Black Diamond makes climbing, skiing, and hiking products designed for customers who are always reaching higher, faster, and further.

Black Diamond itself strives to give its customers precisely what they need to reach their goals. The company uses Commerce Cloud Einstein to personalize product recommendations for a better shopping experience and to increase sales.

Not long ago, Adam Smart, Senior Web Merchant at Black Diamond, was manually loading all on-site product recommendations. This time-consuming task could not be personalized or executed in real time.

“We were very eager to get away from manually loading on-site recommendations,” said Smart.

For an automated approach, the company implemented a third-party product it thought was meeting its needs, but “when we heard that [our commerce provider] Commerce Cloud was embedding a recommendation engine into the platform, we were excited to try it, based on our past success with Salesforce products,” said Smart.

 

We were very happy with the results. Clearly, the defining metric of the test was the revenue lift.”

ADAM SMART | SENIOR WEB MERCHANT AT BLACK DIAMOND

Black Diamond conducted a side-by-side A/B test to compare performance of the two solutions.

“Typically with A/B tests, we see a small lift from one side, which lets us know the better path. We don’t usually see a test where we have 100% confidence in one side, but that’s what happened,” Smart said.

With Commerce Cloud Einstein Product Recommendations, Black Diamond saw a 9.6% increase in conversion rate, and a 15.5% increase in revenue per visitor.

“We were very happy with the results. Clearly, the defining metric of the test was the revenue lift,” said Smart.

He said the implementation was out-of-the-box simple and nearly flawless. Plus, as an embedded component of Commerce Cloud, Product Recommendations eliminated the duplicative costs of using a third-party provider and automatically leveraged the customer and product data already living in the commerce system.

 

As is best practice, Black Diamond placed the recommendations at the bottom portion of its product detail pages.

“We didn’t set up any custom rules,” Smart said. “We used the algorithm, and the system dynamically populated the products.”

Product Recommendations leveraged machine learning to suggest products for both known and anonymous shoppers across the entire shopping journey. The recommendations are generated by the Commerce Cloud Einstein engine, which models shopper activity and affinities in real time to predict the most relevant products for each shopper. With every click and interaction, the engine gets smarter.

Black Diamond is one of nearly 100 Commerce Cloud customers to implement Product Recommendations powered by Einstein, with great results.

“Personalization is king these days, so anything we can personalize we’re going to look into, especially if we don’t have to go with an outside provider,” said Smart. “We really trust Salesforce.”

 
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