Black Diamond

The Problem

Black Diamond (www.blackdiamondequipment.com) is a manufacturer of climbing, skiing, and hiking products. Based in Holladay, Utah, the firm maintains global offices in Switzerland and China. It was founded in 1989 through an employee purchase of bankrupt Chouinard Equipment. These employees loved the company, the product, and believed in its future. Chouinard Equipment was founded in 1957 when Yvon Chouinard began to design, manufacture, and market climbing equipment. As a climbing enthusiast, he naturally hired like-minded employees and their equipment quickly became known for its innovative designs and quality.

The company's focus on innovation and quality climbing gear has never changed, even with a change in ownership. They are known in the industry for being an environmental and customer-minded company. However, the way people interact with the company has changed. Like all other companies, Black Diamond Equipment has moved a significant part of its retail business online. Although it still maintains a physical presence and has a strong dealer/distributor network, it also focuses on providing a positive online user experience.

User reviews and website recommendations have become a key element of the online shopping experience. Black Diamond had a loyal following; however, customers had to enter reviews and recommendations manually onto its website. This system did not allow for a personalized shopping experience or much flexibility. Adam Smart, Senior Web Merchant for Black Diamond, asserted, "We were very eager to get away from manually loading on-site recommendations." This was a time-consuming activity that could not be kept up-to-date in real time.

The IT Solution

A recommendation engine (or a recommender system) is a tool that uses mathematical algorithms to predict what users will or will not like. It uses data from customers, purchase history, likes, dislikes, similarities, differences, and much more to create recommendations and to propose the right method and timing to present an advertisement. Many large companies, such as Facebook, Amazon, Google, and YouTube, utilize recommendations. You would recognize these as the "Other customers purchased this" or the "We thought you would enjoy this video" types of comments. They are currently used in many situations, ranging from buying wine to selecting the next video you will watch!

Black Diamond, a long-time Salesforce.com user, was eager to implement a solution to make these recommendations to customers. There was not one available with its current CRM provider, Salesforce.com, so it decided it was better to implement a third-party recommendations engine that would allow it to begin using a recommender engine.

Then in 2016, Salesforce announced that it would offer an artificial intelligence (AI) add-on to the Commerce Cloud that Black Diamond was using that would provide an integrated recommendation engine. This add-on, called Salesforce Einstein, is intended to enable businesses to leverage AI built right into their CRM to provide deep data analytics that help to drive many organizational decisions, including the decision of what products to recommend to customers based on a historical analysis of the data.

Black Diamond was very excited about this new opportunity to use the AI add-on in Salesforce, but it had just implemented the third-party recommender engine and did not want to make another tech change without evidence that the change was necessary.

Black Diamond decided to implement Salesforce Einstein on a trial basis and run the two recommender engines (the third-party solution and Salesforce Einstein) side-by-side and compare the results.

The Results

The integrated solution of Salesforce Einstein with the existing Commerce Cloud implementation was a clear winner. Not only was the recommendation process automated, but it functioned in real time, it was customized for each customer based on preferences, and it provided invaluable insights into user actions based on the recommendations. While Black Diamond did not report its numbers before the trial started, it did report an increase in both conversion rate (9.6 percent) and in revenue per visitor (15.5 percent). Ultimately, Black Diamond found the Salesforce Einstein solution to be both more effective and more financially viable than the third-party option. As a result, it decided to proceed with a full implementation of the Salesforce Einstein AI product.

J. (2 marks, one mark for each example)

For each of the following two basic components of supply chain management, provide an example of how information systems could be used by Black Diamond to:

i) Plan

ii) Source

K. (2 marks, one mark for each example)

For each of the following two types of report, provide an example that illustrates how the report could provide useful information to Black Diamond about its marketing and sales.

(i) Exception

(ii) Key indicator

Source:Introduction to Information Systems, 5th Canadian Edition

R. Kelly Rainer, Brad Prince, Ingrid Splettstoesser-Hogeterp, Cristobal Sanchez-Rodriguez, Sepideh Ebrahimi