chatbots
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Whatfix nabs $90M to help workers onboard and get the most out of their IT stacks
“Digital transformation” has been on the mind of many an organization in the last year: the pandemic and the shift it’s brought to how we work are speeding up investments in new apps, infrastructure and work practices to improve productivity regardless of where we sit all day. Now, it looks like we’re on to the next stage of that journey: actually figuring out how to adopt and run with all that new tech.
In a sign of the times, today a startup called Whatfix — which has built a platform that helps make better use of tech investments by giving chatbot-style guidance to users on how to use apps, with the option also to apply AI to understand what a person is doing to suggest what actions to take next — is announcing $90 million in funding. It will use the money to continue expanding its tech platform and hiring more talent to meet demand, said CEO Khadim Batti, who co-founded the company with Vara Kumar (CTO), in an interview this week.
Sources close to the company — co-headquartered in San Jose and Bangalore — confirmed that the Series D round was made at a valuation of around $600 million, triple Whatfix’s value in its Series C round last year.
That sharp rise is due in part to the state of the market today, but also the company’s growth within that bigger trend. Whatfix today has some 500 global customers on its books, The Netherlands Red Cross, Experian, Sentry Financial Services, Cardinal Health Canada, BMC Software Inc., and Bausch & Lomb among them. Some 75% of its business is coming out of the U.S., with another 18% from Europe. Revenues in the last six months have been growing at a rate of 100% quarter-on-quarter.
“This pandemic has proven an inflection point for adoption,” said Batti (pictured above, left with Kumar, right).
This latest tranche of equity funding is coming from a mix of financial and strategic investors.
SoftBank’s Vision Fund 2 is leading the round, with Eight Roads Ventures, Sequoia Capital India, Dragoneer Investment Group, F-Prime Capital and Cisco Investments also investing. The company has raised just under $140 million in total.
“Digital adoption solutions” — the general term describing what Whatfix has built — have become a popular solution for enterprises that have found themselves in an IT pickle, Batti said.
“We’ve seen more than $500 billion spent on enterprise software, with areas like SaaS growing very fast. There is so much there, and every employee has access to do better work. But most are not adopting or using that software. This means a lot [of inefficiency] in ‘digital transformation,’” said Batti. “We are focusing on fixing this problem.”
Digital adoption and digital experience overall can come in many forms these days.
They include assistants that are embedded directly into apps themselves (with some versions of this — such as Clippy on Word — nearly as old as software itself). The category also includes separate platforms that integrate at the back end with the apps that you use, providing not just a single ingestion point for data but intelligence on how best to use it, and what to use. (Dooly for sales teams is an example of that, although I don’t know if it would describe itself as a “digital adoption solution” per se.)
Others like Pendo are geared more at observing how your sites and apps are being adopted and used by others. And there are a number of others out there specifically looking at digital adoption by enterprises and competing directly with Whatfix: they include Apty, Userlane, Applearn.
One of the biggest — WalkMe — yesterday announced an IPO at an estimated $2.5 billion valuation.
Overall digital adoption and digital experience are big businesses: one analyst estimates that the market is growing currently at a rate of just under 11% annually and will be worth $15.8 billion by 2025.
Whatfix is built around the premise that it sits on top of whatever apps a company may choose to use, and will work with just about any piece of modern software, Batti said. That includes Whatfix being able to provide assistance on apps even when they have been customised for a particular workplace. It most commonly appears like a little chatbot on the user’s screen, like the one in this paragraph, which can expand with more details and information as needed, like this:
The company works with the most popular software packages — including Salesforce, MS Dynamics, Oracle’s CRM platform, ServiceNow, SuccessFactors, SharePoint, Workday — but, since it is used in the form of a browser extension or an overlay integrated by a company’s IT department, it can be used to help guide people with any application that’s available over the web. Batti said that one priority the startup has is to build deeper integrations with specific apps so that Whatfix can be used better across mobile and with local apps in future, not just via the web.
Many might think of “digital adoption” as training someone to use a particular software package, and while Whatfix is used for that, the company has also found a lot of traction as a tool beyond it, providing support on a more regular basis and across a wider variety of use cases, whether it’s to help guide people through app usage, or to monitor what they are doing in order to help suggest what to do next, and even populate relevant fields if “next” means using a different app.
