Customer Service

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Kustomer acquires Reply.ai to enhance chatbots on its CRM platform

Last December, when CRM startup Kustomer was announcing its latest round of funding — a $60 million round led by Coatue — its co-founder and CEO Brad Birnbaum said it would use some of the money to build more RPA-style automations into its platform to expand KustomerIQ, its AI-based product that helps understand and respond to customer enquiries to take some of the more repetitive load off of agents. Today, Kustomer is announcing some M&A that will help in that strategy: it is acquiring Reply.ai, a startup originally founded in Madrid that has built a code-free platform for companies to create customised chatbots to handle customer service enquires that use machine learning to, over time, become better at responding to those inbound contacts.

Kustomer, which has raised more than $170 million and is now valued at $710 million (per PitchBook), said it is not disclosing the financial terms of the deal.

Reply .ai — whose customers include Coca-Cola, Starbucks, Samsung, and a number of retailers and major ad and marketing agencies working on behalf of clients — had by comparison raised a modest $4 million in funding (with the last round back in 2018). Its list of investors included strategic backers like Aflac and Westfield (the shopping mall giant), as well as Seedcamp, Madrid’s JME Ventures, and Y Combinator, where Reply.ai was a part of its Startup School cohort in 2017.

Birnbaum said that the conversation for acquiring Reply.ai started before the global health pandemic — the two already worked together, as part of Reply.ai’s integrations with a number of CRM platforms. But active discussions, due diligence, and the closing of the deal were all done over Zoom. “We were fortunate that we got to meet before corona, but for the most part we did this remotely,” he said.

Reply.ai was founded back in 2016 — the year when chatbots suddenly became all the rage — and it managed to make it through that and then the subsequent trough of disillusionment, when a lot of the early novelty wore off after they were discovered to be not quite as effective as many had hoped or assumed they would be. One of the reasons for Reply.ai’s survival was that it had proven to be a builder of effective applications in one of the only segments of the market to become a willing customer and user of chatbots: customer service.

While a large part of the CRM industry — estimated to be worth some $40 billion in 2019 —  is still based around human interactions, there has been a growing push to leverage advances in AI, cloud services, and use of the internet as a point of interaction to bring more automation into the process, both to help those who are agents deal with more tricky issues, and to help bring overall costs down for those who rely on customer support as part of their service proposition.

That trend, if anything, is only getting a boost right now. In some cases, agents are unable to work because of social distancing rules in cases where customer queries cannot be handled by remote workers. In others, companies are seeing a lot of financial pressure and are looking to reduce expenses. But at the same time, with more people at home and unable to make physical queries at stores, the whole medium of customer support is seeing new levels of usage.

Kustomer has been taking on the bigger names in CRM, including Salesforce (where Birnbaum and his cofounder Jeremy Suriel previously worked), Zendesk and Oracle, by providing a platform that makes it easier for human agents to handle inbound “omnichannel” customer requests — another big trend, leveraging the rise of multiple messaging and communications platforms as potential routes to both speaking to customers and seeing them complain for all the world to see. So moving deeper into chatbots and other AI-powered tools is a natural progression.

Birnbaum said that one of its key interests with Reply.ai was its focus on “deflection” — the term for using non-human tools and services to help resolve inbound requests before needing to call in a human agent. Reply.ai’s tools have been shown to help deflect 40% of initial inbound queries, he noted.

“Some companies have been dealing with a significant increase in inbound volume, and it’s been hard to scale their teams of agents, especially when they are remote,” he said. “So those companies are looking for ways to respond more rapidly. So anything they can do to help with that deflection and let their agents be more productive to drive higher levels of satisfaction, anything that can enable self-service, is what this is about.”

Other tools in the Reply toolkit, in addition to its chatbot-building platform and deflection capabilities, include agent-assistant tools for suggesting relevant answers, as well as suggestions for tagging (for analytics) and re-routing.

“We are excited for Reply to join Kustomer and share its mission to make customer service more efficient, effective and personalized,” said Omar Pera, one of Reply.ai’s founders, in a statement. “As a long-time partner of Kustomer, we are able to seamlessly integrate our deflection and chatbots technologies into Kustomer’s platform and help brands more cost-effectively increase efficiency. We look forward to working with Brad and the entire team.”

