Traditional uses of AI in ecommerce
From data mining to natural language processing and machine learning, many aspects of AI can change the way we shop online. While ecommerce has quickly adopted AI, its widespread use is traditionally limited to just a few areas:
Product recommendations
Ever added a product to your cart and been recommended a related product you didn’t know you needed? Artificial intelligence has long been used to improve customer experiences by analysing past buyer behaviour and browsing habits to provide recommended products. Machine learning captures and analyses data to create a personalised experience based on users' behaviour or lookalike audiences.
Wiser, an AI driven personalized product recommendations app for Shopify. Wiser
Automated customer service
While chatbots may be infuriating for some, their ability to provide 24/7 support has allowed ecommerce companies to deliver focused support at scale. Bots can provide simple answers to common questions, freeing up the time of live assistants better suited to solving more complex enquiries. As their capabilities grow, chatbots will be used more to process complex B2B and B2C transactions. Juniper Research estimates by 2024, consumer retail spending via chatbots will reach $142 billion worldwide—up from $2.8 billion in 2019.
Zalando’s new fashion assistant powered by ChatGPT. Zalando
Nine emerging uses of AI in ecommerce
Harnessing the power of AI in ecommerce can help future-focused companies stay a step ahead of their competition and secure sustainable growth. Here are a few opportunities that could be right for you:
1. Smarter logistics
Machine learning has been used by large brick-and-mortar retailers, such as Waitrose, to manage inventory for years. In supermarkets, weather predictions and seasonal changes are known to affect food buying behaviour; think hot weather and ice cream. The same technology is now being used in ecommerce to forecast demand, manage inventories, predict transit times and inform customers about delivery delays. Intelligent logistics can free up capital tied up in warehousing products, reduce the number of delivery enquiries, and improve the customer experience by ensuring the right product is available when needed. With an API-first approach, as seen in composable commerce, companies can easily integrate intelligent logistics through plug-and-play applications.
Image by RELEX, a demand planning software. Relex
2. Content localisation
Consumers are more likely to buy a product if they imagine using it. Think about it. You're much more likely to purchase a children’s rug if you see a picture of it in a nursery room. That likelihood increases if the room is decorated to your taste. Industry leaders like Ikea have long recognised the benefits of content localisation, showing their products in different styles according to local trends. Generative Adversarial Networks (GANs) and Natural Language Generation (NLG) tools are making it possible to almost entirely automate content production in the future - taking content localisation to the next level.
textengine.io by Retresco is one NLG provider on the market. textengine.io
3. AI-generated product images
AI-generated product imagery can help businesses create more variations of their products in specific settings. Ecommerce companies can upload a few images of their products and describe the scenario they’d like to visualise using just a few words. If you’re a homeware retailer, this means producing an image of a shelving unit in a living room, bedroom or nursery and tailoring each use case to any decor trend without needing an extensive photoshoot.
booth.ai is one provider of AI generated product photography. booth.ai
4. Content optimisation
AI technology can help analyse specific parts of a website to increase conversion rates and make changes to improve content without affecting the backend. Using AI to automate content improvements can reduce operational costs and time spent on labour-intensive tasks, reducing the total cost of ownership (TCO) while increasing online revenue. Next-generation commerce vendors, such as commercetools, have made AI-driven content optimisation easier.
5. Enhanced virtual assistance
Everyone’s heard of ChatGPT by now, and many companies are trying to find ways to integrate it. Going beyond quick answers to simple questions, ChatGPT can be used in ecommerce to provide complex recommendations, offer personalised promotions, solve delivery and return enquiries, and collect customer feedback - helping ecommerce companies improve their customer experience and offering in new ways.
Image by ChatGPT. ChatGPT
6. Assisted product searches
Have you ever used an online store’s search function to find a product, only to be shown a “No Results” page? AI may be the answer to your problem. AI-driven language models are making it possible to use natural language to find what we want. Product names can vary depending on the user's culture, region or language habits. For example, boots that keep you dry in the rain are called ‘wellies’ in the UK, ‘rainboots’ in the US and ‘gumboots’ in New Zealand. AI learns from past search data and association to improve the accuracy of searches despite fluctuations in language.
7. Pricing optimisation
AI can dynamically change product prices by analysing buyer behaviour against market fluctuations and seasonal changes. With dynamically-generated pricing, ecommerce companies can automatically offer the minimum discount needed to secure a sale during low-demand periods and ask for the maximum price during high demand. While use cases such as holiday accommodation and flights immediately come to mind, many other B2C and B2B companies experience fluctuations that could leverage AI-generated pricing.
Sniffie, IONA’s client, provides a dynamic pricing tool for ecommerce. Sniffie
8. Fraud detection
Businesses lost an estimated $41 billion to ecommerce fraud in 2022, an increase of 105% compared to 2021. With ecommerce fraud booming, companies are investing in cybersecurity and fraud protection. AI can protect businesses from risk by identifying fraudulent transactions with uncanny accuracy, stopping fraudulent transactions by analysing IP addresses, email addresses, and credit card numbers.
9. Omnichannel Experiences
Ecommerce companies can deliver unified experiences across multiple platforms - such as B2B marketplaces, social sales platforms, smart devices and IoT touchpoints - by using AI to analyse consumer behaviour, create segments and optimise content across platforms. Composable commerce solutions have made seamless omnichannel experiences more attainable by making it easier to unite commerce systems with other touchpoints.
Photo by DeepMind on Unsplash Unsplash
AI is radically changing ecommerce
To take full advantage of new technologies, companies must identify the use cases that are relevant to them. Composable commerce makes it easier to harness emerging use cases and allows companies to choose what’s appropriate. By breaking down complex architectures into smaller composable modules, top companies can use composable commerce to curate a selection of APIs and microservices that can be integrated and swapped without the need for expensive developers.
Ready to rethink your ecommerce? Get in touch to book a discovery process and start your composable commerce journey today.