by Lucien Chemaly, Head of Engineering at eddress
Do you think a robot makes a good seller?
This may seem like an odd question, but you'd be surprised to know that many people would, in fact, prefer to buy from a robot.
Artificial intelligence, AI for short, has been an instrumental element of the Amazon e-commerce platform's success. Upselling and cross-selling strategies account for over one-third of the eCommerce giant's revenues. AI is the secret ingredient in Amazon's success recipe, maximizing upselling and cross-selling conversions through enhanced machine-learning personalized recommendations. Indeed, AI injects a new life into the old online shopping style.
What makes AI an indispensable tool for online shopping? After all, product recommendations and personalized content have been around for a long time already. So what difference does AI actually make? The major point of difference between AI solutions for online shopping and traditional e-commerce customer experience is the level of real-time customer behavior understanding. The typical "Dear Susan, we thought you'd like our product X" recommendation email uses knowledge extracted from Susan's data, demographics, and interests. But what if Susan's interests and needs change? Say Susan's data from a few years ago depict a single, independent, and fashion-loving graduate. The new Susan, an established IT professional and mother of a toddler is unlikely to engage with recommendations made using outdated data. That's why to remain relevant, the marketing team needs to go back to the drawing board to include further data. Using static data allows for accurate and relevant personalization as long the customer doesn't change. AI is the ever-adjusting bridge that connects the current customer's behaviors and needs with your online shopping business.
The importance of AI in the e-commerce sector
So, what is the big deal about AI? Artificial intelligence can be found almost everywhere in your day-to-day life. Indeed, a Gartner report forecasts the worldwide AI software market to reach over $62 billion in 2022, an increase of 21.3% from the previous year. The AI market is rising even though its integration into business operations is still in its infancy. According to Gartner experts, companies need to find "use cases that deliver significant business value, yet can be scaled to reduce risk" to demonstrate the impact of AI investment on business stakeholders.
AI application in businesses improves core processes by increasing the speed and accuracy of strategic, knowledge-based decision-making processes.
Before diving more into the many benefits of using artificial intelligence in online shopping, we've listed some of the most common uses of AI in this sector.
- Chatbots and virtual shopping assistants: Advanced chatbots can interpret the words of your customers 24/7 to provide dedicated help around the clock, ensuring they can have a positive customer experience online.
- Personalization: The AI software uses machine-learning technology to derive significant insights from the collected and generated customer data. This means customer segmentation and recommendation are more relevant and accurate.
- Automated product description: When you have a handful of products to upload online, it's easy to create description content yourself. But when your stock contains hundreds or thousands of products, it can be time-consuming and laborious to do it yourself. AI solutions can generate quality and relevant product content.
How AI is changing the online shopping experience
AI applications in e-commerce are transforming the way businesses operate and market to their audience, saving you time, money, and workforce.
Conventional database search engines push out a list of all the products or references matching the search terms. AI delivers smart search results by using information from past searches and browsing history, existing customer behavior data, and predictive search (aka anticipating their next needs).
AI-powered searches utilize knowledge about the customer to adjust the search results for:
- Personalized, need-based search results; for instance, IT professional Susan searches outdoor gear. The AI can consider the current weather to adjust the results. On a rainy day, Susan will see the waterproof gear.
- Intelligent profiling for marketing and upselling purposes; the AI knows that Susan is also the mother of a toddler and can include additional kits tailored to her family needs, such as a child carrier.
- Prolonged online visits as on-site smart search results increase visitors’ engagement on the website by showing results that are tailored to their needs.
- Better on-site SEO; bounce rates and conversion rates are important SEO factors in monitoring how relevant a website is for users. Smart search decreases bounce rate and increase conversion, improving SEO rankings.
Siri, Alexa, and Google Assistant have popularized speaking on your device. As a result, more and more users use voice searches and commands rather than typing. AI solutions can allow customers to use their favorite voice assistant to perform searches or other operations as part of online shopping. With this technology, devices can interact and respond to human questions in natural language. The voice shopping process enables customers to make a purchase using smart speakers or chatbots, acting as an assistant passing the online command on the customer’s behalf.
