Mar 8, 2023
Thanks to e-commerce, customer experience personalization have become a de-facto norm. Already 89% of digital businesses invest in personalization, particularly in delivering personalized content. These companies include big names like Coca-Cola, Netflix, Sephora, etc. Even in the world of B2B sales and marketing, personalized customer experiences are increasingly becoming an expectation. As businesses continue to compete for market share and customer loyalty, it is essential to provide tailored recommendations that meet the specific needs of each customer. Based on a Salesforce survey, 52% of customers expect offers to always be personalized — up from 49% in 2019. In fact, 91% of consumers are more likely to shop with brands that recognize, remember, and provide relevant offers and recommendations. Their expectations are no different when acting for their company instead of for themselves.
This is where product recommendation engines come in. A recommendation engine is an algorithmic tool that uses data to suggest products or services to customers. But, how do they work? They use various types of data to suggest products to customers. This data can include purchase history, browsing behavior, customer demographics, and other relevant factors. The engine analyzes this data to identify patterns and make recommendations based on customer behavior. For example, if a customer has previously purchased a specific product, the engine may suggest complementary or related products that could be of interest to them, by identifying products that are often found in the same shopping baskets as that product.
There are several benefits to incorporating product recommendation engines into B2B sales and marketing strategies:
In conclusion, product recommendation engines are a valuable tool for B2B sales and marketing teams looking to provide personalized customer experiences. By using data to suggest relevant products, businesses can increase sales from existing customers based on ordering patterns and preferences, and thus, boost revenue. They can also create customer satisfaction by understanding their needs, offering individualized suggestions and relevant content, and creating targeted marketing campaigns.
However, according to ClickZ findings, one of the biggest challenges to personalization is “having adequate IT support for data extraction”. Here is where Fructifi steps in. Our software is able to extract data via a direct connection with your ERP or CRM, or by using a daily CSV exporter. No need to hire a costly data scientist, no need for time-consuming quarterly extractions - in a few clicks, your sales team will instantly know what product each customer should be offered, based on their purchasing behavior - a game-changer for your B2B sales and marketing strategies.
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© 2018-2022 Fructifi alle Rechte vorbehalten - Rechtliche Hinweise - Allgemeine Geschäftsbedingungen - Datenschutzbestimmungen