• Recommender systems software is primarily used to improve the relationships with customers, provide a delightful experience, and boost incremental revenues.
• Companies in the space of e-commerce and media are the early adopters of recommender systems. Some good examples are Amazon, Netflix, Spotify, Best Buy, and Youtube. Other industries that have wide adoption of recommender systems are retail, banking, telecom, and utilities.
• All of the industries that have adopted recommender systems engage with clients through some form of digital channels. They use the software and techniques to filter client information and recommend personalized products and services to both consumers and business customers. For example, banks have used the system to promote products to small and medium-sized enterprises.
• From an online commerce's point of view, the B2B segment represented 63.1% of the global e-commerce market revenue in 2019, despite the volume of transactions may well be dominated by the B2C segment. With the prevalence of online commerce across the above-mentioned industries, the B2B segment is expected to present a similar situation.
• Hence, some examples of companies that have implemented recommender systems to better serve their business customers are SAP, NVIDIA, Intuit, and Langevin.
• Although the recommender systems could be a stand-alone software module, it is likely to be integrated with the digital content experience software or a content marketing platform. For example, Dynamic Yield, Qualtrics, and Outgrow, among others. Some significant buyers of the software are Allianze, Microsoft, HP, Xerox, Monsanto, and PwC, which are likely to target business customers (B2B). Other software buyers are IKEA, Sephora, Lacoste, Urban Outfitters, GE, and UPS, which are likely to be consumer-oriented businesses (B2C).

Summary of Early Findings

• The one-hour preliminary research reveals the wide adoption of recommender systems by software buyers to enhance the digital experience of consumers, whereas there appears to be limited information on buyers' business clients. However, the B2B clients are expected to be software buyers' target audiences as well.
• With the trend of online commerce or omni-channels, companies in a variety of service-oriented industries are expected to use recommender systems to improve relationships with their business clients. However, there is a lack of information on the demographics of representative decision-makers per industry sector.
• Limited time was spent on identifying B2B-oriented software buyers, regarding digital experience optimization software, the information on demographics and the B2B use cases is expected to be similar to those of recommender systems.
• Recommender systems softare is expected to be used for buyers' marketing, sales, and business development activities. The decision-makers of software buyers are likely to hold job titles in these business units and hold the title of IT directors/managers. For small companies, such as startups, the CEO is expected to be the key decision-maker. Hence, further research path is recommended to focus on identifying the decision-makers of the companies mentioned above and develop their profiles; software buyers are separated by B2B and B2C businesses.