The platform can be used to create usage guides, multilingual support, multi-device support, user tracking and more, and it comes with low-code options (it can be intergrated into an app with a single line of code, the company says).
The company claims its assistants can increase employee productivity by 35%, reduce training time and costs by 60%, reduce employee case tickets by 50% and increase application data accuracy by 20%.
While the field for digital adoption is very crowded today, it’s numbers like these, Whatfix’s own growth, and the fact that software is continuing to get more capable, but also more complex, that have interested investors.
“Digital Adoption Solutions are enhancing the growth and importance of SaaS products for enterprises globally,” said Munish Varma, Managing Partner, SoftBank Investment Advisers, in a statement. “Whatfix makes it easier for companies to use SaaS products, which increases productivity. Whatfix, with its roster of global clients, is well placed to become a DAS leader, and we are excited to be part of their journey.” Sumer Juneja, Partner, SoftBank Investment Advisers, added: “Enterprises spend billions on applications across multiple functions and yet employee adoption is low. Quick adoption ensures payback on software investments. Whatfix’s solutions will be a key driver for enterprises to achieve this goal, which is reflected in their growth.”
What will be interesting to watch is how platforms like Whatfix’s will evolve over time, and what further functions they might take on. For example, in enterprises, one of the biggest vulnerabilities in security has been how people mistakenly click on dodgy links in emails or otherwise inadvertently pass on information to malicious hackers. Could there be a role for digital adoption assistants to identify when this might happen and alert people before they click the wrong way? Regardless, the question and very existence of loopholes like that are signals for why we’ll probably why we’ll continue to see tools like Whatfix’s around for some time to come.
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Moveworks expands IT chatbot platform to encompass entire organization
When investors gave Moveworks a hefty $75 million Series B at the end of 2019, they were investing in a chatbot startup that to that point had been tuned to answer IT help questions in an automated way. Today, the company announced it had used that money to expand the platform to encompass employee questions across all lines of business.
At the time of that funding, nobody could have anticipated a pandemic either, but throughout last year as companies moved to work from home, having an automated systems in place like Moveworks became even more crucial, says CEO and company co-founder Bhavin Shah.
“It was a tragic year on a variety of fronts, but what it did was it coalesced a lot of energy around people’s need for support, people’s need for speed and help,” Shah said. It helps that employees typically access the Moveworks chatbot inside collaboration tools like Slack or Microsoft Teams, and people have been spending more time in these tools while working at home.
“We definitely saw a lot more interest in the market, and part of that was fueled by the large-scale adoption of collaboration tools like Slack and Microsoft Teams by enterprises around the world,” he said.
The company is working with 100 large enterprise customers today, and those customers were looking for a more automated way for employees to ask questions about a variety of tooling, from HR to finance and facilities management. While Shah says expanding the platform to move beyond IT into other parts of an organization had been on the roadmap, the pandemic definitely underscored the need to expand even more.
While the company spent its first several years tuning the underlying artificial intelligence technology for IT language, they had built it with expansion in mind. “We learned how to build a conversational system so that it can be dynamic and not be predicated on some person’s forethought around [what the question and answer will be] — that approach doesn’t scale. So there were a lot of things around dealing with all these enterprise resources and so forth that really prepared us to be an enterprise-wide partner,” Shah said.
The company also announced a new communications tool that enables companies to use the Moveworks bot to communicate directly with employees to get them to take some action. Shah says companies usually send out an email that, for example, employees have to update their password. The bot tells you it’s time to do that and provides a link to walk you through the process. He says that beta testers have seen a 70% increase in responses using the bot to communicate about an action instead of email.
Shah recognizes that a technology that understands language is going to have a lot of cultural variances and nuances and that requires a diverse team to build a tool like this. He says that his HR team has a set of mandates to make sure they are interviewing people in under-represented roles to build a team that reflects the needs of the customer base and the world at large.
The company has been working with about a dozen customers over the last nine months on the platform expansion, iterating with these customers to improve the quality of the responses, regardless of the type of question or which department it involves. Today, these tools are generally available.
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Landbot closes $8M Series A for its ‘no code’ chatbot builder
Barcelona-based Landbot, a “no-code” chatbot builder, has bagged an $8 million Series A led by the Spanish-Israeli VC firm Swanlaab, alongside support from Spain’s innovation-focused public agency, CDTI. Previous investors Nauta Capital, Encomenda and Bankinter also participated in the round.
