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Oracle adds more AI features to its suite of sales tools

As the biggest sales and marketing technology firms mature, they are all turning to AI and machine learning to advance the field. This morning it was Oracle’s turn, announcing several AI-fueled features for its suite of sales tools.

Rob Tarkoff, who had previous stints at EMC, Adobe and Lithium, and is now EVP of Oracle CX Cloud says that the company has found ways to increase efficiency in the sales and marketing process by using artificial intelligence to speed up previously manual workflows, while taking advantage of all the data that is part of modern sales and marketing.

For starters, the company wants to help managers and salespeople understand the market better to identify the best prospects in the pipeline. To that end, Oracle is announcing integration with DataFox, the company it purchased last fall. The acquisition gave Oracle the ability to integrate highly detailed company profiles into their Customer Experience Cloud, including information such as SEC filings, job postings, news stories and other data about the company.

DataFox company profile. Screenshot: Oracle

“One of the things that DataFox helps you you do better is machine learning-driven sales planning, so you can take sales and account data and optimize territory assignments,” he explained.

The company also announced an AI sales planning tool. Tarkoff says that Oracle created this tool in conjunction with its ERP team. The goal is to use machine learning to help finance make more accurate performance predictions based on internal data.

“It’s really a competitor to companies like Anaplan, where we are now in the business of helping sales leaders optimize planning and forecasting, using predictive models to identify better future trends,” Tarkoff said.

Sales forecasting tool. Screenshot: Oracle

The final tool is really about increasing sales productivity by giving salespeople a virtual assistant. In this case, it’s a chatbot that can help handle tasks like scheduling meetings and offering task reminders to busy sales people, while allowing them to use their voices to enter information about calls and tasks. “We’ve invested a lot in chatbot technology, and a lot in algorithms to help our bots with specific dialogues that have sales- and marketing-industry specific schema and a lot of things that help optimize the automation in a rep’s experience working with sales planning tools,” Tarkoff said.

Brent Leary, principal at CRM Essentials, says that this kind of voice-driven assistant could make it easier to use CRM tools. “The Smarter Sales Assistant has the potential to not only improve the usability of the application, but by letting users interact with the system with their voice it should increase system usage,” he said.

All of these enhancements are designed to increase the level of automation and help sales teams run more efficiently with the ultimate goal of using data to more sales and making better use of sales personnel. They are hardly alone in this goal as competitors like Salesforce, Adobe and Microsoft are bringing a similar level of automation to their sales and marketing tools

The sales forecasting tool and the sales assistant are generally available starting today. The DataFox integration will GA in June.

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Apple Business Chat drives in-seat drink ordering at Quicken Loans Arena in Cleveland

With LeBron James hundreds of miles west plying his trade for the Los Angeles Lakers these days, Cleveland Cavalier fans haven’t had a lot to cheer about this season — but Aramark (the stadium food and beverage vendor) and the Cavs have teamed up with Apple Business Chat to let fans order drinks right from their seats.

It’s a nifty system, first introduced to Phillies fans last summer. In this iteration, Cleveland fans can access a menu, order drinks and get them delivered directly to their seats using iMessage on their iPhones.

You start by opening the Camera app and scanning the QR code on your seat back. That brings up a prompt in Messages to “Hit send to start your order.” From there, you can interact with the order bot to order your beverages. To make it easier, you access a menu and make your selections.

When you’re finished, the bot prompts you for your seat number. You pay for your order with Apple Pay, and the beverages will be delivered directly to you without having to miss any of the game action.

It’s not clear how long you have to wait for the drinks to be delivered, but it beats standing in long lines and brings an entirely digital ordering process to fans. Kevin Kearney, district manager for Aramark’s Sports and Entertainment division, sees this as a way to integrate the mobile experience into the fan experience at the game in a highly accessible way.

“The integration of Apple Business Chat with the ordering process is not only fan-friendly and easily accessible, it’s reflective of fans’ changing expectations and behaviors and we’re looking forward to Cavs and Monsters (Cleveland’s AHL affiliate) fans giving it a try,” Kearney said in a statement.

The program is being piloted for the remainder of the season as the teams and Aramark see how the process works and how fans like using it. It may not take away the sting of LeBron leaving town, but it is a convenient way to get drinks while taking in a game.

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Fresh out of Y Combinator, Leena AI scores $2M seed round

Leena AI, a recent Y Combinator graduate focusing on HR chatbots to help employees answer questions like how much vacation time they have left, announced a $2 million seed round today from a variety of investors including Elad Gil and Snapdeal co-founders Kunal Bahl and Rohit Bansal.

Company co-founder and CEO Adit Jain says the seed money is about scaling the company and gaining customers. They hope to have 50 enterprise customers within the next 12-18 months. They currently have 16.

