continues to grow thanks to the data processing power of AI.
Customer reviews are powerful bits of social proof that can sway decisions about what to buy or whether to buy at all. Research consistently shows that product reviews have a very strong influence on buying decisions and the more there are on a product page, the better.
The problem, however, is the growing number of fake reviews used to create artificially positive or negative impressions of a product’s value or quality. The stakes are high— a very positive rating is often the path to continued success and a low rating can kill a product immediately after launch. Fake reviews can artificially inflate a rating or unfairly take it as low as it can go.
Preserving the integrity of customer reviews is critical for retailers too since a lack of confidence in their authenticity undermines overall trust in the site. Even the biggest platforms, like Amazon, have to deal with this trend and, once again, AI is there to provide a solution.
Much the same as it analyzes chat histories to make chatbots better, AI looks through huge numbers of reviews that are verified as being authentic and identifies the characteristics that define them. Things like length, structure, tone, key words and other metrics are used to compare to new reviews and make decisions about whether they are real or not. Those that don’t make the cut can be deleted or flagged for review while those that are approved can be highlighted or given “verified” status.
Given the importance of legitimate reviews, even negative ones, ecommerce platforms can’t afford to let them become a Wild West free-for-all where anything goes. There has to be some form of management and moderation to preserve their credibility and the trust that customers place in them. Only AI can handle that amount of data in real time and make automated and accurate decisions about which reviews are likely to be fake or otherwise inconsistent with the kinds of reviews you want to have on your page.
Legitimate reviews of all kinds help reinforce the trustworthiness of the product itself and the site that’s selling it and AI makes it possible to automate the process of managing them.
In the context of enhancing the user experience in ecommerce and retail, AI’s value lies in the converting oceans of data into actionable insights in real time. This means being able to leverage that data even as it’s updated and changed and use it to create a more personalized and relevant browsing, shopping and after-purchase path for every customer.
Every click and page view is a tiny data point that, when collected and analyzed, helps create a more complete customer profile. Using AI, the shape of that profile reveals contours and details that can’t otherwise be seen. When you’re aware of these details, they can be applied to things like search results, recommendations or other customer interactions.
With ecommerce established as an increasingly vital segment of the retail industry, we can look forward to more innovation powered by the unparalleled capabilities of AI-powered data analysis.