We last chatted to Landbot back in 2018 when it raised a $2.2 million seed and had 900+ customers. It’s grown that to ~2,200 paying customers, with some 50,000 individuals now using its tool (across both free and paid accounts).
Since its seed it’s also increased recurrent revenues 10x — and is expecting growth to keep stepping up, fuelled by the new financing.
It says the coronavirus pandemic has supercharged demand for conversational landing pages as all sorts of businesses look for ways to automate higher volumes of digitally inbound customer comms, without needing to make major investments in in-house IT.
Landbot’s customers range from SMEs to specific teams and products within larger organisations, with the startup name-checking the likes of Nestlé, MediaMarkt, Coca-Cola, Cepsa, PcComponentes and Prudential among its customer roster.
“We are seeing strong traction from industries like eCommerce, Financial Services and Marketing Agencies,” CEO & co-founder Jiaqi Pan tells TechCrunch. “The ecommerce segment is one we have seen the most growth in since COVID-19, where we increased 2x the number of customers from ecommerce industry.”
The new funding will be used to double Landbot’s team during 2021 (currently it employs 40 people) — with hiring planned across sales, marketing and engineering.
The startup, which launched its “no code” flavor of chatbot builder back in 2017, previously relocated HQ from Valencia to Barcelona to help with recruitment.
Since Landbot’s launch, the burgeoning “no code/low code” movement has become a fully fledged trend driven by demand for productivity — and lead-boosting digital services outstripping most businesses’ supply of expert in-house techies able to build stuff.
Hence the rise of service-builder tools that make customizable tech capabilities accessible to non-technical staff.
The pandemic has merely poured more fuel on this fire — and low-friction tools like Landbot are clearly reaping the rewards.
Interestingly, as well as competing with other conversational chatbot builders, like San Francisco-based ManyChat, Landbot says it’s seeing traction from customers who are seeking to replace web forms with more engaging chat interfaces.
Its drag-and-drop chatbot builder tool supports information workers to design what Landbot bills as “an immersive web page experience filled with gifs and visual elements to capture the attention of the end-user” — so you can understand the appeal for SMEs to be able to replace their boring old static forms with an experience any smartphone user is familiar with from using messaging apps like WhatsApp.
“In terms of the main competitor in the no-code space, we have some overlap with ManyChat as the most direct competitor for Chatbot. On the other hand, as we have a lot of customers using us to replace their forms we are competing also against form builders like Typeform,” says Pan, the latter another Barcelona-based startup which similarly bills itself as a platform for “conversational” and “interactive” data collection.
Landbot notes it recently acquired India-based Morph.AI, a chat-based marketing automation tool, which it’s using to help convert social, website and ad traffic into leads — also with the aim of further expanding into presence in the Asian market.
To date, 90% of its customers are international, with 60% coming from the U.S., U.K. and Germany.
Commenting on the Series A in a statement, Juan Revuelta, general partner of Swanlaab, said: “The beauty of Landbot is in the drag and drop solution of the product. The simplicity is critical to making this product accessible to everyone across many different types of business. If you’re a small company you don’t have the luxury of time or money to solve issues in customer service or run lavish marketing campaigns.
“Landbot helps all businesses to have truly frictionless conversations with customers and exchange the data they need to make smarter decisions and scale. The team has had a remarkable 2020, and we’re excited to support them in helping more businesses this year.”
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ultimate.ai scores $20M for a supportive approach to customer service automation
Ultimate.ai, a virtual customer service agent builder, has closed a $20 million Series A round of funding, led by Omers Ventures with participation from Felicis Ventures and existing investors HV Capital, and Maki.vc — bringing its total raised to date to more than $25 million.
The European startup’s flagship claim for the data-ingesting bot-builder platform is it’s capable of automating up to 80% of customer support interactions.
The focus, as tends to be the case for all these customer service conversational AI plays, is freeing (human) support agents from dealing with dull, repetitive stuff — so they can apply their (less limited) skills to more complex, consultative or emotionally demanding customer queries.
When we last spoke to the Helsinki- and Berlin-based startup, back in 2018 for a $1.3 million seed round, it described itself as a “language-agnostic” conversational AI — having started out with the hard (linguistic) challenge of Finnish — claiming that gave it an edge in a competitive space with customers in non-English speaking markets. (Though it did also tackle English too.)
