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Youper, a chatbot that helps users navigate their emotions, raises $3 million in seed funding
Youper, a mental health app with a chatbot it calls an “emotional health assistant,” has raised $3 million in seed funding from Goodwater Capital. The funds will be used to accelerate development of Youper’s artificial intelligence-based capabilities and grow its user base.
Based in San Francisco, Youper was co-founded in 2016 by Dr. Jose Hamilton. For a decade, Hamilton worked as a psychiatrist in clinical settings, seeing more than 3,000 patients. While talking to them, he realized that a handful of barriers kept many people from seeking help earlier, even if they had dealt with anxiety or depression for years.
“The first one is fear, taking care of yourself, talking about your mental health, understanding your mental health,” he tells TechCrunch. “Seeing a therapist or psychiatrist is super intimidating. That’s why all of my patients used to say the same things. The second barrier is cost, of course. Psychiatrists and therapists are super expensive.”
Hamilton teamed up with co-founders Diego Couto, the startup’s chief product and growth officer, and Thiago Marafon, its CTO, to create an app that would make mental healthcare less intimidating and more accessible. They originally created an app that did not have a conversational interface. Instead, Hamilton says it took a similar approach to Calm and Headspace. But that resulted in a very low user engagement rate and, after a year, the team realized Youper needed to provide a more personalized experience, matching users to the right psychological techniques, including cognitive behavioral techniques and mindfulness, for their needs.
Youper is part of a growing roster of apps that use AI-based chatbots to help users improve their emotional health, including Woebot, Wysa and X2’s Tess. Hamilton says Youper wants to differentiate with its focus on personalization, combining mental health research and user data to match the right psychological techniques with users.
Screenshots from Youper, an app for emotional well-being.
The startup claims Youper has been downloaded more than one million times so far. Most of its users are young adults, and there are more women than men who use Youper.
“I think that’s because women are facing new challenges in our society by conquering new spaces and assuming new roles, and that poses an emotional toll. Another reason is that women are more tuned into self-care than men,” he says. “Sometimes I feel that we men wait for too long suffering in silence.”
For users who have never consulted with a provider, Youper provides a gentle introduction to the types of questions and exercises they might experience in therapy. The questions and exercises given by Youper’s chatbot are meant to help users achieve a better understanding of their emotions, thoughts and behavior.
Youper’s chatbot asks users to focus on their thoughts and identify how they are feeling from a menu of descriptive words. Then a scale lets them rate the strength of that emotion from “slightly” to “extremely.” More questions help them narrow down what is causing those feelings and track their mood. Users are also given options for mindfulness exercises and journaling prompts.
Hamilton says that the average time users spend during each session with its chatbot is about seven minutes, with 80% reporting a reduction in negative moods after one conversation. The startup also claims that after 30 days, a quarter of people who signed up for Youper are still active users.
Youper is currently free, though the company may test a freemium model in the future with premium features. It uses anonymized user data in its own research to improve Youper, but keeps it private and does not share or sell user data or information.
Of course, an app is not a replacement for seeing a therapist or psychiatrist, but Youper presents a much lower barrier to entry for people who worried about the stigma of seeing a professional. Hamilton says he hopes using Youper will encourage more people to seek medical treatment sooner if they need it by making them more comfortable with the idea of discussing their emotional health.
“On average, it takes 10 years for someone to finally talk to a health provider. This could become 10 minutes with an app like Youper,” Hamilton says. “Having an app with a super low barrier to entry, no stigma, something that is about emotional health and taking care of yourself, shows that you don’t need to be afraid.”
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AI has become table stakes in sales, customer service and marketing software
Artificial intelligence and machine learning has become essential if you are selling sales, customer service and marketing software, especially in large enterprises. The biggest vendors from Adobe to Salesforce to Microsoft to Oracle are jockeying for position to bring automation and intelligence to these areas.
Just today, Oracle announced several new AI features in its sales tools suite and Salesforce did the same in its customer service cloud. Both companies are building on artificial intelligence underpinnings that have been in place for several years.
All of these companies want to help their customers achieve their business goals by using increasing levels of automation and intelligence. Paul Greenberg, managing principal at The 56 Group, who has written multiple books about the CRM industry, including CRM at the Speed of Light, says that while AI has been around for many years, it’s just now reaching a level of maturity to be of value for more businesses.