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Revenue train kept rolling all year long for Salesforce

Salesforce turned 20 this year, and the most successful pure enterprise SaaS company ever showed no signs of slowing down. Consider that the company finished the year on an $18 billion run rate, rushing toward its 2022 revenue goal of $20 billion. Oh, and it also spent a tidy $15.7 billion to buy Tableau this year in the most high-profile and expensive acquisition it’s ever made.

Co-founder, chairman and CEO Marc Benioff published a book called Trailblazer about running a socially responsible company, and made the rounds promoting it. In fact, he even stopped by TechCrunch Disrupt in San Francisco in September, telling the audience that capitalism as we know it is dead. Still, the company announced it was building two more towers in Sydney and Dublin.

It also promoted Bret Taylor just last week, who could be in line as heir apparent to Benioff and co-CEO Keith Block whenever they decide to retire. The company closed the year with a bang with a $4.5 billion quarter. Salesforce, for the most part, has somehow been able to balance Benioff’s vision of responsible capitalism while building a company makes money in bunches, one that continues to grow and flourish, and that’s showing no signs of slowing down anytime soon.

All aboard the gravy train

The company just keeps churning out good quarters. Here’s what this year looked like:

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Oto snags $5.3M seed to use AI to understand voice intonation

Oto, a startup spun off from research at SRI International to help customer service operations understand voice intonation, announced a $5.3 million seed round today.

Participants in the round included Firstminute Capital, Fusion Fund, Interlace Ventures, SAP.iO and SRI International . The total includes a previous $1 million seed round, according to the company.

Teo Borschberg, co-founder and CEO at Oto, says the company launched out of SRI International, the same company where Apple’s Siri technology was originally developed. It has been developing intonation data, based originally on SRI research, to help customer service operations respond better to caller’s emotions. The goal is to use this area of artificial intelligence to improve interactions between customer service reps (CSRs) and customers in real time.

As part of the research phase, the company compiled a database of 100,000 utterances from 3,000 speakers, culled from two million sales conversations. From this data, it has built a couple of tools to help customer service operations automate intonation understanding.

The first is a live coaching tool. It’s difficult to have management monitor every call, so only a small percentage gets monitored. With Oto, CSRs can get real-time coaching on every call to raise their energy or to calm a frustrated customer before a problem escalates. “In real time, we’re able to guide the agents on how they sound, how energetic they are, and we can nudge and push them to be more energetic,” Borschberg explained.

He says this has three main advantages: more engaged agents, higher sales conversion rates and better satisfaction scores and cost reduction.

The other product measures the quality of a customer experience and gives a score at the end of each call to help the CSR (and their managers) understand how well they did, simply based on intonation. It displays the score in a dashboard. “We’re building a universal understanding of satisfaction from intonation, where we can learn acoustic signatures that are positive, neutral, negative,” Borschberg said.

He sees a huge market opportunity here, pointing to Qualtrics, which sold to SAP last year for $8 billion. He believes that surveying people is just a part of the story. You can build a better customer experience when you understand intonation of just how well that experience is going, and you put it on a scale so that it makes it easy to understand just how well or how poorly you are doing.

The company has 20 employees today, with offices in New York, Zurich and Lisbon. It has seven customers working with the product so far, but it is still early days.

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This brilliant app waits on hold for you

DoNotPay helps you get out of parking tickets and cancel forgotten subscriptions, and now it can call you when it’s your turn in a customer service phone queue. The app today is launching “Skip Waiting On Hold.” Just type in the company you need to talk to, and DoNotPay calls for you using tricks to get a human on the line quickly. Then it calls you back and connects you to the agent so you never have to listen to that annoying hold music.

And in case the company tries to jerk you around or screw you over, the DoNotPay app lets you instantly share to social media a legal recording of the call to shame them.

How To Get Off hold

Skip Waiting On Hold comes as part of the $3 per month DoNotPay suite of services designed to save people time and money by battling bureaucracy on their behalf. It can handle DMV paperwork for you, write legal letters to scare businesses out of overcharging you and it provides a credit card that automatically cancels subscriptions when your free trial ends.

“I think the world would be a lot fairer place if people had someone fighting for them” says DoNotPay’s 22-year-old founder Joshua Browder. Indeed; $3 per month gets the iOS app‘s 10,000 customers unlimited access to all the features with no extra fees or commissions on money saved. “If DoNotPay takes a commission then we have an incentive to perpetuate the problems we are fighting against.”