We wrote about the company in June when it was part of the Y Combinator Summer 2018 class. At the time Jain explained that they began in 2015 in India as a company called Chatteron. The original idea was to help others build chatbots, but like many startups, they realized there was a need not being addressed, in this case around HR, and they started Leena AI last year to focus specifically on that.

As they delved deeper into the HR problem, they found most employees had trouble getting answers to basic questions like how much vacation time they had or how to get a new baby on their health insurance. This forced a call to a help desk when the information was available online, but not always easy to find.

Jain pointed out that most HR policies are defined in policy documents, but employees don’t always know where they are. They felt a chatbot would be a good way to solve this problem and save a lot of time searching or calling for answers that should be easily found. What’s more, they learned that the vast majority of questions are fairly common and therefore easier for a system to learn.

Employees can access the Leena chatbot in Slack, Workplace by Facebook, Outlook, Skype for Business, Microsoft Teams and Cisco Spark. They also offer Web and mobile access to their service independent of these other tools.

Photo: Leena AI

What’s more, since most companies use a common set of backend HR systems like those from Oracle, SAP and NetSuite (also owned by Oracle), they have been able to build a set of standard integrators that are available out of the box with their solution.

The customer provides Leena with a handbook or a set of policy documents and they put their machine learning to work on that. Jain says, armed with this information, they can convert these documents into a structured set of questions and answers and feed that to the chatbot. They apply Natural Language Processing (NLP) to understand the question being asked and provide the correct answer.

They see room to move beyond HR and expand into other departments such as IT, finance and vendor procurement that could also take advantage of bots to answer a set of common questions. For now, as a recent YC graduate, they have their first bit of significant funding and they will concentrate on building HR chatbots and see where that takes them.

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Facebook taps banks, but for chatbots not purchase data like Google

Backlash swelled this morning after Facebook’s aspirations in financial services were blown out of proportion by a Wall Street Journal report that neglected how the social network already works with banks. Facebook spokesperson Elisabeth Diana tells TechCrunch it’s not asking for credit card transaction data from banks and it’s not interested in building a dedicated banking feature where you could interact with your accounts. It also says its work with banks isn’t to gather data to power ad targeting, or even personalize content such as which Marketplace products you see based on what you buy elsewhere.

Instead, Facebook already lets Citibank customers in Singapore connect their accounts so they can ping their bank’s Messenger chatbot to check their balance, report fraud or get customer service’s help if they’re locked out of their account without having to wait on hold on the phone. That chatbot integration, which has no humans on the other end to limit privacy risks, was announced last year and launched this March. Facebook works with PayPal in more than 40 countries to let users get receipts via Messenger for their purchases.

Expansions of these partnerships to more financial services providers could boost usage of Messenger by increasing its convenience — and make it more of a centralized utility akin to China’s WeChat. But Facebook’s relationships with banks in the current form aren’t likely to produce a steep change in ad targeting power that warrants significant heightening of its earning expectations. The reality of today’s news is out of step with the 3.5 percent share price climb triggered by the WSJ’s report.

“A recent Wall Street Journal story implies incorrectly that we are actively asking financial services companies for financial transaction data – this is not true. Like many online companies with commerce businesses, we partner with banks and credit card companies to offer services like customer chat or account management. Account linking enables people to receive real-time updates in Facebook Messenger where people can keep track of their transaction data like account balances, receipts, and shipping updates,” Diana told TechCrunch. “The idea is that messaging with a bank can be better than waiting on hold over the phone – and it’s completely opt-in. We’re not using this information beyond enabling these types of experiences – not for advertising or anything else. A critical part of these partnerships is keeping people’s information safe and secure.”

Diana says banks and credit card companies have also approached it about potential partnerships, not just the other way around as the WSJ reports. She says any features that come from those talks would be opt-in, rather than happening behind users’ backs. The spokesperson stressed these integrations would only be built if they could be privacy safe. For example, signing up to use the Citibank Messenger chatbot requires two-factor authentication through your phone.

But renewed interest in Facebook’s dealings with banks comes at a time when many are pointing to its poor track record with privacy following the Cambridge Analytica scandal, where people were duped into volunteering the personal info of them and their friends. Facebook hasn’t had a big traditional data breach where data was outright stolen, as has befallen LinkedIn, eBay, Yahoo [part of TechCrunch’s parent company] and others. But users are rightfully reluctant to see Facebook ingest any more of their sensitive data for fear it could leak or be misused.