“The investments in the constant improvement of AI by companies like Oracle, Microsoft and Salesforce are substantial enough to both indicate that AI has become part of what they have to offer — not an optional [feature] — and that the demand is high for AI from companies that are large and complex to help them deal with varying needs at scale, as well as smaller companies who are using it to solve customer service issues or minimize service query responses with chatbots,” Greenberg explained.
This would suggest that injecting intelligence in applications can help even the playing field for companies of all sizes, allowing the smaller ones to behave like they were much larger, and for the larger ones to do more than they could before, all thanks to AI.
The machine learning side of the equation allows these algorithms to see patterns that would be hard for humans to pick out of the mountains of data being generated by companies of all sizes today. In fact, Greenberg says that AI has improved enough in recent years that it has gone from predictive to prescriptive, meaning it can suggest the prospect to call that is most likely to result in a sale, or the best combination of offers to construct a successful marketing campaign.
Brent Leary, principle at CRM Insights, says that AI, especially when voice is involved, can make software tools easier to use and increase engagement. “If sales professionals are able to use natural language to interact with CRM, as opposed to typing and clicking, that’s a huge barrier to adoption that begins to crumble. And making it easier and more efficient to use these apps should mean more data enters the system, which result in quicker, more relevant AI-driven insights,” he said.
All of this shows that AI has become an essential part of these software tools, which is why all of the major players in this space have built AI into their platforms. In an interview last year at the Adobe Summit, Adobe CTO Abhay Parasnis had this to say about AI: “AI will be the single most transformational force in technology,” he told TechCrunch. He appears to be right. It has certainly been transformative in sales, customer service and marketing.
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Landbot gets $2.2M for its on-message ‘anti-AI’ chatbot
Who needs AI to have a good conversation? Spanish startup Landbot has bagged a $2.2 million seed round for a ‘dumb’ chatbot that doesn’t use AI at all but offers something closer to an old school ‘choose your adventure’ interaction by using a conversational choice interface to engage potential customers when they land on a website.
The rampant popularity of consumer messaging apps has long been influencing product development decisions, and plenty of fusty business tools have been consumerized in recent years, including by having messaging-style interfaces applied to simplify all kinds of digital interactions.
In the case of Landbot, the team is deploying a familiar rich texting interface as a website navigation tool — meaning site visitors aren’t left to figure out where to click to find stuff on their own. Instead they’re pro-actively met with an interactive, adaptive messaging thread that uses conversational choice prompts to get them the information they need.
Call it a chatty twist on the ‘lazyweb’…
It’s also of course mobile first design, where constrained screen real estate is never very friendly to full fat homepages. Using a messaging thread interface plus marketing bots thus offers an alternative way to cut to the navigational chase, while simultaneously creaming off intent intelligence on potential customers. (Albeit it does risk getting old fast if your site visitors have a habit of clearing their cookies.)
Landbot, which was launched just over a year ago in June 2017, started as an internal experiment after its makers got frustrated by the vagaries of their own AI chatbots. So they had the idea to create a drag-and-drop style bot-builder that doesn’t require coding to support custom conversation flows.
“Since we already had a product, a business model, and some customers, we developed Landbot as an internal experiment. “What would happen with a full-screen conversation instead of the regular live-chat?,” we thought. What we got? A five times higher conversion rate on our homepage! Ever since, our whole strategy changed and Landbot, born from an experiment, became our core product,” explains CEO and co-founder Jiaqi Pan.
At the same time, the current crop of ‘cutting-edge’ AI chatbots are more often defined by their limitations than by having impressively expansive conversational capacities. Witness, for example, Google’s Duplex voice AI, heavily trained to perform very specific and pretty formulaic tasks — such as booking a hair appointment or a restaurant. Very few companies are in a position to burn so much engineering resource to try to make AI useful.
So there’s something rather elegant about eschewing the complexity and chaos of an AI engine (over)powering customer engagement tools — and just giving businesses user-friendly building blocks to create their own custom chat flows and channel site visitors through a few key flows.
After all, a small business knows its customers best. So a tool that helps SMEs create an engaging interface themselves, without having to plough resources they likely don’t have into training high maintenance chat AIs which are probably overkill for their needs anyway, seems a good and sensible thing.
Hence Pan talks about “democratizing the power of chatbots”. “Most landbot customers are marketing managers from small and medium companies that want to discover new ways of optimizing their conversion rates,” he tells us, saying that most are using the tool to convert more leads in their home/landing page; add dynamic surveys/forms to their websites; or explain their services — “in a more engaging way while scoring leads and being able to take over conversations when necessary”. (Buddy Nutrition is a Landbot customer, for example).
