Sep
01
2020
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Salesforce beefing up field service offering with AI

Salesforce has been adding artificial intelligence to all parts of its platform for several years now. It calls the underlying artificial intelligence layer on the Salesforce platform Einstein. Today the company announced some enhancements to its field service offerings that take advantage of this capability.

Eric Jacobson, VP of product management at Salesforce says that when COVID hit, it pretty much stopped field service in its tracks during April, but like many other parts of business, it began to pick up again later in the quarter, and people still needed to have their appliances maintained.

“Even though we’re sheltering in place, the physical world still has physical needs. Hospitals still have to maintain their equipment. Employees still need to have equipment replaced or repaired while working at home and people still need their washing machine [or other appliances] repaired,” Jacobson said.

Today’s announcements are designed in some ways for a COVID world where efficiency is more critical than ever. That means the field service tech needs to be prepared ahead of time on all of the details of the nature of the repair. He or she has to have the right parts and customers need to know when their technician will be there.

While it’s possible to do much of that in a manual fashion, adding a dose of AI helps streamline and scale that process. For starters, the company announced Dynamic Priority. Certainly humans are capable of prioritizing a list of repairs, but by letting the machine set priority based on factors like service agreement type or how critical the repair is, it can organize calls much faster, leaving dispatchers to handle other tasks.

Even before the day starts, technicians receive their schedule and, using machine learning, can determine what parts they are most likely to need in the truck for the day’s repairs. Based on the nature of the repair and the particular make and model of machine, the Einstein Recommendation Builder can help predict the parts that will be needed to minimize the number of required trips, something that is important at all times, but especially during a pandemic.

“It’s always been an inconvenience and annoyance to have somebody come back for a follow-up appointment. But now it’s not just an annoyance, it’s actually a safety consideration for you and for the technician because it’s increased exposure,” Jacobson explained.

Salesforce also wants to give the customer the same capability they are used to getting in a rideshare app, where you can track the progress of the driver to your destination. Appointment Assistant, a new app, gives customers this ability, so they know when to expect the repair person to arrive.

Finally, Salesforce has teamed with ServiceMax to offer a new capability to get the big picture view of an asset with the goal of ensuring uptime, particularly important in settings like hospitals or manufacturing. “We’ve partnered with a long-time Salesforce partner ServiceMax to create a brand new offering that takes industry best practice and builds it right in. Asset 360 builds on top of Salesforce field service and delivers those specific capabilities around asset performance insight, viewing and managing up time and managing warranty processes to really ensure availability,” he said.

As with all Salesforce announcements, the availability of these capabilities will vary as each is in various forms of development. “Dynamic Priority will be generally available in October 2020. Einstein Recommendation Builder will be in beta in October 2020. Asset 360 will be generally available in November 2020. Appointment Assistant will be in closed pilot in US in October 2020,” according to information provided by the company.

Apr
10
2019
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Salesforce and Google want to build a smarter customer service experience

Anyone who has dealt with bad customer service has felt frustration with the lack of basic understanding of who you are as a customer and what you need. Google and Salesforce feel your pain, and today the two companies expanded their partnership to try and create a smarter customer service experience.

The goal is to combine Salesforce’s customer knowledge with Google’s customer service-related AI products and build on the strengths of the combined solution to produce a better customer service experience, whether that’s with an agent or a chatbot..

Bill Patterson, executive vice president for Salesforce Service Cloud, gets that bad customer service is a source of vexation for many consumers, but his goal is to change that. Patterson points out that Google and Salesforce have been working together since 2017, but mostly on sales- and marketing-related projects. Today’s announcement marks the first time they are working on a customer service solution together.

For starters, the partnership is looking at the human customer service agent experience.”The combination of Google Contact Center AI, which highlights the language and the stream of intelligence that comes through that interaction, combined with the customer data and the business process information that that Salesforce has, really makes that an incredibly enriching experience for agents,” Patterson explained.

The Google software will understand voice and intent, and have access to a set of external information like weather or news events that might be having an impact on the customers, while Salesforce looks at the hard data it stores about the customer such as who they are, their buying history and previous interactions.

The companies believe that by bringing these two types of data together, they can surface relevant information in real time to help the agent give the best answer. It may be the best article or it could be just suggesting that a shipment might be late because of bad weather in the area.

Customer service agent screen showing information surfaced by intelligent layers in Google and Salesforce

The second part of the announcement involves improving the chatbot experience. We’ve all dealt with rigid chatbots, who can’t understand your request. Sure, it can sometimes channel your call to the right person, but if you have any question outside the most basic ones, it tends to get stuck, while you scream “Operator! I said OPERATOR!” (Or at least I do.)

Google and Salesforce are hoping to change that by bringing together Einstein, Salesforce’s artificial intelligence layer and Google Natural Language Understanding (NLU) in its Google Dialogflow product to better understand the request, monitor the sentiment and direct you to a human operator before you get frustrated.

Patterson’s department, which is on a $3.8 billion run rate, is poised to become the largest revenue producer in the Salesforce family by the end of the year. The company itself is on a run rate over $14 billion.

“So many organizations just struggle with primitives of great customer service and experience. We have a lot of passion for making everyday interaction better with agents,” he said. Maybe this partnership will bring some much needed improvement.

