Salesforce CRM, internet of things sensor data and AI applications have traditionally existed in separate silos....
The early use cases for IoT primarily focused on improving home and industrial automation, while Salesforce has been driven by its strong focus on sales automation.
Now, though, leading players in IoT are pondering how to bridge this gap to improve service, support and customer experience. These explorations are still in their early days, and it may take several years for firms to identify and fine-tune practical use cases.
Some of the key components of this strategy are being driven by recent improvements to Salesforce's Einstein platform for AI applications, as well as its IoT Cloud platform for the internet of things, which got a reboot at the Dreamforce annual user conference after its 2015 initial release.
Two companies in the energy sector demonstrated IoT projects at Dreamforce, which isn't a coincidence: All the large CRM vendors are finding that power companies are looking to automate field service and are willing to try IoT equipment to get there.
Improving the consumer experience
IoT adoption is likely to be driven by the simplicity of augmenting existing Salesforce implementations onto consolidated platforms owing to security, privacy, integration and data management challenges, said Seb Chakraborty, global CTO at Hive, a business unit of multinational energy services provider Centrica.
Hive focuses on delivering energy monitoring and home automation devices to consumers and businesses in several countries, including the U.K., U.S. and Ireland. These devices are delivered through utility channel partners, such as British Gas in the U.K. and Direct Energy in the U.S.
"We use Salesforce as a way to grow the partner channel," said Chakraborty.
Hive has already developed a rich set of AI applications for helping consumers get the most out of the data from their IoT devices. The next step lies in integrating this with Salesforce data to complement Hive's channel partnerships while improving the overall customer experience.
Hive started with Salesforce CRM, and then added Service Cloud to improve its understanding and management of product usage. They are now looking at using IoT Cloud to check battery levels, automate the setup of new customers and confirm product warranties.
"We want to know why customers are not using features," said Chakraborty.
As part of this process, Hive is experimenting with Salesforce Einstein to improve data analysis.
"We receive billions of events, and being able to mine this data and spot anomalies is important," Chakraborty said. "Einstein makes it easier to bring data in for analysis in a more declarative way than traditional machine learning tools."
Chakraborty is particularly concerned with staying in compliance with the new General Data Protection Regulation (GDPR) set to take hold next year. GDPR threatens to dramatically increase penalties for data and privacy breaches in the European Union. One of the attractions of both Einstein AI applications and IoT Cloud services is that they enable Hive to more easily manage sensitive customer data on one platform.
Better B2B sales and service
New Salesforce IoT Cloud enhancements also show promise in the industrial automation space, said Cyril Perducat, executive VP for IoT at Schneider Electric.
The $25-billion company, which focuses on industrial power infrastructure, has used Salesforce for eight years. Over the last couple of years, it has moved its customer support and service management onto Salesforce. It has recently begun experimenting with AI applications and IoT to improve the efficiency of its service and support offerings.
Schneider has already done considerable work developing its IoT platform to enhance its ability to gather information about the industrial equipment it installs. The Salesforce IoT platform enables them to better leverage this information with its various Salesforce tools for customers in its building, industrial, data center and grid business units.
One important use case for IoT data lies in using AI applications to proactively repair equipment before it causes a failure.
"By mixing asset information and customer information, and by knowing equipment usage, we can show a different customer experience and create new sources of revenue," Perducat said.
Schneider has started experimenting with Einstein for the sales side of its business, as well, to improve lead generation and scoring. It leverages information about potential leads, which is normalized and cleaned with Einstein to prioritize sales resources.
"Einstein can analyze data from 1,000 opportunities to recommend the 10 most likely to close," Perducat said.
Going forward, Perducat said Schneider plans to experiment with other Einstein use cases, including improved customer support and product recommendations.