How Einstein Will Impact B2B Organizations

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How Einstein Will Impact B2B Organizations

By Special Guest
Shawn Belling, VP of product development and support at CloudCraze
  |  March 07, 2017

Salesforce in September announced the release of Einstein artificial intelligence, promising partner businesses the ability to build advanced AI-powered apps that learn more from every customer interaction. The platform has the potential to make machine learning more accessible to all businesses, providing powerful insights that further personalize interactions within both B2C and B2B spaces.

Additionally, AI capabilities can automate previously time-consuming tasks, narrow in on promising sales opportunities, and parse out the most important insights. When used strategically, these functions can dramatically improve customer experiences.

B2B organizations face unique challenges that AI can help solve. Einstein will help make jobs easier and more profitable by servicing low-volume customers with greater efficiency, creating more seamless shopping experiences, providing geolocation services, and more. Salesforce Einstein’s omnichannel functionality, paired with its mobile-first strategy, will play a large role in enhancing the B2B customer experience.

Harness the Power of Customer Data

With every click of a button, customers are providing businesses with data about their product preferences, shopping habits, business needs, and more. However, with so much data to sift through, it isn’t easy for businesses to make those insights actionable on their own. Many businesses have turned to expensive third-party services, but these solutions aren’t feasible for organizations with smaller budgets.

With Einstein, businesses can gather actionable consumer data from complex algorithms in a way that makes sense for decision makers, not just mathematicians. Thanks to Einstein’s automated nature and Salesforce integration, affordability does not sacrifice quality.

These advanced algorithms eliminate the need to make recommendations or assumptions based on the broad demographic characteristics of customers, enabling businesses to segment consumers on an individual basis. Al-powered algorithms can motivate another piece of intelligence to make decisions, using data on previous purchases, customer location, and responses to promotions. With this data, businesses can automatically offer potential promotions at the right price and time both to maximize the likelihood of purchase, and to increase the likelihood of consumers habitually making multiple purchases over time.

AI also enables businesses to constantly adapt to new consumer behaviors. Machine learning identifies and accounts for even the slightest changes in consumer preferences to develop stronger insights as it processes new data.

A Mobile-First Strategy for the Masses

Salesforce has worked hard to create a mobile-first experience for users. And mobile gives organizations access to incredible amounts of data collected from passive sensors that store information just from users carrying the devices in their pockets. Location services and app preferences constantly run in the background of a phone to provide data on where a user has been and what she might like. Beyond that, mobile allows sales reps to create orders more efficiently on site. It also allows the rep to gather customer data in real time and offer the most relevant content and products.

AI will make this mobile-first experience even more powerful, especially for reps and customers on the go. Access to real-time customer data and analytics will enable more personalized offerings, efficient transactions, and overall business process improvements.

Now, as Salesforce partners gain access to integrate Einstein into native apps, this functionality will spread to an even wider audience throughout the Salesforce ecosystem. B2B buyers and sellers will interact in new ways as mobile communication becomes uniquely tailored and transaction processes become increasingly seamless, resulting in greater customer loyalty and major revenue gains.

What Einstein means for B2B sellers

In a B2B context, buyers are more likely to make consistent purchases over time. For example, a small grocery store owner may make habitual orders of the same products to keep shelves stocked. While this isn’t always a simple pattern, sellers can use machine-learning algorithms to analyze these behaviors and make it easier for buyers to make repeat purchases.

Over time, businesses can use sophisticated processes to automate orders before customers even request them. Algorithms can accomplish this with data points like time of purchase, order volume, location and other factors. For example, the same grocery store owner could go into her mobile app and access her cart, and find that it is already filled with the right number of items she routinely orders, accompanied with additional recommendations based on her previous purchases and future product trends. This makes her life easier in the moment, ensures her long-term loyalty, and saves time for the sales rep.

In the midst of automation, B2B sellers must also be careful to avoid a cardinal sin: overwhelming buyers with too many options. Sellers can rely on Einstein’s algorithms to narrow in on specific products and promotions without overloading buyers.

Salesforce’s unveiling of Einstein marks a significant shift toward accessible, simplified machine learning that will revolutionize the way businesses interact with and market to shoppers. Only time will tell how Einstein impacts day-to-day commerce relationships, but the future certainly looks bright.

Shawn Belling is vice president of product development and support at CloudCraze.




Edited by Alicia Young
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