The impact of AI across commerce promises to be far-reaching. We are already seeing startups building AI-powered solutions across personalization, customer service, supply chain management, fraud detection, and increased automation across many manual tasks.
Two areas in commerce we see significant opportunities are discovery and personalization in eCommerce, and supply chain management.
eCommerce Discovery and Personalization
Conversion rates in eCommerce are typically under 3%, with many categories between 0.6-1.5%. This means that for every 100 visitors on a site, fewer than 1 makes purchases in many cases.
At Silicon Road Ventures, we have seen more than 100 companies over the past 3 years trying to solve each of these problems.
AI could prove to be a powerful tool in improving conversion rates. Here are a couple of ways how:
Data shows that when shoppers are shown products that are relevant to them, they are more likely to purchase. This is intuitive but can be challenging to implement, especially with the more widespread online privacy regulations being implemented.
Here’s how AI can help. AI can improve personalization by analyzing large amounts of data on customer behavior and preferences, and then use that information to offer tailored recommendations and shopping experiences.
Imagine you're shopping on an online clothing retailer's website. The website has an AI-powered recommendation engine that uses your browsing and purchase history, as well as other data points such as your location, age, and gender, to suggest items that are likely to be of interest to you.
As you browse the site, you notice that the recommended products are not only relevant to your preferences, but they also match your style and fit preferences. You can also see how the recommended products would look on you, thanks to the AI-powered virtual try-on feature.
In addition to the historical information, the website's AI system analyzes your behavior on the site in real time, making adjustments to the recommendations based on your clicks, page views, and purchases. This allows the system to continuously improve the accuracy of its recommendations and offer even more personalized suggestions.
By offering highly personalized recommendations and shopping experiences, the retailer can increase the likelihood of making sales, improve conversion, and build customer loyalty. The use of AI in this context can help businesses to improve customer satisfaction, drive repeat purchases, and ultimately increase revenue.
Supply Chain and Logistics
Up until COVID-driven supply chain issues, logistics & supply chain management was largely a specialization inside commerce. But, once consumers were impacted, this niche was thrust front and center on national news media. For a time in 2020 and 2021, toys weren’t available for holidays and lead time for new cars stretched to months. Consumers felt the crunch of a fragile supply chain.
This was not just an inconvenience, but one that hit the wallet, as well. As a result of the reduced supply curve and equal or increased demand curve, prices rose for the same items. Thus, we entered into one of the early accelerators of the inflation situation we now find ourselves in today.
AI can help solve these problems in the future. Here’s how:
Businesses often track detailed data on their supply chain operations and inventory levels, production capacity, and shipping times. AI’s ability to process and extract key insights across vast amounts of data can help businesses to reduce costs and improve delivery times.
AI can improve supply chain management in commerce by analyzing data from across the supply chain, identifying patterns, and making predictions that can be used to optimize operations. Here's an example:
Imagine a large retailer or brand that relies on a complex supply chain to get products to customers. The company uses an AI-powered supply chain management system that analyzes data from a variety of sources, including production schedules, inventory levels, shipping times, and weather forecasts.
Based on this data, the system can predict future demand and adjust production and shipping schedules accordingly. For example, if the system predicts a surge in demand for a particular product in a certain region, it can automatically adjust production schedules to ensure that there are enough products in stock to meet demand.
One of our portfolio companies, Pull Logic, is doing exactly this using predictive intelligence from Georgia Tech research.
The system can also optimize shipping routes and delivery times based on real-time data, such as traffic conditions and weather patterns. This helps to reduce delivery times, improve efficiency, and reduce costs.
Additionally, the system can monitor inventory levels in real time and automatically place orders for new supplies when stock levels get low. This helps to prevent stockouts and reduce the risk of overstocking, which can lead to waste and unnecessary costs.
By using AI to optimize the supply chain, the e-commerce company can improve efficiency, reduce costs, and provide a better experience for customers by ensuring that products are delivered on time and in good condition.
In summary, with the advancements in AI we are truly at the bleeding edge of what’s possible in commerce. We know there are existing legacy problems that need to be solved, but we are excited to see a future where AI can be used as a predictive intelligence solution to anticipate and solve problems before they arise.
As a firm, innovation in commerce is exclusively where we focus. If you are building a company in this space, we would love to hear from you. Please reach out here. (firstname.lastname@example.org)