The Hidden Cost of Manually Updating Product Data on Your Website
By Benj Cohen
Are you losing customers because they can’t find what they need from your website?
Your customers expect B2B websites to have detailed product information such as descriptions, features, visual assets, pricing and availability. If your website doesn’t, they will turn to your competitors to find what they need.
Those are just the minimum requirements for customers. You can elevate your game by showing online shoppers tailored recommendations including related, complementary and substitute products.
Think of Amazon. The company never misses a chance to recommend a related item at every stage of your shopping experience. You can do that, too.
Unfortunately, manually updating product information for hundreds of thousands of items is difficult – if not impossible. It wastes valuable time, and manual processes are prone to human error. Over time, inaccuracies and lost time add up.
The result: a poor customer and employee experience.
Your ecommerce team has other priorities. No matter how dedicated they are, manually mapping product relationships could take years. While that’s happening, product lines and specs are changing. Product information is going out of date.
You need help. If you can’t tell the buyer which items are related, similar or pair well together, your customer experience will suffer, and you’ll miss valuable sales opportunities.
B2B customers spend just 17% of their time meeting in person with potential suppliers, according to Gartner. This limited amount of face-to-face interaction with a sales rep means your ecommerce site has to work even harder.
Customers like to do research online to compare products before reaching out. This is especially true for younger generations.
Is your website up to the task of answering their questions?
To ensure your ecommerce site lives up to expectations, you need a product recommendation engine, powered by artificial intelligence (AI).
What Are Product Affinities and Why are They Important?
Product affinities are pairings between similar or related items. For example, gloves and safety glasses are two very different items. But they both serve the mission of safety. Because of this, customers frequently buy them together.
When your database connects these, customers searching for gloves will see safety glasses as a recommendation.
That makes it easier for them to find everything they need in one visit. It’s also a way to guide customers with a more personalized experience on your website.
How Does AI Help?
Most distributors have decades of data, which can feel overwhelming. Without AI, this data is just noise. This is where AI comes into play. AI models can process vast amounts of messy, unorganized information to find sales and customer behavior patterns.
For instance, if the AI model discovers that customers often purchase two items in the same order, it will tag them as “related.” Then, it will suggest the same pairing to future buyers. This is collaborative filtering and is the model Amazon has used for decades.
Doing this manually is far from comprehensive given the vast amounts of data distributors have to sift through. AI-powered automation removes those limits.
With so many products and so little time, the only way to get up to speed is with the help of AI. You can’t afford to miss out on the upsell and cross-sell opportunities.
Some ways AI improves upselling and cross-selling include:
? Similar Products: When customers browse an item that’s out of stock, AI will automatically identify substitutes for that product. AI does the heavy lifting so your team doesn’t need to manually hard-code product associations. This makes it easy for customers to get what they need from you – without buying from your competitor.
? Frequently Ordered Together: Guiding customers to order everything they need in a single order boosts revenue and increases efficiency. Frequently Ordered Together items aren’t similar – they’re complementary. Our earlier example of gloves and safety goggles falls into this category.
? Complete the Cart: Recommendations like “Customers Also Bought” and “Add to Cart” show online shoppers products similar customers added to their cart. This boosts sales and ensures buyers get everything they need in a single order.
? Due-to-Reorder: By looking at each customer’s transaction history, AI identifies specific products customers are due to reorder to protect existing business and prevent churn.
McKinsey found that businesses that implemented automation benefitted from lower costs, greater productivity, improved quality control, greater employee experience, and higher customer satisfaction. They also experienced reduced operating expenses.
The sooner you update your items to reflect affinity tags, the sooner you will see higher sales and happier customers.
Benj Cohen is the founder of proton.ai.
INDUSTRIAL SUPPLY MAGAZINE
The November/December issue of Industrial Supply magazine features an in-depth cover story about Kimball Midwest. Plus, we're featuring articles by contributing writers Dirk Beveridge, Frank Hurtte, and Mike Marks, as well as interviews with numerous product and distribution industry experts.