Browder comes from a family of activists. His father Bill Browder got the Magnitsky Act passed, which lets the U.S. government freeze the foreign assets and visas of human rights abusers. It’s named after Bill’s Russian lawyer who was murdered in Moscow after uncovering a $230 million government corruption scheme linked to President Putin’s underlings.

DoNotPay app

“These big companies [and governments] are getting away with a lot,” Browder tells me. He hit a breaking point when frustrated with the process of appealing parking tickets. He built DoNotPay to cut through hassles designed to separate us from our money. In April it raised a $3.5 million seed round led by Felicis to develop an Android version after picking up early funding from Andreessen Horowitz. Surprisingly, the startup has never been sued.

For Skip Waiting On Hold, DoNotPay built out a database of priority and VIP customer service numbers for tons of companies. For legality, if you opt in to recording the exchanges, the app automatically plays a message informing both parties they’ll be recorded. A human voice detection system hears when a real agent picks up the phone, and then rings your phone. It’s like having customer service call you.

Not only can DoNotPay help you get in touch about cancelling subscriptions, scoring refunds or retrieving information, it’s like “a body camera for customer service calls,” Browder says. “Before they make a decision that rips off the customer, they’ll think ‘this could be made public and go viral and hurt our business.’ ” For example, an airline that jacks up prices for rescheduled flights surrounding hurricanes could be shamed for profiting off of natural disasters.

Record and share customer service calls

The full list of DoNotPay services includes:

  1. Customer service disputes where it contacts companies about refunds for Comcast bills, delayed flights, etc.
  2. The free trial credit card that auto-cancels subscriptions before you’re actually charged
  3. Traffic and parking appeals where it generates a letter for you based on answers to questions, like if signs were too hard to read or there was a mistake on the ticket
  4. Hidden money discovery that finds refunds in your bank fees, identifies forgotten subscriptions, gets you free stuff on your birthday and more
  5. Government paperwork assistance that can help you get DMV appointments and fill out forms
  6. Skip Waiting On Hold

Browder hopes that with time, companies and governments will make all these chores easier for everyone. To avoid putting itself out of a job, DoNotPay is constantly looking for new annoyances to eliminate. “I’m from the U.K. America seems to be a pay-to-play society. The more money you have, the more rights you have,” Browder concludes. But those rights could be restored for all by building a robot lawyer that’s affordable to everyone.

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Facebook has acquired Servicefriend, which builds ‘hybrid’ chatbots, for Calibra customer service

As Facebook prepares to launch its new cryptocurrency Libra in 2020, it’s putting the pieces in place to help it run. In one of the latest developments, it has acquired Servicefriend, a startup that built bots — chat clients for messaging apps based on artificial intelligence — to help customer service teams, TechCrunch has confirmed.

The news was first reported in Israel, where Servicefriend is based, after one of its investors, Roberto Singler, alerted local publication The Marker about the deal. We reached out to Ido Arad, one of the co-founders of the company, who referred our questions to a team at Facebook. Facebook then confirmed the acquisition with an Apple-like non-specific statement:

“We acquire smaller tech companies from time to time. We don’t always discuss our plans,” a Facebook spokesperson said.

Several people, including Arad, his co-founder Shahar Ben Ami, and at least one other indicate that they now work at Facebook within the Calibra digital wallet group on their LinkedIn profiles. Their jobs at the social network started this month, meaning this acquisition closed in recent weeks. (Several others indicate that they are still at Servicefriend, meaning they too may have likely made the move as well.)

Although Facebook isn’t specifying what they will be working on, the most obvious area will be in building a bot — or more likely, a network of bots — for the customer service layer for the Calibra digital wallet that Facebook is developing.

Facebook’s plan is to build a range of financial services for people to use Calibra to pay out and receive Libra — for example, to send money to contacts, pay bills, top up their phones, buy things and more.

It remains to be seen just how much people will trust Facebook as a provider of all these. So that is where having “human” and accessible customer service experience will be essential.

“We are here for you,” Calibra notes on its welcome page, where it promises 24-7 support in WhatsApp and Messenger for its users.