Two years on the startup’s marketing focus is broader; today it talks about its customer service automation platform as an “AI-first” ‘no code’ tool — sating it wants to empower b2c users to get the most out of AI by helping them design virtual agents that can usefully handle complex customer interactions.
ultimate.ai will hand-hold you through the process of building a super savvy customer service robot, is the pitch.
Co-founder and CEO Reetu Kainulainen claims it’s always been “no code and intuitive” — though there’s now a handy reference label to align what it’s doing with a wider b2b trend. (‘No code’ or ‘low code’ referring to a digital tool-building movement that aims to widen access to powerful technologies like AI without the need for the user to possess deep technical know-how in order to make useful use of them.)
“Everything we build is to guide users to creating the best virtual agents. The whole user journey — discovery, design, expansion — is all within ultimate.ai,” Kainulainen tells TechCrunch.
“In the past two years, we have been laser focused on building a very deep customer service automation platform — one that goes beyond simple FAQ answers in chat — and enables brands to design complex, personalized workflows that can be deployed across all digital support channels.
“We believe that customer service automation will be its own category in the future and so we are working hard to define what that means today.”
As an example, Kainulainen points to “one click” integration with “any major CRM” (including Salesforce and Zendesk) — which lets customers quickly import existing customer support logs so ultimate.ai’s platform can analyze the data to help them build a useful bot.
“Immediately, you are shown a breakdown of your most common customer service cases and the impact automation can have for your business,” he goes on, saying the platform shows templates and “best practices” to help the customer design their automation workflows — “tailored for your cases and industry”.
Once a virtual agent is live users can run A/B tests via the platform to check and optimize performance — and, here too, the promise is further hand-holding, with Kainulainen saying it will “proactively suggests new cases and data to improve your virtual agent”.
“Where we are very strong is in large-scale customer support organizations, who are looking for a holistic, advanced automation platform that can be managed and implemented by non-technical users,” he says.
“The bigger picture is that each of our competitors views the opportunity more narrowly than ultimate.ai does: Our best competitors are either focused on chatbots only, or otherwise limited to the ecosystem of their mother company. Our vision has always been the big picture: Of automation becoming one of the primary means of providing customer service.”
Having multilingual smarts remains an advantage, with ultimate.ai’s virtual agents able to handle interactions in over 20 languages at this point.
“Our market — the customer service automation market — has a lot of players,” Kainulainen goes on, name-checking the likes of Ada Support and Einstein Bots (Salesforce’s own solution) as key competitors.
“This is because it is new and, until recently, solutions were so early that there were virtually no barriers to entry. But the market has changed a lot in the last four years. There are now only a handful of players globally that are worth paying attention to and we are one of them.”
The 2016-founded startup is hitting the nail on the head for a growing number of customers — with close to 100 signed up to its platform at this point, including the likes of Deezer, Telia, Footasylum, and Finnair. Per Kainulainen, it works best for “b2c brands with large (and often repetitive) customer service volumes”.
“This is where automation can provide a huge impact from day one and really free up people to take on more creative and challenging work. We have a broad customer base of close to 100 great brands… and do particularly well in industries like retail/ecommerce, telecommunications and travel,” he adds.
It’s enjoyed a major growth spurt this year, as businesses of all stripes were forced to ramp up their attention to online customer interactions as the coronavirus pandemic became an engine for digital activity.
Customer retention has also risen in priority for many businesses, as a highly contagious virus and public health safety measures put in place to reduce its spread, flipped markets into recession — which Kainulainen points to as another growth driver.
Overall, he says it’s tripled ARR over the last 12 months (albeit, it was the same growth story last year too). Plus it’s tripled headcount to deal with the COVID-19 effect.
Now ultimate.ai is gearing up for fresh growth — saying it’s expecting major developments next year.
“COVID-19 has… prompted one of the most accelerated periods of change in the customer service industry,” says Kainulainen, predicting 2021 will bring “immense innovation” in the space — and that “booming” automation technologies will take “center stage”.
Of course it’s a convenient narrative for a customer service chatbot maker to tell.
But COVID-19 is clearly accelerating digital transformation of consumer focused businesses — a movement that, logically, pumps demand for smarter tools to handle online customer support. So those positioned to harness new momentum for customer service automation — by being able to offer an accessible, scalable and effective product (as ultimate.ai claims it does) — are sitting pretty in the middle of a pandemic.
