Salesforce Einstein, Thunder and Lightning – just hooks to grab your attention?
Salesforce’s World Tour rolled into London last week. The company focused heavily on how its Intelligent Customer Success Platform enables developers to pull together IoT (Thunder IoT Cloud) and AI (Einstein) capabilities to power sales and marketing apps (built on the Lightning Platform).
When Salesforce talks ‘IoT’, it’s really talking about real-time event processing. It’s not so much interested in the interconnectivity of devices, as which business applications (specifically sales and marketing applications, supporting its Analytics, Sales and Marketing Clouds) can be enriched by the addition of in-the-moment data streams available at various stages of the customer journey. Taking the much vaunted IoT concept of predictive maintenance, Salesforce is promoting its IoT / AI integrations as bringing “predictive service” to the end customer. Not just anticipating maintenance interventions in cars, factories, etc. (well-worn use case examples for IoT players) – but fine-tuning and tailoring marketing based on the availability of highly granular and timely customer data. The Salesforce Thunder IoT Platform is pitched as a low-code environment too, with the aim of making it easier for its customers to integrate IoT capabilities without relying on expensive, scarce, specialist resources.
On the subject of improving access to insight, Salesforce’s Einstein AI platform is designed to ‘infuse the power of AI’ into sales and marketing applications in a seamless way (improving the quality and speed of insight without having to rely on teams of data scientists); similar to how Adobe Sensei is tailored to customer intelligence use cases, rather than being a more generic AI / ML framework (as we covered in last week’s report on the Adobe Summit).
As an established platform player, Salesforce has the developer ecosystem to exploit these new capabilities, but I’m more convinced by the AI angle of Einstein rather than the IoT angle at present. How much Salesforce apps will benefit from the ingestion of real-time customer data that’s already held within the Salesforce environment (as opposed to third-party real-time sources – the latter, Salesforce relies upon its partnership with IBM and integration with the Watson IoT platform to provide) remains to be seen. However, the Einstein angle – although too heavily bounded within sales and marketing use cases to really be described as true ‘AI’ – does bring some welcome data-driven assistance and augmentation to sales and marketing business processes (Einstein Lead Scoring, for instance).
In short, the IoT and AI labels are there to get your attention. It doesn’t really mean Salesforce is entering the IoT and AI spaces per se. For example, although Hive featured on-stage as an IoT focused customer with its Connected Home products, it has chosen to integrate its own custom IoT platform, Honeycomb, with the Salesforce Marketing Cloud; Hive isn’t built on Thunder). And Einstein is really bringing data-driven insight to augment people-focused sales and marketing processes.
However, this is where both new technologies will establish footholds in mainstream IT organisations. Yes, there will be innovative and highly disruptive new applications every so often that might grab the headlines and win a few battles, but the war of advancing automation / augmentation and interconnectivity will be won by vendors that are able to bring enhancements into mainstream business processes seamlessly and transform from within… almost without the end customer even noticing. If Salesforce is careful, it has the potential to win big here.
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