Artificial intelligence (AI) is changing what’s possible in online retail. Explore today’s exciting AI capabilities, innovative companies, and promising investment opportunities in e-commerce.
How generative AI is transforming e-commerce
Takeaway
THE NEW UX
“AI has been pervasive for some
time — but generative AI goes further. It can create and produce text, images, video, and numerous other types of content, and as such its potential to disrupt industries is immense. While there is a lot of buzz today, this is very much a long-term productivity story.”
What is generative AI for e-commerce?
Defining AI
The consumer
journey, personalized
Generative AI analyzes customer data and behavior patterns to enhance and personalize the consumer experience, driving online sales and retention.
THE NEW UX
Defining AI
Generative AI improves profit margins by optimizing logistics
To cope with supply chain disruptions and shrinking profit margins, e-commerce leverages AI to streamline logistics across production, shipping, warehousing, inventory, and pricing.
Optimized Ops
Are there roadblocks to generative AI in e-commerce?
___________________
1. Statista (07/2023): Revenue of the e-commerce industry in the U.S. 2017-2027. The information has been established on the basis of data, projections, forecasts, anticipations and hypothesis which are subjective. This analysis and conclusions are the expression of an opinion, based on available data at a specific date. Due to the subjective aspect of these analyses, the effective evolution of the economic variables and values of the financial markets could be significantly different for the projections, forecast, anticipations and hypothesis which are communicated in this material.
2. Statistia (08/2023): E-commerce as percentage of total retail sales worldwide from 2015 to 2027
3. FactSet (05/23/2023): Highest Number of S&P 500 Companies Citing “AI” on Q1 Earnings Calls in Over 10 Years
4. Nasdaq (09/30/2023): September, Third Quarter 2023 Review & Outlook. The potential growth of the sector does not guarantee future results
5. The Decoder (07/11/2023): GPT-4 architecture, datasets, costs and more leaked
6. Tech Crunch (04/28/2023): OpenAI closes $300M share sale at $27B-29B valuation
7. Tech Monitor (04/06/2023): Why Nvidia won’t be worried by Google’s AI supercomputer breakthrough
8. Tech Crunch (08/24/2023): Hugging Face raises $235M from investors, including Salesforce and Nvidia
9. Techcrunch+ (06/29/2023): Inflection lands $1.3B investment to build more ‘personal’ AI
10. Decrypt (06/29/2023): AI Chatbot Startup Rockets to $4 Billion Valuation With Microsoft, Nvidia Backing
11. Grand View Research (n.d.): Chatbot Market Size, Share & Trends, Analysis Report By Application
12. PRNewswire (02/23/2022): Bloomreach Valuation Soars to $2.2 Billion
13. Crunchbase News (05/24/2023): More Big Money For AI: Insider Raises $105M
14. Forbes (06/14/2023): AI And Retail: Consumer Adoption On The Rise, Yet Uncertainty Looms
15. Google Data, Global (4/6/2023): New tools to help small businesses connect with online shoppers
16. Martechvibe (03/15/2022): Bloom Raises Funds To Bring Generative AI To eCommerce
17. Globe Newswire (02/28/2023): Nextech's Breakthrough Generative AI Plus Record 3D Model Demand
18. Coresight Research (02/16/2023): CGI and 3D Product Imagery: The Future of Visual Merchandising
in E-Commerce
19. EY Global (05/16/2023): EY Future Consumer Index: Consumers losing trust and turning away from brands amid cost-of-living crisis
20. Yahoo Finance (01/26/2023): Vizcom: The Visual Design Company that is Seeking to Expedite the Process of having an Idea and Bringing it to Life
21. Journal of Commerce (08/10/2023): Logistics industry tiptoeing toward AI adoption: Freightos research
22. McKinsey (10/27/2016): Supply Chain 4.0 – the next-generation digital supply chain
23. Axios (07/25/2023): Axios Pro: Retail Deals
24. Crunchbase (06/09/2022): LilyAI
25. Crunchbase (04/21/2022): Crossing Minds
26. PRNewswire (02/23/2022): Bloomreach Valuation Soars to $2.2 Billion
27. TechCrunch+ (07/28/2021): Search API startup Algolia raises $150 million at $2.25 billion valuation
28. Forbes (9/7/2021): Personalizing Price With AI: How Walmart, Kroger Do It
Jeremy Gleeson
Head of Investment Team, AXA IM Core - Equity
Generative AI is a specific type of AI, used to create something new based on a given set of training data.