“We started our chatbot journey using Artificial Intelligence technology but found out that there was a huge gap between user expectations and reality. No matter how well trained our chatbots were, users were constantly dropped off the desired flow, which ended up in 20 different ways of saying “TALK WITH A HUMAN”,” he adds. “But we were in love with the conversational approach and, inspired by some great automation flow builders out there, we decided to give Conversational User Interfaces a try. Some would call them ‘dumb chatbots’.
“The results were amazing: The implementation process was way shorter, the technical background was removed from the equation and, finally, costs dropped too! Now, even companies with 100% focus on AI-based chatbots use Landbot as a truly cost-effective prototyping tool. We ended up creating the easiest and fastest chatbot builder out there. No technical knowledge, just a drag and drop interface and unlimited possibilities.”
Despite the startup-y hyperbole, the team does seem to have hit a sweet spot for their product. In less than a year since launching — via Product Hunt — Landbot has signed up more than 900 customers from 50+ countries, and is seeing a 30-40% MRR Growth MoM, according to Pan. Although they are offering a (branded) freemium version to help stoke the product’s growth, as well as paid tiers.
The $2.2M seed round is led by Nauta Capital, with Bankinter and Encomenda Smart Capital also participating. The plan for the funding is to grow headcount and pay for relocating Landbot’s head office from Valencia to Barcelona — to help with their international talent hunt as they look to triple the size of the team.
They’ll also be using the funding on their own brand marketing, rather than relying on viral growth — acknowledging that marketing spend is going to be important to stand out in such a crowded space, with thousands of competing solutions also vying for SMEs’ cash.
And, indeed, other conversational UIs out in the wild delivering a similarly chatty experience on the customer end, though Landbot’s claim is it’s differentiating in the market behind the scenes, with easy to use, ‘no coding necessary’ customization tools.
On the competition from, Pan names the likes of Chatfuel and Manychat as “powerful but channel-dependent” rival chatbot builders, while at the more powerful end he points to DialogFlow or IBM Watson but notes they do require technical knowledge, so the market positioning is different.
“Landbot tries to bring chatbots to the average Joe,” he adds. “While still keeping features for developers that demand complex functionalities in their chatbots (they can achieve by configuring webhooks, callbacks, CSS and JS customization).”
He also identifies players in the automated lead generation space — such as Intercom (Operator) and Drift (Drift bot) — saying they are aiming to transform sales and marketing processes “into something more conversational”. “The flow customization possibilities are fewer but the whole product is robust as they cover each stage of the conversion funnel, all the way to customer service,” he adds.
In terms of capabilities, Landbot also rubs up against survey/form offerings like SurveyMonkey and Google Form — or indeed Barcelona-based Typeform, which has raised around $50M since 2012 and bills itself as a platform for “conversational data collection”.
Pan rather delightfully characterizes Typeform as “bringing that conversational essence to the almighty sequences of fields”. Though he argues it’s also more limited “in terms of integrations and real-time human take-over capabilities”, i.e. as a consequence of wrangling those “almighty sequences”. So basically his argument is that Landbot isn’t saddled with Typeform’s form(ulaic) straightjacket. (Though Typeform would probably retort that its conversational platform is flexible.)
Still, where customer engagement is concerned, there’s never going to be one way. Sometimes the straight form will do it, but for another brand or use case something more colloquial might be called for.
Commenting on the seed round in a statement, Jordi Vinas, general partner at Nauta Capital, adds: “Landbot has experienced strong commercial traction and virality over the past months and the team has been able to attract customers from a variety of countries and verticals. We strongly believe in Jiaqi’s ability to continue scaling the business in a capital efficient way.”
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MeetFrank nets $1.1M for its passive job matching chatbot
MeetFrank, aka a ‘secret’ recruitment app that uses machine learning plus a chatbot wrapper to take the strain out of passive job hunting and talent-to-vacancy matching, has closed a €1 million (~$1.1M) seed funding round to fuel market expansion in Europe.
Hummingbird VC, Karma VC, and Change Ventures are the investors.
The Estonian startup was only founded last September but says it has ~125,000 active users in its first markets: Estonia, Finland, Sweden, Latvia, Lithuania, plus its most recent market addition, Germany, an expansion this seed has financed.
Around 2,000 companies are using the app to try to attract talent. In Germany employers on board with MeetFrank include Daimler, Eon, Delivery Hero, SumUp, Blinkist, High Mobility and MyTaxi.
