Salesforce and AWS: Cloud Vendors Talk Changes, New Releases
All of the takeaways partners need from Salesforce Connections and AWS’ Machine Learning Summit.
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Salesforce unveiled a new version of Marketing Cloud 360. This edition delivers real-time engagement, audience segmentation and loyalty management. Salesforce said users gain more visibility and can personalize messaging because of the embedded artificial intelligence capabilities. Plus, Marketing Cloud 360 provides unified analytics.
The next slide has more insight into new capabilities.
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Marketing Cloud 360 now incorporates reports from Datorama. This gives marketers access to new types of reports – email, mobile, customer journey – to analyze and act accordingly. This is available now.
There’s also Snapchat Audience Match. Users take data stored in Salesforce to create campaigns for Snapchat audiences. This will become available later this month.
Finally, Marketing Cloud 360 features WhatsApp integration. Businesses set up an account, channels and message templates and communicate with customers directly on WhatsApp. Capabilities include keyword detection and transactional messaging. This is available now.
The latest iteration of Commerce Cloud 360, part of Salesforce CDP, will go live in October. This version will help companies to identify business trends and personalize customer experiences across channels.
“We’re really focused on creating an integrated commerce experience with our Salesforce CDP out of the box,” Lidiane Jones, executive vice president and general manager of Commerce Cloud at Salesforce, told reporters in a press conference previewing the new Salesforce releases.
The next slide offers more details.
Commerce Cloud soon will contain the following:
· B2B2C Commerce app: Lets companies launch a direct-to-consumer ecommerce storefront with clicks, not code.
· Salesforce Order Management: Provides views into real-time inventory across stores and fulfillment centers. Buyers get to use self-service fulfillment tracking, and oversee cancellations, order modifications and more.
· Headless PWA Kit and Managed Runtime: Developers can decouple front-end and back-end technologies to achieve so-called headless commerce. Developers spend less time on infrastructure maintenance and more time creating customer experiences.
“The digital market is a huge opportunity, one our partners are prepared to tackle,” Tyler Prince, executive vice president of worldwide alliances and channels for Salesforce, told Channel Futures. “We’re excited to see Salesforce partners extend the power of these new marketing and commerce technologies to customers across industries.”
Meanwhile, AWS on Wednesday held its Machine Learning Summit.
Much of the event constituted a review of available capabilities and featured customer case studies. Swami Sivasubramanian, vice president of AI and machine learning at AWS, hosted the one-day conference. He called machine learning “one of the most transformative technologies people will encounter in our generation.”
“We’re just scratching the service with what is possible,” he added, giving vaccine and crop production as two examples.
Even though most of the keynote served as a review of AWS’ machine learning portfolio, there were a couple of new announcements.
AWS debuted the following machine learning platforms:
· Monitron: A new system that uses ML to detect abnormal behavior in industry machinery. Take, for example, conveyor belts in Amazon fulfillment centers. Monitron, which AWS tested in Germany, looks for abnormal vibrations on conveyors, as one example. It then alerts technicians to needed repairs, reducing downtime. Monitron lets business users “easily add intelligence to applications without requiring machine-learning skills,” Sivasubramanian said.
· Practical Data Science MOOC: Data professionals now may take the three-course, 10-week specialization to learn ML in the AWS cloud. The first installment provides foundational concepts for exploratory data analysis, automated machine learning and text classification algorithms. The second one teaches students to automate tasks by building a machine-learning pipeline. And the third teaches performance-improvement and cost-reduction techniques. This allows users to tune model accuracy, compare prediction performance and generate new training data.
AWS debuted the following machine learning platforms:
· Monitron: A new system that uses ML to detect abnormal behavior in industry machinery. Take, for example, conveyor belts in Amazon fulfillment centers. Monitron, which AWS tested in Germany, looks for abnormal vibrations on conveyors, as one example. It then alerts technicians to needed repairs, reducing downtime. Monitron lets business users “easily add intelligence to applications without requiring machine-learning skills,” Sivasubramanian said.
· Practical Data Science MOOC: Data professionals now may take the three-course, 10-week specialization to learn ML in the AWS cloud. The first installment provides foundational concepts for exploratory data analysis, automated machine learning and text classification algorithms. The second one teaches students to automate tasks by building a machine-learning pipeline. And the third teaches performance-improvement and cost-reduction techniques. This allows users to tune model accuracy, compare prediction performance and generate new training data.
Two prominent cloud vendors, Salesforce and Amazon Web Services (AWS), held separate virtual events on Wednesday. Salesforce hosted its annual Connections conference while AWS dove into artificial intelligence with its Machine Learning Summit.
Salesforce announced some changes across its Digital 360 portfolio. Overall, Salesforce is continuing its push to help users move to digital-first models, and connect with customers through email and online transactions.
Salesforce’s David Schmaier
“Being digital-first and customer centric has never been more important,” said David Schmaier, president and chief product officer of Salesforce. “With Digital 360, companies have the full power of Salesforce to go digital faster, build a single view of their customers, and drive growth.”
Next, as noted, AWS spent the day talking about machine learning. It’s a hot subject. IDC expects spending on AI (which includes machine learning) to double by 2024, reaching $110 billion. In the slideshow above, we cover today’s most relevant Salesforce and AWS takeaways for partners.
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