“We believe that the best product will win this market,” adds Kainulainen. “We have a big vision for what we want ultimate.ai to be. Market maturity for our technology has accelerated massively in 2020, achieving in one year what could have probably taken five. We will capitalize on that by building more, faster.”
The Series A funding will go on sales and marketing, with a planned market push in North America and a desire to go deeper throughout Europe, as well as being ploughed into further product development.
And while — clearly — not every potential b2c customer will be able to ‘automagic’ away 80% of their customer support pings, Kainulainen argues ultimate.ai can still offer a compelling sales pitch to businesses with more “consultative” customer support needs, where automation will only be able to play a far more limited role.
“There’s often a strong correlation between how consultative a customer service organization needs to be and how highly trained and experienced their team is. In other words, it is often the case that organizations with ‘lower bound’ automation potential also only need 10% automation to still drive a huge ROI,” he suggests.
“For example, one of our customers is a large national pharmacy group, where customer service agents are qualified pharmacists who provide prescription medical advice. Here, the goal isn’t to achieve a very high automation rate but rather to automate basic, repetitive processes to free up the pharmacists for more challenging tasks that better use their capabilities.
“For this customer, in addition to the automation of simple requests (which alone provides a huge value) our real-time answer recommendations help pharmacists respond faster and easier.”
Commenting on the Series A in a statement, Omers Ventures managing partner, Jambu Palaniappan, dubbed the startup’s growth “truly spectacular”, as well as lauding its “world-class team” and founders “with a strong vision and unrivalled knowledge of AI”.
“There are numerous chatbot companies out there but ultimate.ai represents something much bigger because at its core is an automation company with massive potential,” he added. “We look forward to working with Sarah, Reetu, Jaakko, and Markus as they expand internationally and advance their deep product capabilities even further.”
“The customer service industry is undergoing an automation revolution. In ultimate.ai, we saw a vision that’s bold enough to lead the way,” added Aydin Senkut, founder and managing partner of Felicis Ventures, in another supporting statement. “We believe that, just in the same way that category leaders have defined marketing and sales automation, ultimate.ai will do the same for customer service.”
Jambu Palaniappan, managing partner at Omers Ventures, will join the ultimate.ai board. Aydin Senkut, founder and managing partner of Felicis Ventures, will join as an investor, alongside former head of Airbnb for Business Mark McCabe, and former EVP global sales of payment giant Adyen, Thijn Lamers.
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Leena AI nabs $8M Series A as it expands from chatbots to HR service platform
When we covered Leena AI as a member of the Y Combinator Summer 2018 cohort, the young startup was firmly focused on building HR chatbots, but in the intervening years it has expanded the vision to a broader HR policy platform. Today, the company announced an $8 million Series A led by Greycroft with help from several individual industry investors.
Company CEO and co-founder Adit Jain says that in 2018 the company was concentrating on building an intelligent virtual assistant for HR-related questions. It allowed employees to ask the bot questions like how many vacation days they have left or what holidays they have off this year.
Over the last couple of years since leaving Y Combinator, the company has moved into broader HR service delivery. “So I’m talking about having an intelligent case management, knowledge management and document management system, which is backing the virtual assistant as well,” Jain explained.
He says that users should think of it as an entire system where the chatbot is the user interface for employees to interact with the HR information on the back end. For example, he says that the knowledge management component is where the chatbots find the answers to questions, and as employees interact with the chatbot, it grows more intelligent based on the feedback from them.
The document management piece enables HR to write or import HR policies and the case management system comes into play when the situation is too complex for the chatbot to handle and it has to be escalated to a human HR representative.
When we spoke to Jain in September 2018 at the time of his startup’s $2 million seed round, he had 16 customers and hoped to have 50 in the next 12-18 months. Today the company has 100 enterprise customers with 300,000 employees using the platform worldwide.
In fact, the pandemic has fueled business with more than half of those customers coming on board this year. He says this is because companies are looking for ways to digitize processes like HR as employees are working from home more.
“This is a trend that’s going to continue as organizations have realized the value of doing things with more and more digital applications taking care of your processes […] especially mundane, repeatable tasks being handed over to technology more and more,” Jain said.