Facebook has recently cracked down on the use of data brokers that suck in public and purchased data sets for ad targeting. It no longer lets data brokers upload Managed Custom Audience lists of user contact info or power Partner Categories for targeting ads based on interests. It also more adamantly demands that advertisers have the consent of users whose email addresses or phone numbers they upload for Custom Audience targeting, though Facebook does little to verify that consent and advertisers could still buy data sets from brokers and upload them themselves

Facebook’s statement today shows more scruples than Google, which last year struck ad measurement data deals with data brokers that have access to 70 percent of credit and debit card transactions in the U.S. That led to a formal complaint to the FTC from the Electronic Privacy Information Center. [Correction: Google tells us the deals are for ad measurement data, not ad targeting as we originally published. It only learns the aggregate purchase value, not what the items were bought, and the data is encrypted.]

Cambridge Analytica has brought on an overdue era of scrutiny regarding privacy and how internet giants use our data. Practices that were overlooked, accepted as industry standard or seen as just the way business gets done are coming under fire. Internet users aren’t likely to escape ads, and some would rather have those they see be relevant thanks to deep targeting data. But the combination of our offline purchase behavior with our online identities seems to trigger uproar absent from sites using cookies to track our web browsing and buying.

Facebook’s probably better off backing away from anything that involves sensitive data like checking account balances until Cambridge Analytica blows over and it’s proven its newfound sense of responsibility translates into a safer social networking. But at least for now, it’s not slurping up our banking data wholesale.

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Leena AI builds HR chatbots to answer policy questions automatically

Say you have a job with a large company and you want to know how much vacation time you have left, or how to add your new baby to your healthcare. This usually involves emailing or calling HR and waiting for an answer, or it could even involve crossing multiple systems to get what you need.

Leena AI, a member of the Y Combinator Summer 2018 class, wants to change that by building HR bots to answer questions for employees instantly.

The bots can be integrated into Slack or Workplace by Facebook and they are built and trained using information in policy documents and by pulling data from various back-end systems like Oracle and SAP.

Adit Jain, co-founder at Leena AI, says the company has its roots in another startup called Chatteron, which the founders started after they got out of college in India in 2015. That product helped people build their own chatbots. Jain says along the way, they discovered while doing their market research a particularly strong need in HR. They started Leena AI last year to address that specific requirement.

Jain says when building bots, the team learned through its experience with Chatteron that it’s better to concentrate on a single subject because the underlying machine learning model gets better the more it’s used. “Once you create a bot, for it to really add value and be [extremely] accurate, and for it to really go deep, it takes a lot of time and effort and that can only happen through verticalization,” Jain explained.

Photo: Leena AI

What’s more, as the founders have become more knowledgeable about the needs of HR, they have learned that 80 percent of the questions cover similar topics, like vacation, sick time and expense reporting. They have also seen companies using similar back-end systems, so they can now build standard integrators for common applications like SAP, Oracle and NetSuite.

Of course, even though people may ask similar questions, the company may have unique terminology or people may ask the question in an unusual way. Jain says that’s where the natural language processing (NLP) comes in. The system can learn these variations over time as they build a larger database of possible queries.

The company just launched in 2017 and already has a dozen paying customers. They hope to double that number in just 60 days. Jain believes being part of Y Combinator should help in that regard. The partners are helping the team refine its pitch and making introductions to companies that could make use of this tool.

Their ultimate goal is nothing less than to be ubiquitous, to help bridge multiple legacy systems to provide answers seamlessly for employees to all their questions. If they can achieve that, they should be a successful company.

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ServiceNow chatbot builder helps automate common service requests

When it comes to making requests inside a company for new equipment or to learn about HR policies, it can be a frustrating experience for both sides of the equation. HR and IT are probably tired of answering the same questions. Employees are tired of calling a help desk for routine inquiries and waiting for answers. ServiceNow’s new bot-building technology is designed to alleviate that problem by providing a way to create an automated bot-driven process for routine requests.

The company claims that you can build these bots to provide end-to-end service. Meaning if you tell the bot you need a new phone, it can pull your records, understand what you currently have and order a new one all in the same interaction — and all within a common messaging interface such as Slack or Microsoft Teams.

It also works for customer service transactions to process routine customer inquiries without having to route them to a CSR to answer typical questions.

The new chatbot building tool called Virtual Agent, has been built into the ServiceNow Now platform and provides a way for developers to build conversational interfaces easily, says CJ Desai, chief product officer at ServiceNow. “[The Virtual Agent] enables our customers to develop a wide range of intelligent service conversations from a quick question to an entire business action through the messaging platform of their choice,” Desai said in a statement.

The announcement is part of a broader AI initiative on the part of ServiceNow, which purchased Parlo, a chatbot startup, just last week for an undisclosed amount of cash. The acquisition should help give ServiceNow more AI engineering talent and help them beef up their natural language processing (NLP) to further refine and improve their chatbot products moving forward, as the Parlo team and technology get incorporated into the ServiceNow platform.

The company claims that using these chatbots, customers can reduce call volume to help desks and customer service by 15-20 percent, using the standard argument that it should free humans to handle more difficult inquiries.