Screenshot 2019 09 21 at 23.25.18

Servicefriend has worked on Facebook’s platform in the past: specifically it built “hybrid” bots for Messenger for companies to use to complement teams of humans, to better scale their services on messaging platforms. In one Messenger bot that Servicefriend built for Globe Telecom in the Philippines, it noted that the hybrid bot was able to bring the “agent hours” down to under 20 hours for each 1,000 customer interactions.

Bots have been a relatively problematic area for Facebook. The company launched a personal assistant called M in 2015, and then bots that let users talk to businesses in 2016 on Messenger, with quite some fanfare, although the reality was that nothing really worked as well as promised, and in some cases worked significantly worse than whatever services they aimed to replace.

While AI-based assistants such as Alexa have become synonymous with how a computer can carry on a conversation and provide information to humans, the consensus around bots these days is that the most workable way forward is to build services that complement, rather than completely replace, teams.

For Facebook, getting its customer service on Calibra right can help it build and expand its credibility (note: another area where Servicefriend has build services is in using customer service as a marketing channel). Getting it wrong could mean issues not just with customers, but with partners and possibly regulators.

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Battlefield winner Forethought adds tool to automate support ticket routing

Last year at this time, Forethought won the TechCrunch Disrupt Battlefield competition. A $9 million Series A investment followed last December. Today at TechCrunch Sessions: Enterprise in San Francisco, the company introduced the latest addition to its platform, called Agatha Predictions.

Forethought CEO and co-founder Deon Nicholas said that after launching its original product, Agatha Answers (to provide suggested answers to customer queries), customers were asking for help with the routing part of the process, as well. “We learned that there’s a whole front end of that problem before the ticket even gets to the agent,” he said. Forethought developed Agatha Predictions to help sort the tickets and get them to the most qualified agent to solve the problem.

“It’s effectively an entire tool that helps triage and route tickets. So when a ticket is coming in, it can predict whether it’s a high-priority or low-priority ticket and which agent is best qualified to handle this question. And this all happens before the agent even touches the ticket. This really helps drive efficiencies across the organization by helping to reduce triage time,” Nicholas explained.

The original product (Agatha Answers) is designed to help agents get answers more quickly and reduce the amount of time it takes to resolve an issue. “It’s a tool that integrates into your Help Desk software, indexes your past support tickets, knowledge base articles and other [related content]. Then we give agents suggested answers to help them close questions with reduced handle time,” Nicholas said.

He says that Agatha Predictions is based on the same underlying AI engine as Agatha Answers. Both use Natural Language Understanding (NLU) developed by the company. “We’ve been building out our product, and the Natural Language Understanding engine, the engine behind the system, works in a very similar manner [across our products]. So as a ticket comes in the AI reads it, understands what the customer is asking about, and understands the semantics, the words being used,” he explained. This enables them to automate the routing and supply a likely answer for the issue involved.

Nicholas maintains that winning Battlefield gave his company a jump start and a certain legitimacy it lacked as an early-stage startup. Lots of customers came knocking after the event, as did investors. The company has grown from five employees when it launched last year at TechCrunch Disrupt to 20 today.

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Klaus, the ‘conversation review’ tool for support teams, picks up $1.9M seed

“No bad conversations between companies and their customers is what we’re shooting for,” Kair Käsper tells me. He’s the head of Growth of a relatively new startup called Klaus, which he founded together with old high school friend Martin Kõiva.

Most recently the pair were employees at Pipedrive, holding the roles of director of Product Marketing and global head of Customer Support, respectively. Many years prior to that they shared a flat together and worked on a number of projects. One of those was an applicant-tracking startup called Jobkitten “that didn’t really go anywhere.”

The latest Käsper and Kõiva venture, however, appears to already be on firmer footing. Described as a “conversation review and QA tool for support teams,” Klaus is designed to help companies improve the quality of customer service. Two years in the making but only launched formally six months ago, customers already include Automattic, Wistia and Soundcloud. And today the Estonian startup is disclosing $1.9 million in seed funding led by Creandum, the first Baltic investment by the Swedish VC firm and the first from its new fund.

“The problem is that maintaining an even, high level of customer service quality is hard,” explains Käsper. “It becomes even harder if you have over 20,000 monthly conversations with customers and your support team is 100 people in three offices.

“As the head of customer support, you want everyone on your team to provide answers that meet with internal standards, regardless of how long they’ve been with the company or how seriously they take their job. You get very anxious in this situation, because you have no idea about what’s going on in those thousands of conversations. For you, no visibility means no control.”