As the business has grown this year, the company has expanded from 30 to 75 employees and he hopes to double that number in the next year. As he does, he has discussed with his lead investor how to build a diverse and inclusive culture at Leena AI .
One thing he is trying to do is raise some money from a diverse group of investors, approximately $400,000, and his hope is that these diverse investors can help him build solid diversity programs as he adds employees to his growing company.
That the startup hasn’t only grown during these turbulent times, but thrived, shows that companies are looking to modernize every part of the enterprise technology stack, and that includes HR.
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Directly, which taps experts to train chatbots, raises $11M, closes out Series B at $51M
Directly, a startup whose mission is to help build better customer service chatbots by using experts in specific areas to train them, has raised more funding as it opens up a new front to grow its business: APIs and a partner ecosystem that can now also tap into its expert network. Today Directly is announcing that it has added $11 million to close out its Series B at $51 million (it raised $20 million back in January of this year, and another $20 million as part of the Series B back in 2018).
The funding is coming from Triangle Peak Partners and Toba Capital, while its previous investors in the round included strategic backers Samsung NEXT and Microsoft’s M12 Ventures (who are both customers, alongside companies like Airbnb), as well as Industry Ventures, True Ventures, Costanoa Ventures and Northgate. (As we reported when covering the initial close, Directly’s valuation at that time was at $110 million post-money, and so this would likely put it at $120 million or higher, given how the business has expanded.)
While chatbots have now been around for years, a key focus in the tech world has been how to help them work better, after initial efforts saw so many disappointing results that it was fair to ask whether they were even worth the trouble.
Directly’s premise is that the most important part of getting a chatbot to work well is to make sure that it’s trained correctly, and its approach to that is very practical: find experts both to troubleshoot questions and provide answers.
As we’ve described before, its platform helps businesses identify and reach out to “experts” in the business or product in question, collect knowledge from them, and then fold that into a company’s AI to help train it and answer questions more accurately. It also looks at data input and output into those AI systems to figure out what is working, and what is not, and how to fix that, too.
The information is typically collected by way of question-and-answer sessions. Directly compensates experts both for submitting information as well as to pay out royalties when their knowledge has been put to use, “just as you would in traditional copyright licensing in music,” its co-founder Antony Brydon explained to me earlier this year.
It can take as little as 100 experts, but potentially many more, to train a system, depending on how much the information needs to be updated over time. (Directly’s work for Xbox, for example, used 1,000 experts but has to date answered millions of questions.)
Directly’s pitch to customers is that building a better chatbot can help deflect more questions from actual live agents (and subsequently cut operational costs for a business). It claims that customer contacts can be reduced by up to 80%, with customer satisfaction by up to 20%, as a result.
What’s interesting is that now Directly sees an opportunity in expanding that expert ecosystem to a wider group of partners, some of which might have previously been seen as competitors. (Not unlike Amazon’s AI powering a multitude of other businesses, some of which might also be in the market of selling the same services that Amazon does).
The partner ecosystem, as Directly calls it, use APIs to link into Directly’s platform. Meya, Percept.ai, and SmartAction — which themselves provide a range of customer service automation tools — are three of the first users.
“The team at Directly have quickly proven to be trusted and invaluable partners,” said Erik Kalviainen, CEO at Meya, in a statement. “As a result of our collaboration, Meya is now able to take advantage of a whole new set of capabilities that will enable us to deliver automated solutions both faster and with higher resolution rates, without customers needing to deploy significant internal resources. That’s a powerful advantage at a time when scale and efficiency are key to any successful customer support operation.”
The prospect of a bigger business funnel beyond even what Directly was pulling in itself is likely what attracted the most recent investment.
“Directly has established itself as a true leader in helping customers thrive during these turbulent economic times,” said Tyler Peterson, Partner at Triangle Peak Partners, in a statement. “There is little doubt that automation will play a tremendous role in the future of customer support, but Directly is realizing that potential today. Their platform enables businesses to strike just the right balance between automation and human support, helping them adopt AI-powered solutions in a way that is practical, accessible, and demonstrably effective.”
In January, Mike de la Cruz, who took over as CEO at the time of the funding announcement, said the company was gearing up for a larger Series C in 2021. It’s not clear how and if that will be impacted by the current state of the world. But in the meantime, as more organizations are looking for ways to connect with customers outside of channels that might require people to physically visit stores, or for employees to sit in call centres, it presents a huge opportunity for companies like this one.