Retailers can use AI tools and consumer data to target consumers based on behavior and demographics, offering tailored marketing campaigns and discount offers pinpointed to encourage engagement and loyalty.
Targeted marketing
and advertising
The dynamic market ahead in online retail
Generative AI will transform e-commerce quickly, while potentially driving above-market returns. Investors could see opportunities at every level, from tech providers to leaders in retail AI implementation.
Takeaway
Globally, online sales will make up a quarter of total retail by 2027.²
Now every shopper can have a unique site experience and custom-picked products, reducing shopper fatigue and boosting conversion. AI tools can analyze customer browsing, purchasing, and zero-party data to generate recommendations while honing predictive accuracy over time.
Personalized consumer journeys
AI easily generates large volumes of copy and can translate, optimize for SEO, or A/B test content. AI can also quickly generate product images and 3D models. Google data reveals product offers with more than one image see 76% more impressions and 32% more clicks.¹⁶
Optimized product copy and imagery
Product design
Product design tools leveraging generative AI can spark consumer creativity, allowing them to customize products for direct purchase, or help designers rapidly develop new prototypes and stay ahead of trends.
AI demand forecasting uses historical data, market trends, user sentiment data, and input from robots to help brands make informed manufacturing and inventory decisions. Mass customization through AI design
tools could help retailers avoid costly over-stocking.
Inventory optimization
AI can automate the organization, tagging, and curation of extensive catalogs. It efficiently labels, categorizes, and removes duplicates, accelerating processes and creating an intelligent taxonomy for improved search and recommendation algorithms.
Product data and category management
AI helps retailers implement dynamic, optimized pricing based on real-time markets or consumer behavior, whether discounts or upsell opportunities. It can also help retailers manage supplier relationships and negotiate procurement contracts.
Pricing and procurement
AI can help optimize every part of
the supply chain, from suppliers and warehousing to last-mile routing
and delivery, helping to reduce costs, improve efficiency, and avoid delays. Customer-facing bots could provide real-time shipping updates.
Supply chain logistics
AI computing is costly, driving up
the cost of these services. While investments and venture capital are boosting growth today, it’s unclear if hardware, software, and computing costs will decrease.
High costs
Poor data leads to inaccurate or biased results. AI depends on
high-quality, accessible data that
is collected, cleaned, and engineered for specific use cases.
Data collection and quality
Investors should recognize that businesses will need to navigate compliance regulations and ethical considerations while balancing the risk of data breaches.
Ethics and regulations
Even as retailers race to leverage generative AI, rapidly evolving capabilities and a lack of industry expertise could be barriers to effective implementation.
New technology
Collections of information, such as data on customer behavior, sales trends, or product information, used to train and validate AI or ML models.
Datasets
This capability allows retailers to quickly generate high-quality, relevant imagery to showcase products and appeal to specific demographics. Platforms like Dall-E from OpenAI and Midjourney are current leaders in image generation.
Image generation
NLP refers to how programs can understand and generate language, which powers chatbots, search functions, sentiment analysis, and product recommendations. Hugging Face⁸, which started in NLP, is valued at $4.5 billion with investments from Nvidia, Salesforce, and others.
Natural language processing (NLP)
This involves teaching machines to interpret and make decisions based on visual data. It powers visual search, product, recognition, and indexing and tagging processes.
Computer vision
ML, a method of data analysis, uses algorithms to parse data, learn from it, and make predictions or decisions with minimal human intervention. Generative AI is a specialized version of ML, focused on generating new instances, like text or images.
Machine learning (ML)
LLMs are trained on vast amounts of text data to generate human-like text, enabling various content creation capabilities. Arguably the most well-known LLM is GPT, used in ChatGPT, and trained on 1.8 trillion parameters⁵ – hence the OpenAI⁶ valuation of nearly $30 billion.
