Imagine you’re trying to write something from scratch, but you can’t seem to get started. There’s a blank page staring back, daring you to fill it with words.
Wouldn’t it be helpful to get a suggestion, a jump start, to get things going?
The same is often true for your customers when they shop online. If an item they’re looking for is out of stock, it can be daunting to find a suitable alternative. When making a big purchase, it takes effort to remember everything they need. We often hear from electrical distributors how frustrating it is to spend money shipping out a single conduit fitting because it wasn’t added to the original order.
Today, artificial intelligence (AI) can offer your customers the jump start they need to make informed decisions about your products.
Why Your Customers Trust AI Recommendations
AI is everywhere you shop or make decisions, from Amazon to Netflix to Google. As humans, we’ve grown to increasingly rely on – and trust – machines to give us product recommendations.
You’ve heard of word of mouth. Well, the “word-of-machine effect” is when humans take the word of a machine over the words of humans, especially regarding the features and benefits of a product. The good news for distributors is their catalogs are filled with functional and practical products, making AI recommendation software an excellent fit.
To illustrate why your customers trust AI’s recommendations more than humans, here are two fascinating experiments that show the “word-of-machine effect” in action.
- Haircare Product Test: In this Boston experiment, over 200 people participated in an on-the-street blind haircare products market test. Casual passersby were asked to choose between two haircare product samples, one recommended by AI and the other by a human. When participants were asked to focus on the practical, utilitarian aspects of the product, such as performance or chemical composition, 67% chose the AI-recommended sample. However, when participants focused on the more hedonic aspects of the product, such as the scent or a “spa-like vibe,” 58% chose the human-recommended sample.
- Real Estate Experiment: This experiment occurred in the Italian resort town of Cortina. Researchers asked participants to consider a real estate investment’s functional and practical or emotional and sensory-based qualities. Then the test subjects had to choose between property lists curated by an AI or a human real estate agent. When the real estate pitch focused on practicality, 60% of the participants chose the AI-recommended properties. But when the pitch appealed to the senses, 76% chose the human-curated list of properties.
As these experiments show, AI recommendations are effective at influencing customers about product features. Distributors can gain an advantage by using AI to make product recommendations to customers.
One Distributor’s Story
One industrial distributor expressed skepticism about implementing AI-powered product recommendations. How could they trust an AI tool to identify suitable substitutes and relevant add-ons for their 1 million-plus SKUs? If the AI showed customers the wrong recommendations, could it harm the relationship instead of improving it? Despite these concerns, the distributor heard about the positive impact of personalized AI recommendations from other distributors and decided to take a chance on implementing these tools.
The Results
Customer satisfaction improved, and the average value per order increased by 10%. Were the AI-generated recommendations perfect 100% of the time? It’s tough to say, but it doesn’t matter. Even if the AI models didn’t generate perfect recommendations 100% of the time, the results were clear — having recommendations that were spot on most of the time was far better than having no recommendations at all.
Why AI Recommendations Work for Distributors
Two significant factors contribute to the success of AI-powered product recommendations:
- Prompting the Buyer: Add-on recommendations are helpful suggestions that prompt buyers to consider other products they should purchase from the distributor. Even if the item displayed on the recommendation carousel isn’t a perfect match, the AI prompt gets the customer thinking about the other products and categories they need.
- The Human Element: AI recommendations don’t have to be 100% accurate because humans have sound judgment. If someone sees a recommendation that isn’t relevant to them, they’ll just ignore it and move on. The good thing for distributors is that their customers are often experts on the products they’re ordering, and they know best whether to listen to a recommendation or not.
How AI Recommendations Work
AI recommendation software uses machine learning algorithms to analyze user preferences and behavior data. Then it provides personalized recommendations for products, services or content that the user will likely be interested in. The data is collected from end-users, including purchase and search history. That data is filtered back into the system, which uses machine learning algorithms to learn from the patterns in the data. The recommendation model changes based on customer behavior and, over time, improves its accuracy.
The Power of Trusting AI
AI models may not be perfect, but their absence is far more detrimental to a distributor than a recommendation engine that occasionally slips up. If you trust a human sales rep to represent your company and recommend products to customers, you should trust AI. The key lies in understanding the limitations and strengths of AI and human intelligence and leveraging them to enhance customer experiences.
Distributors should trust AI to make product recommendations, not because they are infallible, but because they provide a valuable starting point for customer engagement, increase average order value and improve overall customer sentiment. By combining the power of AI with human experience and judgment, distributors can create a winning combination that drives growth and success in the ever-evolving world of distribution sales.
Benj Cohen founded Proton.ai, an AI-powered CRM for distributors. His company’s mission is to help distributors harness cutting-edge artificial intelligence (AI) to drive increased sales. Benj learned about distribution firsthand at Benco Dental, a family business started by his great grandfather. He graduated Harvard University with a degree in Applied Math, and speaks regularly at industry events on the benefits of AI for distributors. Benj has been featured in trade publications including MDM, Industrial Distribution, and Industrial Supply Magazine. His company, Proton.ai, announced a $20 million Series A round of funding in 2022, led by Felicis Ventures. In 2023, Benj was recognized in Forbes 30 Under 30 – the first leader in distribution to receive such recognition.