Screenshot 2

He says that his and Kõiva’s firsthand experience at Pipedrive taught them that the key to quality assurance is going through past interactions and giving systematic feedback to agents. “Kind of like code review in engineering or the editorial process in writing,” he says. “Teams all over the world are discovering this now, but they almost always start with a manual process, managed in spreadsheets. They get stuck fast.”

To make this type of feedback loop more scalable, Klaus has created a purpose-built UI for giving internal feedback. Smartly, it also integrates with modern SaaS help desk solutions, such as Zendesk and Intercom.

“[The software also has] countless specialized features that allow you to focus on the actual feedback instead of managing a spreadsheet,” adds the Klaus head of Growth. They include the ability to easily filter out conversations for review, rate them based on a customized score card and notify agents of received feedback through email or Slack.

Meanwhile, the young company makes money by charging a monthly or yearly subscription fee based on how many users are connected to its app. In other words, just like Pipedrive before it, another classic enterprise SaaS play out of Estonia.

Update: An earlier version of this article wrongly said that Kair Käsper is CEO of Klaus; his job title is actually head of Growth.

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Nine lessons on how Niantic reached a $4B valuation

We’ve captured much of Niantic’s ongoing story in the first three parts of our EC-1, from its beginnings as an “entrepreneurial lab” within Google, to its spin-out as an independent company and the launch of Pokémon GO, to its ongoing focus on becoming a platform for others to build augmented reality products upon.

It’s not an origin story that serves as an easily replicable blueprint — but if we zoom out a bit, what’s to be learned?

A few key themes stuck with me as I researched Niantic’s story so far. Some of them – like the challenges involved with moving millions of users around the real world – are unique to this new augmented reality that Niantic is helping to create. Others – like that scaling is damned hard – are well-understood startup norms, but interesting to see from the perspective of an experienced team dealing with a product launch that went from zero to 100 real quick.

The reading time for this article is 21 minutes (5,125 words).

Build on top of what works best

Everything Niantic has built so far is an evolution of what the team had built before it. Each major step on Niantic’s path has a clear footprint that precedes it; a chunk of DNA that proved advantageous, and is carried along into the next thing.

Looking back, it’s a cycle we can see play out on repeat: build a thing, identify what works about it, trim the extra bits, then build a new thing from that foundation.

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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.

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Salesforce update brings AI and Quip to customer service chat experience

When Salesforce introduced Einstein, its artificial intelligence platform in 2016, it was laying the ground work for artificial intelligence underpinnings across the platform. Since then the company has introduced a variety of AI enhancements to the Salesforce product family. Today, customer service got some AI updates.

The goal of any customer service interaction is to get the customer answers as quickly as possible. Many users opt to use chat over phone, and Salesforce has added some AI features to help customer service agents get answers more quickly in the chat interface. (The company hinted that phone customer service enhancements are coming.)

For starters, Salesforce is using machine learning to deliver article recommendations, response recommendations and next best actions to the agent in real time as they interact with customers.  “With Einstein article recommendations, we can use machine learning on past cases and we can look at how articles were used to successfully solve similar cases in the past, and serve up the best article right in the console to help the agent with the case,” Martha Walchuk, senior director of product marketing for Salesforce Service Cloud explained.

Salesforce Service Console. Screenshot: Salesforce

The company is also using similar technology to provide response recommendations, which the agent can copy and paste into the chat to speed up the time to response. Before the interaction ends, the company can offer the next best action (which was announced last year) based on the conversation. For example, they could offer related information, an upsell recommendation or whatever type of action the customer defines.

Salesforce is also using machine learning to help route each person to the most appropriate customer service rep. As Salesforce describes it, this feature uses machine learning to filter cases and route them to the right queue or agent automatically, based on defined criteria such as best qualified agent or past outcomes.

Finally, the company is embedding Quip, the company it acquired in 2016 for $750 million, into the customer service console to allow agents to communicate with one another to find answers to difficult problems. That not only helps solve the issues faster, the conversations themselves become part of the knowledge base, which Salesforce can draw upon to help teach the machine learning algorithms about the correct responses to commonly asked questions in the future.

As with the Oracle AI announcement this morning, this use of artificial intelligence in sales, service and marketing is part of a much broader industry trend, as these companies try to inject intelligence into workflows to make them run more efficiently.

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