Rakesh Kumar, chief technology officer at Pimcore Global Services
In its Digital Economy Index report released in March 2021, Adobe claimed that 2022 would be the first trillion-dollar year for U.S. ecommerce. The increased adoption of artificial intelligence (AI) fuels this rapid growth, which is reshaping the ecommerce experience of today’s consumers.
From subtle changes like reducing product return rates to more apparent ones like hyper-personalized shopper journeys, retailers across the globe are experimenting with AI for a variety of use cases.
Thanks to the high emphasis on customer centricity, the need for human-centric AI interaction has become a vehicle not just to outdo the competition but deliver in a more open and resilient marketplace. Studies show that 70% of American and European decision-makers in the ecommerce industry believe that AI is a significant change for their business. AI is transforming the ecommerce industry by predicting customer shopping patterns based on purchase history, products searched, and browsing habits, as personalized product recommendations increasingly influence customer choices.
By entering the realm of customer behavior, AI is already assisting ecommerce businesses in online searches, identifying prospective consumers, sensing customer interests, presenting relevant products at the right time, and implementing analytics to broaden reach and customer base. AI is helping global brands like Nike raise the bar when delivering exceptional customer experiences. The iconic brand uses AI algorithms to offer tailored workout regimens and product recommendations as part of its customer loyalty programs.
But it’s not only the prominent players—mid-sized businesses are also leveraging the AI advantage to enhance customer experience. ecommerce retailers like The North Face utilize AI-driven virtual assistants to understand customer requirements better and provide personalized product recommendations based on real-time customer inputs.
Ways AI helps retailers
Simply put, AI enables ecommerce players to prepare better for the game ahead. Analyzing trends and customer behavior patterns can help improve sales processes and enhance strategic go-to-market decisions that impact the bottom line. Let us explore how:
- Targeted marketing: A recent Deloitte study revealed that three out of the top five priorities of early AI adopters are developing new products, augmenting existing products and services, and enhancing customer relationships. Targeted marketing is what ecommerce companies swear by while employing AI at the initial stages of the customer journey. With AI, they can target potential buyers in the “consideration” phase, guide them in their product research, and help them find their desired products. Using AI, ecommerce brands can define predictive patterns to forecast customers’ buying decisions and easily identify buyers who are ‘most likely to buy.’ AI enables a 360-degree customer view, allowing businesses to establish targeted marketing strategies and execute effective campaigns with rich digital content to increase conversion rates.
- Personalized recommendations: With Amazon setting new standards for personalized shopping experiences online, mid-sized ecommerce businesses are investing big time in AI to engage new customers and boost repeat sales. Studies show that 80% of consumers prefer to purchase brands that offer personalized recommendations. AI empowers ecommerce with a real-time view of customer preferences and helps them deliver suitable product suggestions by analyzing purchase history, clicks, and search queries. This leads to cross-sell and upsell opportunities and unique shopping experiences that have the customers hooked forever. Whether a large, well-known brand or a mid-sized ecommerce business, AI-driven personalized recommendations and one-to-one customer experiences guarantee a strong competitive position in today’s over-crowded market.
- Customer segmentation: One of the cornerstones of successful ecommerce marketing, customer segmentation, is what differentiates leaders from laggards. Thanks to AI, customer segmentation is no longer limited to the traditional demographic parameters. It is a far more complex, value-driven exercise that allows ecommerce marketers to group customers in real-time, based on behavioral data without any human bias. With an increasing demand for hyper-personalized customer experiences, ecommerce companies can no longer be happy with knowing ‘who’ buys their products. Instead, they must know ‘where, when, and how consumers interact with their business to devise successful retail strategies. AI-driven customer segmentation enables ecommerce businesses to adopt advanced targeting approaches to serve smaller customer groups with clearly defined attributes—these aids in optimizing marketing efforts immensely.
- Strengthening sales processes: By integrating AI with CRM, ecommerce businesses are fulfilling customer demands faster and boosting their sales processes to uncover new opportunities. Research shows that brands can gain more leads (over 50%) and achieve cost benefits (40-60%) by leveraging AI for sales. AI helps mid-sized ecommerce businesses to streamline their checkout process by pre-qualifying customers and leads. It simplifies prospecting, creates better buyer personas, and helps sales reps identify high-value customers. By automating lead qualification and nurturing, AI allows sales teams to focus on qualified leads. AI also automates repetitive tasks so that sales reps can spend more time on selling products. This empowers sales teams with a real-time view of deal status in the pipeline and offers insights on deal scores to improve sales forecasts.
- High-end shopping assistance (chatbots and voice assistants): AI-enabled chatbots have radically altered the ecommerce industry. Studies show that while chatbots have ramped sales by 67%, response times have improved by 4x, and customer satisfaction has shot up by 24%. What makes chatbots more effective nowadays is that they are highly capable of two-way communication with the user. They don’t merely tell them what to do but also listen to their questions. AI-driven virtual assistants and bots are also very effective when nudging users towards a desired location, like a webpage for new products and promotional offers. Besides providing updates on orders, returns, and loyalty points, bots are increasingly used by mid-sized ecommerce brands to function as personal shopping assistants that can offer tailor-made advice and personalized tips for a high-end shopping experience.
Many believe that the emergence of disruptive technologies like AI and machine learning (ML) have contributed to the recent boom in online retail sales—up from $1.3 trillion in 2014 to $4.8 trillion in 2021. As borderless ecommerce becomes mainstream, AI is in for more rapid integration with retailers pumping in more money in tools that enable differentiators like personalized recommendations, voice search, virtual assistants, and more.
Researchers project retailer spending on AI to be $7.3 billion in 2022, with 54% on customer service and sentiment analysis, 30% on automated marketing, and 16% on-demand forecasting. Besides improving customer experience—the goal of any retailer—AI-driven platforms are increasingly used for demand forecasting, which is emerging as a vital tool for ecommerce businesses. With the advent of ‘special shopping days’ like Black Friday and Boxing Day, an accurate assessment of customer demand and correct inventory planning has attained utmost importance.
As we welcome 2022, ecommerce businesses face an interesting mix of challenges and opportunities, with little room for error. Top priorities are managing demands, adapting to fluctuating customer priorities, meeting sustainability goals, and tackling supply-chain disruptions. That said, as economies recover and demand gradually picks up, ecommerce business leaders will rely heavily on AI to unlock growth opportunities, adapt to changing consumer needs, and focus on the bottom line.
Pimcore provides open-source software for running ecommerce sites and data management systems.
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