“At its core, our business is about helping customer support leaders resolve customer issues with the right mix of automation and human support,” said de la Cruz in a statement. “It’s one thing to deliver a great product today, but we’re committed to ensuring that our customers have the solutions they need over the long term. That means constantly investing in our platform and expanding our capabilities, so that we can keep up with the rapid pace of technological change and an unpredictable economic landscape. These new partnerships and this latest expansion of our recent funding round have positioned us to do just that. We’re excited to be collaborating with our new partners, and very thankful to all of our investors for their support.”
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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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Espressive lands $30M Series B to build better help chatbots
Espressive, a four-year-old startup from former ServiceNow employees, is working to build a better chatbot to reduce calls to company help desks. Today, the company announced a $30 million Series B investment.
Insight Partners led the round with help from Series A lead investor General Catalyst along with Wing Venture Capital. Under the terms of today’s agreement, Insight founder and managing director Jeff Horing will be joining the Espressive Board. Today’s investment brings the total raised to $53 million, according to the company.
Company founder and CEO Pat Calhoun says that when he was at ServiceNow he observed that, in many companies, employees often got frustrated looking for answers to basic questions. That resulted in a call to a Help Desk requiring human intervention to answer the question.
He believed that there was a way to automate this with AI-driven chatbots, and he founded Espressive to develop a solution. “Our job is to help employees get immediate answers to their questions or solutions or resolutions to their issues, so that they can get back to work,” he said.
They do that by providing a very narrowly focused natural language processing (NLP) engine to understand the question and find answers quickly, while using machine learning to improve on those answers over time.
“We’re not trying to solve every problem that NLP can address. We’re going after a very specific set of use cases which is really around employee language, and as a result, we’ve really tuned our engine to have the highest accuracy possible in the industry,” Calhoun told TechCrunch.
He says what they’ve done to increase accuracy is combine the NLP with image recognition technology. “What we’ve done is we’ve built our NLP engine on top of some image recognition architecture that’s really designed for a high degree of accuracy and essentially breaks down the phrase to understand the true meaning behind the phrase,” he said.
The solution is designed to provide a single immediate answer. If, for some reason, it can’t understand a request, it will open a help ticket automatically and route it to a human to resolve, but they try to keep that to a minimum. He says that when they deploy their solution, they tune it to the individual customers’ buzzwords and terminology.
So far they have been able to reduce help desk calls by 40% to 60% across customers with around 85% employee participation, which shows that they are using the tool and it’s providing the answers they need. In fact, the product understands 750 million employee phrases out of the box.
The company was founded in 2016. It currently has 65 employees and 35 customers, but with the new funding, both of those numbers should increase.
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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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ServiceNow teams with Workplace by Facebook on service chatbot
One of the great things about enterprise chat applications, beyond giving employees a common channel to communicate, is the ability to integrate with other enterprise applications. Today, Workplace, Facebook’s enterprise collaboration and communication application, and ServiceNow announced a new chatbot to make it easier for employees to navigate a company’s help desks inside Workplace Chat.
The beauty of the chatbot is that employees can get answers to common questions whenever they want, wherever they happen to be. The Workplace-ServiceNow integration happens in Workplace Chat and can can involve IT or HR help desk scenarios. A chatbot can help companies save time and money, and employees can get answers to common problems much faster.
Previously, getting these kind of answers would have required navigating multiple systems, making a phone call or submitting a ticket to the appropriate help desk. This approach provides a level of convenience and immediacy.
Companies can brainstorm common questions and answers and build them in the ServiceNow Virtual Agent Designer. It comes with some standard templates, and doesn’t require any kind of advanced scripting or programming skills. Instead, non-technical end users can adapt pre-populated templates to meet the needs, language and workflows of an individual organization.
Screenshot: ServiceNow
This is all part of a strategy by Facebook to integrate more enterprise applications into the tool. In May at the F8 conference, Facebook announced 52 such integrations from companies like Atlassian, SurveyMonkey, HubSpot and Marketo (the company Adobe bought in September for $4.75 billion).
This is part of a broader enterprise chat application trend around making these applications the center of every employee’s work life, while reducing task switching, the act of moving from application to application. This kind of integration is something that Slack has done very well and has up until now provided it with a differentiator, but the other enterprise players are catching on and today’s announcement with ServiceNow is part of that.
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