Discover the insights from our partner Constructor on how B2B manufacturers, distributors and wholesalers can build buyer confidence by employing smart product recommendations.
A key goal in B2B eCommerce is providing a frictionless buying experience. Yes, there are many complexities introduced in B2B purchase environments, like custom pricing models, different purchasing roles and approval structures, product catalogs with millions of alphanumeric SKUs, and so on.
Having a targeted eCommerce strategy alongside best-of-breed product discovery solutions — often easily paired with eCommerce platforms, through a composable approach — allows B2B companies to facilitate a more hassle-free and cohesive experience across the buyer journey.
Part of this strategy can entail delivering dynamic, AI-powered product recommendations, so B2B manufacturers, distributors and wholesalers who successfully engage their buyers, elicit interest and drive conversions.
About product recommendations
Product recommendations are strategically placed product suggestions the buyer may be interested in. There are many strategies for recommendation pods or groupings of product suggestions.
These strategies need to consider the nuances involved with driving B2B business success, such as factoring in complex product catalogs, account-specific pricing, custom discounts, etc.
But with a solution that’s purpose-built for the unique demands of B2B eCommerce, you can dynamically surface recommendations that reflect customers’ needs, priorities, roles, history and intent for easier buying.
When applied strategically, product recommendations pack a punch, being both good for buyers and good for business.
Customers benefit from a more helpful and efficient purchasing experience. Putting relevant, personalized suggestions at buyers’ fingertips increases their confidence in the purchase they’ll make.
This benefits the business as well, as greater confidence among buyers translates to increased satisfaction. Product recommendations also provide valuable cross-sell and upsell opportunities for businesses, contributing to better digital experiences that increase loyalty and deepen relationships over time.
Princess Auto, a leading provider of farm, industrial, garage and hydraulics tools and equipment, uses AI-driven product recommendations throughout the online purchase journey that factor in buyer behavior.
As customers view products, “You might also be interested in these…” recommendations on product detail pages (PDPs) map to the person’s intent and history.
Princess Auto also leverages product recommendations on its checkout pages to catch customers’ eyes prior to purchase and increase average order value (AOV).
Strategies to build buyer confidence with B2B product recommendations
Building B2B buyer confidence via recommendations requires a nuanced approach that addresses buyers’ specific business needs and concerns. Here are some key strategies to consider:
With all product recommendations, it’s important to show them in the right place and at the right time.
They should match the buyers’ intent and reflect where they are in their journey, speeding up the pathway to purchase. With the right purpose-built technology, recommendation pods can be optimized for a variety of KPIs, including AOV, RPV and customer lifetime value (LTV).
Common placements for recommendation “blocks” or pods include on your:
eCommerce homepage
Category pages
PDPs
Search pages
Order/checkout pages
404 pages (helping reduce abandonment)
They can even be used in email campaigns, to achieve more personalized outreach.
When placed thoughtfully and helpfully within these areas, product recommendations don’t interrupt the buyer journey but, rather, bring additional value: Increasing buyer confidence in what they’re purchasing and whom they’re purchasing from.
Your buyers have different needs, pain points and goals. So, when it comes to product recommendations, one size doesn’t fit all.
To boost B2B buyer confidence with product recommendations, personalize them to the buyer at hand. For example, there are often many variations of products, restrictions or conditions for each account as well as multiple people who may access it — all considerations to factor into personalization.
Orderer vs. buyer permissions can complicate personalization efforts as well, where one user is approved to build out an order while another can modify or complete it.
With an AI-native recommendation engine that analyzes customer clickstream data to allow for a consolidated view of each individual and account, you can drive useful, accurate personalized recommendations, instilling buyer confidence with targeted suggestions.
Leading B2B distributors and manufacturers employ product recommendations to encourage various buyer behaviors and drive sales, such as:
Repeat purchases. Let buyers know when it’s time to replenish materials and supplies.
Related products. Highlight items that are commonly purchased together, such as spare parts and maintenance supplies for machinery or other secondary items that go with the main purchase (e.g., toner with printing equipment).
Cross-category bundles. Create a bundle or kit to promote items across product categories (e.g., a facilities maintenance package with cleaning supplies, tools, HVAC filters, etc.).
Customized product/pricing bundles. Spotlight relevant details and promotions for specific clients.
Suitable replacements for out-of-stock products. Recoup buyers’ interest by highlighting alternative items that meet their business needs.
Bulk discounts. Encourage higher-volume purchases by showing where bulk discounts are available.
To ensure product recommendations address the specific needs, concerns and requirements of B2B buyers, keep a couple of additional points in mind:
Good recommendations come from good customer data. As in, data about the customer (their history, intent, business, industry, etc.). While good recommendation and personalization engines can make targeted recommendations to first-time visitors — and even for new products — the more info collected about a customer, the more finetuned your recommendations can be.
Good recommendations come from good product data, too. This includes specifications, features, compatibility, use cases, etc. Because B2B buyers often require more technical details to make informed decisions, product listings must be complete and accurate. Poor data drives poor experiences — as the saying goes: Garbage in, garbage out. But when product data is complete, up-to-date and accurate, recommendations can surface more relevant items and are much more likely to drive conversions. AI-based solutions are available to help with this, generating and enriching product data to improve product catalog quality and discoverability.
Using the right tools to improve the B2B digital customer experience
With a versatile recommendations engine, layered on top of a composable commerce platform, you can create digital experiences that engage and motivate buyers, boost their confidence and increase your bottom line.
Product recommendations are one key tool in your toolbox when it comes to aiding in product discovery and improving B2B buyer experiences.
Learn more ways to build frictionless B2B commerce experiences with this guide from Constructor and commercetools.
Nate Roy is director of brand and content at Constructor, a leading AI-based platform for eCommerce product discovery and search. He is passionate about building seamless and interconnected customer journeys that deliver truly differentiated value at each stage — drawing heavily from his background in customer success and sales roles. Prior to Constructor, Nate was director of presales engineering at Paperless Parts, sales engineering manager at Salsify and technical consultant at HubSpot. He also served in the U.S. Army National Guard as a UH-60 (Blackhawk) mechanic.