Large language models (LLMs)
A semiconductor chip designed to handle complex calculations and parallel processing tasks. Nvidia proved to be a leading GPU provider in 2023, while Google has launched cloud tensor processing units (TPUs) as an alternative.⁷
Graphics processing units (GPUs)
Conversational chatbots
Today’s chatbots are next-level. With NLP capabilities, they are context-aware sales assistants, tailoring product discovery, recommendations, and deals in real time. They can cross-sell and upsell, assist with logistical inquiries, and gather feedback.
Yet the costs of shipping, returns, price matching, and supply chain disruptions have led to shrinking profit margins.
AI could boost sales while maximizing logistical efficiency — and early adopters will have
a competitive edge.
On the front end, AI serves as a “sales assistant” for every consumer, from product discovery to fielding questions.
Behind the scenes, AI can analyze data in real-time to optimize logistics and improve supply chain efficiency.
Investor Outlook
Some retailers have launched their own chatbots, such as online resaler Mercari’s Merchat AI, powered by ChatGPT. Carrefour was one of the first to integrate OpenAI into its customer experience, with a chatbot that helps shoppers with product selection.
Other retailers rely on vendors, such as established players in omnichannel retail like IBM’s Watson Assistant and Salesforce’s Contact Genie, or more specialized U.S.-based companies
like Inventa Holdings, Inc., eGain Corporation, Nuance Communications, and Conversia, Inc., that focus on
purpose-built bots.
While ChatGPT is popular, other NLP solutions could soon appear in e-commerce. Inflection AI,⁹ which offers AI-powered chatbot Pi, is funded by Microsoft and Nvidia and valued at
$4 billion as of mid-2023. Competitor Character.AI¹⁰ is valued
at $1 billion.
- 30.34% of the chatbot market was held by retail and
e-commerce in 2022
- 24.0% CAGR between 2023-2030 is expected for the North
American chatbot market¹¹
Tech Enablers
Tech Enablers
Tech Enablers
Capabilities
Capabilities
Capabilities
Capabilities
Investors should note the top tech companies, specialized start-ups, and leading retailers innovating with AI today.
AI Today
Optimized Ops
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Chris Iggo
Chair of the AXA IM Investment Institute and CIO of AXA IM Core
Businesses that embrace AI should in turn provide investors the opportunity to benefit from higher profits and growing market share. In an economy which might be growing more quickly, AI can be a potential driver of better investment returns.
Investor Outlook
Investor Outlook
Up-and-coming companies enabling e-commerce personalization include Bloomreach¹², valued at $2.2 billion and Insider¹³, with $274 million in funding. Algolia is a site search and discovery platform, and Adobe’s “Project Fast Filtered” simplifies large-scale product navigation.
On the retailer side, EDreams ODIGEO, one of Europe’s largest
e-commerce firms, is working with Google Cloud to build tailored travel planning experiences. Stitch Fix, an online personal styling service, openly uses generative AI for outfit selection, text composition, and feedback analysis at scale.
- Half of consumers agree they are comfortable using AI
to improve purchase experiences
- 61% of consumers trust AI to deliver them tailored
promotions and deals¹⁴
Investor Outlook
Investor Outlook
Bloom¹⁶, the product photo performance engine with $1.1 million in funding, tracks consumers’ on-site shopping behaviors to generate and deliver imagery with personalized models and environments. NexTech¹⁷, a 3D model supplier to Amazon, helps brands create Metaverse experiences and announced a breakthrough in fast, AI-powered 3D model texture creation in early 2023.
- 60% of brands and retailers plan to invest in AI to automate
product visual content online¹⁸
Well-known players in e-commerce help smaller businesses customize their sites, including Google’s Product Studio, Shopify, which offers Shopify Magic, and eBay, with its Smart Store platform.
Amazon now offers an integrated LLM tool for sellers to write product listings. Dedicated tools like Narrativa help automate the copywriting process for e-commerce, turning product specifications into unique product descriptions.
Investor Outlook
Investor Outlook
Meta has unveiled its AI Sandbox with AI-driven ad updates for advertisers. Rival Google announced a new Search Generative Experience feature built to perform smart shopping research for users and enable seamless purchases.
Startup Treat uses generative AI with proprietary and customer data to create personalized ads that incorporate elements shown to perform well with target demographics.