You are familiar with the media stories of Alexa accidentally being activated and ordering items from Amazon in customers' houses. Voice shopping is a trend to follow, and one that has thankfully learned from its early mishaps. Nowadays, busy customers rely on voice shopping to save time and hassle. The technology also supports independent shopping for individuals who would otherwise need further assistance, such as visually impaired individuals.
Intelligent AI-driven product recommendations make up over one-third of Amazon's revenues through strategic upselling and reselling. According to research, personalized product recommendations increase online shopping conversion rates by 915%. To put it clearly, a recommendation engine uses machine learning algorithms to filter data and suggest the most relevant products/services to a particular customer. It operates on the principle of identifying patterns in the collected consumer behavior data.
They provide many benefits, including:
- Increasing customer retention and sales, as customers receive relevant recommendations, encourages them to stay with the same business.
- An increasing number of returning customers, as satisfied customers are likely to come back and buy again.
- Enabling high-performing personalized email campaigns, using AI product recommendations in marketing email campaigns to suggest relevant products to each customer.
- Personalizing the shopping experience; the feature ensures customers see the products that are relevant to them, instead of having to scroll through your entire stock. This saves your customers time and also ensures the website is geared up to turn every visitor into a lead/buyer.
Which stocks are running low? What is going to sell this season? AI can not only monitor your stock levels but also aggregate data and analytical knowledge to improve your inventory strategy:
- Forecasting changes in market demands using comparison data from previous years, real-time market monitoring, and also latest news for trend identification. For example, the AI can order more product X stocks ahead of the Christmas season because product X is popular and always sells well during this period.
- Identifying potential issues such as weather-related delivery delays or supply problems. The AI can use weather forecasts and geographical data to identify where issues may arise, such as how a tornado forecast can affect supply delivery, and adjust accordingly by choosing other suppliers or ordering via a different schedule.
- Tracking real-time economic changes using market and stock data. It can ensure you don’t overstock when your customers can’t afford to buy, for instance, or help you avoid price increases for your stocks.
- Sales projections based on analysis from current and previous sales. The projection is done using data month-on-month and year-on-year data via machine learning algorithms to predict how much the business is likely to sell.
As a rule of thumb, AI inventory management can reduce supply chain mistakes by up to 40%, preventing damaging costs. Additionally, the increased accuracy also reduces lost sales caused by incorrect stock numbers and misunderstandings of consumer demand.
Why stick to the automated "how was your order" email when you can do so much more? AI can manage big data and maintain effective customer engagement throughout the post-sale process:
- Automated follow-up communication, such as when a customer is satisfied with their order, the system can send a “leave a review” email.
- Automated complaints, returns, and refund management, such as when a customer is not satisfied, the system can record the issue and make easy decisions about replacement, refund, and/or return. More complex issues can be directed to the customer service team.
- Automated limited-time offers for upselling and follow-up sales. This is the typical “24-hour only” offer for a product or service related to the customer’s current purchase.
- Automated customized offers to existing customers. The AI could use Susan’s current data to make a special offer on her birthday, for example.
Conclusion
AI-based solutions for online shopping improve both your business and your customer experiences. Using machine-learning technologies and algorithms, artificial intelligence has become instrumental to online shopping success in a hyper-competitive environment. Enhanced customer experience maximizes sales and saves business time, such is the promise made by AI to the e-commerce sector.
But at eddress, we believe there is still a lot more to uncover. The potential of AI for online shopping is forever transforming the customer experience. Businesses can pair AI with underutilized AR (augmented reality) and VR (virtual reality) technology to deliver a hyper-personalized, automated, and immersive sensory experience to the customer. With the growing adoption of AI, it would make sense in the future to let your business's AI schedule product and brand discovery activities on partner platforms. We can imagine a scenario where businesses will let the AI plan marketing campaigns and ensure ads can be seen by the relevant audience, for instance. We can expect a future where AI becomes part of off-site campaigns, such as targeting Susan with AI-created ads and replacing traditional Google display advertisements.