The company joins a slew of other platform players including Salesforce, IBM, Oracle, AWS, and others who are incorporating chatbot building technology into their platforms.

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Google Cloud releases Dialogflow Enterprise Edition for building chat apps

Building conversational interfaces is a hot new area for developers. Chatbots can be a way to reduce friction in websites and apps and to give customers quick answers to commonly asked questions in a conversational framework. Today, Google announced it was making Dialogflow Enterprise Edition generally available. It had previously been in beta.

This technology came to them via the API.AI acquisition in 2016. Google wisely decided to change the name of the tool along the way, giving it a moniker that more closely matched what it actually does. The company reports that hundreds of thousands of developers are using the tool already to build conversational interfaces.

This isn’t just an all-Google tool, though. It works across voice interface platforms, including Google Assistant, Amazon Alexa and Facebook Messenger, giving developers a tool to develop their chat apps once and use them across several devices without having to change the underlying code in a significant way.

What’s more, with today’s release the company is providing increased functionality and making it easier to transition to the enterprise edition at the same time.

“Starting today, you can combine batch operations that would have required multiple API calls into a single API call, reducing lines of code and shortening development time. Dialogflow API V2 is also now the default for all new agents, integrating with Google Cloud Speech-to-Text, enabling agent management via API, supporting gRPC, and providing an easy transition to Enterprise Edition with no code migration,” Dan Aharon, Google’s product manager for Cloud AI, wrote in a company blog post announcing the tool.

The company showed off a few new customers using Dialogflow to build chat interfaces for their customers, including KLM Royal Dutch Airlines, Domino’s and Ticketmaster.

The new tool, which is available today, supports more than 30 languages and as a generally available enterprise product comes with a support package and service level agreement (SLA).

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Guestfriend automates chatbot creation for restaurants

While chatbots might sound like an interesting experiment for restaurants and other small businesses, they probably can’t devote much time or money to building them. So a startup called Guestfriend is planning to make the process as fast and easy as possible.

The company has raised $5 million in seed funding from Primary Venture Partners, Techstars Ventures and betaworks. It’s led by Bo Peabody, a venture partner and entrepreneur in residence at Greycroft who also co-owns the Mezze Restaurant Group. Peabody compared the current moment to the year 2000, when “every small business woke up and said, ‘I need a website.’”

“That moment is coming for chatbots,” he predicted.

But rather than asking a restaurant owner or employee to go online and design the conversational flow of a chatbot themselves, Guestfriend can automatically create a chatbot based on information that’s already online — hours, menu, support for dietary restrictions and so on. In that sense, Peabody said, “It’s really just a website that you talk to.”

“The ah-ha moment was when I realized that building a bot for my restaurant was virtually impossible to do as a one-off, but all of the answers to almost any question are available online, mostly in structured APIs,” he said.

GuestFriend

Peabody suggested that the real challenge was building natural language technology that could support the range of questions that someone might ask — for example, all the different ways that people might ask about the dress code. That’s one reason why it was important to target a specific industry, though he eventually plans to expand into home services, retail, spas/salons/exercise and hotels. (“It’s really the Yelp verticals.”)

Guestfriend chatbots work across platforms, including SMS, Facebook, Twitter and Google search results (via Google My Business), with plans to support speech platforms like Amazon Alexa and Google Home.

The company is actually building these chatbots without waiting for restaurants to sign up. (You can try them out on the Guestfriend website.) The idea is that publishers with restaurant listings can also incorporate them as a new way to interact with their sites.

At the same time, restaurants can come in and claim their chatbots, which will be updated accordingly everywhere that they’re available. The restaurant can then be as hands-on or as hands-off as they want.

I brought up the fact that I often visit restaurants’ Facebook Pages in the hopes of answering more timely questions, like whether or not a restaurant is staying open despite bad weather or a holiday. Peabody suggested that as with social media or a website, the up-to-dateness of the information will depend on the restaurant — some of them might want to update every day with things like daily specials. For others, a completely automated approach might be the most appealing.

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Microsoft makes Azure Bot Service generally available for developers

 Microsoft introduced the Azure Bot Framework more than two years ago and companies have been building chatbots for a variety of scenarios ever since. Today, the company made generally available the Microsoft Azure Bot Service and Microsoft Cognitive Language Understanding service (known as LUIS). Read More

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Google launches a paid enterprise edition of its Dialogflow chatbot builder

 Google today announced the beta launch of its enterprise edition of Dialogflow, its tool for building chatbots and other conversational applications. In addition, Dialogflow (both in its free and enterprise version) is now getting built-in support for speech recognition, something that developers previously had to source through the Google Cloud Speech API or similar services. Unsurprisingly,… Read More

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