- 66% of consumers are willing to share their data in exchange
for cheaper options¹⁹
Investor Outlook
Investor Outlook
Customizable products are making headway in fashion. Nike offers Nike By You, which allows consumers to customize shoe colors and materials using 3D modeling, while Adidas offers several customization options during checkout. These tools could also offer retailers valuable data to anticipate consumer trends.
On the designer side, tools like CALA make it possible to quickly generate, prototype, and produce new designs, leveraging OpenAI’s DALL-E API. Vizcom²⁰ has raised $5 million in funding for its tool that turns 2D sketches into 3D photorealistic renders.
Investor Outlook
Investor Outlook
Fashion group URBN uses AI-driven o9 Solutions tools for demand planning across its global brands, while H&M Group partnered with Google Cloud in 2020 to improve demand forecasting.
- AI-powered demand forecasting could cut supply chain
network errors by 50% while speeding service.²²
Walmart uses AI to streamline e-commerce fulfillment, while Amazon uses AI algorithms to predict stock demand. Dexory²³,
a startup with $19 million in funding, offers robots and AI for inventory management.
AI/ML-powered platforms for business operations include AWS Supply Chain, Google Cloud’s Vertex AI, and Microsoft’s Supply Chain Platform, plus services from Sentient Technologies, IBM, Oracle, and Dataiku.
Alibaba Cloud offers AI-powered analytics and robotics for production, while Alibaba Group (though currently facing regulatory challenges) led the shift to mass e-commerce customization as early as 2017.
Investor Outlook
Investor Outlook
Investors may want to note players who offer solutions in this
e-commerce niche, including Lily AI,²⁴ with over $39.5 million in funding, Crossing Minds,²⁵ with $13.5 million in funding (including strategic investment from Shopify), and Bloomreach2²⁶ and Algolia,²⁷ each valued over $2.2 billion.
Other companies of interest include Pixyle, which offers image recognition software for fashion retailers, and DotActiv, which works on automated product classification.
Investor Outlook
Investor Outlook
A range of companies, like DLabs.AI, Retalon, and Alibaba Cloud, offer dynamic pricing and AI-powered promotions for consumers, often as part of broader personalization strategies.
Pactum AI enables major retailers, like Walmart, to automate supplier procurement negotiations for pricing optimization across thousands of suppliers.
- 58% of top retailers already planned to implement AI pricing
technology by the end of 2021²⁸
Investor Outlook
Investor Outlook
Some companies focus on AI tools specifically for logistics, training dedicated LLMs for industry use. Rippey.ai offers proprietary bots for forwarders that provide shipping quotes and track and book shipments. Microsoft offers an AI-driven assistant for integration in CRM and ERP systems.
- 80% of logistics professionals either plan to use or already
use AI for pricing, shipping, or customer support²¹
Investor Outlook
Using consumer data in AI requires consumer buy-in, which means retailers must balance privacy and consent with data collection.
Consumer trust
AI modeling can lack transparency, and retailers will need a way to understand the rationale behind outputs.
Transparency
The future of e-commerce is here. AI makes online shopping a hyper-personalized experience for consumers, while on the backend, it streamlines supply chains and optimizes inventory.
Online retailers, top brands, and specialized vendors are quickly evolving to embrace AI, opening the door to investment opportunities. Those leading the way today will be best-positioned for tomorrow, with U.S. e-commerce revenue expected to grow 53% between 2023 and 2027, reaching $1.4 trillion USD.¹
In the S&P 500, 110 companies mentioned “AI” during their first-quarter earnings calls,
the highest number in more than a decade.³
The tech-heavy Nasdaq index has seen 35% YTD total returns as of end of Q3 2023, as giants like Amazon, Alphabe t, Microsoft, and Apple turn to AI.⁴
New technology
High costs
Data collection and quality
Ethics and regulations
Consumer trust
Transparency
Optimized product copy
and imagery
Conversational chatbots
Targeted marketing
and advertising
Personalized consumer
journeys
Product design
Investor Outlook
Investor Outlook
Investor Outlook
Investor Outlook
Investor Outlook
Investor Outlook
Investor Outlook
Investor Outlook
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