Just like B2C, B2B business buyers are purchasing more products online than ever before. In fact, online revenue for B2B ecommerce is forecasted to reach $7.88 trillion in 2022. And McKinsey research indicates that 35% of B2B buyers are willing to spend $500,000 or more in a single transaction through remote or online sales channels. Like their consumer counterparts, B2B buyers want the online experience to be as simple and convenient as possible — which means product recommendations tailored to who they are and what they want.
The truth is that, while B2B selling is “business,” it’s also a very personal business — with years-long relationships cultivated between direct sales and their customers. As B2B commerce shifts to online channels and face-to-face time wanes, your ability to connect more meaningfully in the digital space will become essential.
B2B buyers expect consumer-like experiences
Of course, the consumerisation of B2B is not new. But while it once was considered a business differentiator, now it’s an absolute expectation. Buyers want their experiences to be fast, easy, always on and mobile first. They want features like quoting and customer-specific pricing. And they want easy access to sales reps. But that’s not all.
They’re also expecting you to use the power of data to drive increasingly personalised experiences — through product recommendations.
Product recommendations powered by AI (like Product Recommendations by Adobe Sensei) can help B2B merchants deliver more relevant product recommendations to individual buyers, increase conversion rates and average order values and automate once tedious and time-consuming merchandising tasks. By freeing up resources, merchandisers can then work on more critical areas like analytics, user experiences, search management and more.
Product recommendation types
By 2026, IDC predicts that companies will use AI to deliver deeply personalised journey engagement, eliminating 40% of marketing and sales human touch points. Product recommendations can fill that space, especially if they live throughout your B2B website — on the homepage, search, category pages, product pages, in the shopping basket and confirmation pages.
There are also four different types of B2B product recommendations. The first is “behaviour-based”—and it focuses on the buyer’sprevious purchasing patterns. Examples include:
- Bought this, bought that - Recommending items most often purchased by buyers who purchased the specified item.
- Viewed this, bought that - Recommending items most often purchased by buyers who viewed the specified item.
- Viewed this, viewed that - Recommending items most often viewed by buyers who viewed the specified item.
- Recently viewed - Displaying products most recently viewed by the buyer.
The second category of product recommendations are “popularity-based.” They focus on:
- Conversion (view to basket) - Recommending products with the highest view-to-basket conversion rate. Simply put, out of all the buyer sessions that viewed the product, what percentage added that product to their basket?
- Conversion (view to purchase) - Recommending products with the highest view-to-purchase conversion rate. Out of all the buyer sessions that viewed the product, what percentage actually purchased the product?
- Most added to basket - Recommending items most frequently added to baskets by buyers within the last seven days.
- Most purchased - Recommending items most purchased by buyers within the last seven days.
- Most viewed - Recommending items most viewed by buyers within the last seven days.
- Trending - Recommending items based on recent momentum of the product’s popularity.
The third recommendation type is “Item-based.” It’s focused on previous product searches and looks for:
- More like this - Recommending items based on similar content and attributes.
- Visual similarity - Recommending similar looking products to the product being viewed.
Finally, the fourth recommendation category is “Personalised shopper-based”:
- Recommended for you - Recommending items based on each buyer’s current and previous on-site behaviour.
Several B2B distinctions
While much of this may sound very similar to consumer recommendations, an important distinction is that B2B shop fronts often require more complex logic, which dictates both product visibility and pricing for specific customers or customer-groups.
As a result, your platform needs to honour category permissions, shared catalogues and customer-group-specific pricing. For example, if you’ve hidden certain categories from your retail customer segment, then a shopper in that segment would not be shown recommendations for products in those categories. Also, when you define a shared catalogue for specific customer groups and companies, those shoppers will see recommendations only for products they can access. All recommended products will reflect correct customer-group-specific pricing based on each shopper’s customer group.
The language used to recommend should also change. Instead of “Users also bought this,” buyers would see something like, “Users in your company also bought this.”
Do not underestimate the value of product recommendations
Despite these distinctions, product recommendations are well worth the effort, as they’re proven to drive both higher revenue and a better customer experience. For example, 35% of Amazon's revenue is the result of product recommendations. Personalised product recommendations have been known to increase conversion rates by 320%. And 60% of consumers now say they will likely become repeat buyers after a positive personalised shopping experience with a retailer.
In some ways, product recommendations may be even more important for B2B buyers because B2B merchants tend to have large and varied product lines. Not every customer can know all the product possibilities.
And while B2C merchants will aim to have a user swap a less expensive item for a more expensive item (up-sell), with a secondary goal of cross-sell (buy a related item to go with your original item), B2B merchants have a different focus. They’re looking at cross-sell, complimentary products and increasing units in the basket. As a general rule, B2B companies strive for a higher number of units per order, as opposed to average basket size.