Sep
06
2018
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Salesforce updates Sales Cloud ahead of Dreamforce with increased automation

Dreamforce, Salesforce’s massive customer conference is coming later this month to San Francisco, but the news is starting already well ahead of the event. Today, the company announced updates to its core Sales Cloud with an emphasis toward automation and integration.

For starters, the company wants to simplify inside phone sales, giving the team not only a list of calls organized by those most likely to convert, but walking them through a sales process that’s been defined by management according to what they believe to be best practices.

High Velocity Sales is designed to take underlying intelligence from Salesforce Einstein and apply it to the sales process to give sales people the best chance to convert that prospect. That includes defining contact cadence and content. For calls, the content could be as detailed as call scripts with what to say to the prospect. For emails, it could provide key details designed to move the prospect closer to sale and how often to send that next email.

Defining sales cadence workflow in Sales Cloud. Photo: Salesforce

Once the sales teams begins to move that sale towards a close, Salesforce CPQ (configure, price, quote) capabilities come into play. That product has its roots in the company’s SteelBrick acquisition several years ago, and it too gets a shiny new update for Dreamforce this year.

As sales inches toward a win, it typically moves the process to the the proposal stage where pricing and purchases are agreed upon, and if all goes well a contract gets signed. Updates to CPQ are designed to automate this to the extent possible, pulling information from notes and conversations into an automated quote, or relying on the sales person when it gets more complex.

The idea though is to help sales automate the quote and creation of bill once the quote has been accepted to the extent possible, even providing a mechanism for automatic renewal when a subscription is involved.

The last piece involves Pardot Einstein, a sales and marketing tool, designed to help find the best prospects that come through a company’s marketing process. This is also getting some help from the intelligence layer in a couple of ways.

Einstein Campaign Insights looks at the range of marketing campaigns that are coming out of the marketing organization, determining which campaigns are performing — and those that aren’t — and pushing the art of campaign creation using data science to help determine which types of activities are most likely to succeed in helping convert that shopper into a buyer.

The other piece is called Einstein Behavior Score, which again is using the company’s underlying artificial intelligence tooling to analyze buying behavior based on intent. In other words, which people coming through your web site and apps are most likely to actually buy based on their behaviors — pages they visit, items they click and so forth.

Salesforce recognized the power of artificial intelligence to drive a more automated sales process early on, introducing Einstein in 2016. In typical Salesforce fashion, it has built upon that initial announcement and tried to use AI to automate and drive more successful sales.

The core CRM tool that is the center of the Sales Cloud, is simply a system of record of the customers inside any organization, but the company is trying to automate and integrate across its broad family of products whenever possible to make connections between products and services that might be difficult for humans to make on their own.

While it’s easy to get lost in AI marketing hype — and calling their AI layer by the name “Einstein” certainly doesn’t help in that regard — the company is trying to take advantage of the technology to help customers drive more sales faster, which is the goal of any sales team. It will be up to Salesforce’s customers to decide how well it works.

Nov
06
2017
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Salesforce to offer more customized AI with myEinstein

 It’s been just over a year since Salesforce introduced Einstein, a set of artificial intelligence technologies that are designed to underlie and enhance the Salesforce product set. Today, at Dreamforce, the company’s enormous customer conference taking place this week in San Francisco, it announced myEinstein, a package of tools it created to help developers and Salesforce… Read More

Jun
28
2017
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Salesforce introduces several Einstein AI tools for third-party developers

 Salesforce launched three AI tools for developers today at the TrailheaDX developer conference. These algorithms, which fall under the new Einstein Platform Services, enable third-party developers to add Einstein intelligence to applications built on top of the Salesforce platform. The new services include sentiment and intent analysis and some pretty sophisticated image recognition… Read More

Mar
07
2017
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Salesforce Einstein AI can generate models automatically

 When Salesforce announced its spring release this week, it revealed that its artificial intelligence platform, dubbed Einstein, can build data models automatically, even when customers have customized their products to meet the company’s unique requirements. Read More

Feb
13
2017
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Salesforce adds some artificial intelligence to customer service products

Customer service reps Last Fall when Salesforce introduced Einstein, its artificial intelligence initiative, it debuted with some intelligence built into the core CRM tool, but with a promise that it would expand into other products over time. Today it announced it was adding Einstein AI to its Service Cloud customer service platform. The goal is to make life easier for customer service reps and their managers.… Read More

Jan
18
2017
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Salesforce opens engineering office in Microsoft’s and Amazon’s backyards

Lobby in Salesforce's Bellevue, Washington engineering offices. Salesforce announced today that it plans to open an engineering and innovation hub in the Seattle area, greatly expanding its presence there. Company co-founder Parker Harris says the office, which is located in the Nine Two Nine Office Tower in Bellevue, will be dedicated mostly to supporting the company’s artificial intelligence initiative, introduced last Fall, which… Read More

Sep
18
2016
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Salesforce Einstein delivers artificial intelligence across the Salesforce platform

erman-born physicist Albert Einstein (1879 - 1955) standing beside a blackboard with chalk-marked mathematical calculations written across it. Say what you will about Salesforce, the company is always looking ahead. This afternoon, it announced Salesforce Einstein, its artificial intelligence (AI) initiative. The timing, which comes just ahead of rival Oracle’s Open World keynote address, is probably not a coincidence. Regardless, the larger AI theme is something Salesforce has been working on across various pieces of its… Read More

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