“The average company profile we have at the moment is a start-up/scale-up company that develops their product in-house,” says co-founder Kaarel Holm.
“At the moment we are mainly focused on technology-related companies — so positions you can find from average start-up or a scale-up,” he tells TechCrunch. “Around 50% of the position are engineering and other 50% is marketing, sales, customer support, legal, data science, product/project management etc.”
He names TransferWise, Taxify, Testlio, Smartly and High-Mobility as other early customers.
Here’s how MeetFrank works on the talent side: The person downloads the app and goes through a relatively quick onboarding chat with ‘Frank’ (the emoji-loving chatbot) where they are asked to specify their skills and experience — choosing from pre-set lists, rather than needing to type — plus to state their current job title and salary.
So while MeetFrank’s target is passive job seekers, these people do still need to actively download the app and input some data.
Hence the chatbot having a strong emoji + GIF game to convince talent that a little upfront effort will go a long way…
The bot also asks what would convince them to switch jobs — offering options to choose from such as a higher salary, more flexible or remote working, relocation, a startup culture and so on.
The anonymous aspect comes in because there’s no requirement for users to provide their real name or any other identifying personal information in order to get matches with potential positions.
Talent is therefore assessed on its merits, at least at this stage of the job hunt.
And while people are asked up front to specify their current salary, which you might think puts them at a potential disadvantage during any pay negotiations, Holm says the aim of MeetFrank’s platform is also to encourage greater openness from employers and steer away from traditional pay negotiation situations.
“We use salary as one datapoint for matching and we try to make sure that offers we make to the user are match their preferences. In lot of cases the salary is the main deal breaker and we would like to present the information as early as possible,” he explains. “Companies on the other side of the marketplace disclose their salary for the users as well — in that case we can avoid the negotiating disadvantage.”
“The policy of MeetFrank platform is that companies have to be extremely open about the position they are trying to fill — this also includes the salary information,” he adds.
Employers are not at all anonymous on the platform. On the contrary, they have to write detailed job advertisements — including levels of pay for advertised roles.
And a pay range will be disclosed to applicants that the app deems potentially suitable — i.e. after its matching process — by displaying a percentage of how much more they could earn above their current salary.
So employers need to be comfortable showing their hand to people who may just be curious what’s out there.
For employers, MeetFrank takes over the ad placement process — using its machine learning to algorithmically match potential candidates to positions. So its proposition is automatic pre-selection across “thousands” of potential job applicants.
And also the possibility of reaching talent which might otherwise not realize that company is hiring. Or think about working for a certain brand.
The app is mainly focused on a “passive talent pool” — aka “currently or recently employed talent that is open for offers”, as Holm puts it. So it’s certainly cherrypicking easier types of jobs to match and fill.
“Entry level jobs is bit out of reach for us at the moment but we will launch a beta project with couple of universities in the autumn this year,” he adds when we ask if the app is open to matching people who don’t currently have a job or are looking for a first job.
Holm says MeetFrank is currently showing 50% MRR growth. It’s already out of the pre-revenue phase — so is charging employers to advertise (the service remains free for the talent side).
The main monetization model is a daily subscription, with employers being charged on a pay-as-you-go basis. Holm says the price per day for employers is €9, and MeetFrank lets them cancel at any time — with no minimum time commitment required to sign up.
“We believe that the new-aged classifieds will only monetize on that kind of on-demand model and should only pay when they find us useful. This also lowers the barrier of entry to most of the start-ups and allows them to vet the market and get visibility with low budgets,” he adds.
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Hugging Face raises $4 million for its artificial BFF
Chatbot startup Hugging Face has raised a $4 million seed round led by Ronny Conway from a_capital. Existing investors Betaworks, SV Angel and Kevin Durant are also participating.
I already reviewed Hugging Face so I won’t write the same thing again. But the startup has been building a chatbot app with a strong personality for bored teenagers. Instead of focusing on customer support or convenience, Hugging Face is focusing on emotions and entertainment.
It’s been available in the App Store as a standalone app and on Kik. Today, the company is also launching Hugging Face on Messenger. It should help bring new users.
Even without Messenger, Hugging Face now handles 1 million messages per day. In total, Hugging Face has received over 100 million messages.
It’s also worth noting that Hugging Face accepts text messages, photos, emojis, everything. So you can take a selfie, send a sad emoji, and the chatbot will know how you feel.
And it’s clear that Hugging Face is betting on surprise and enjoyment. The app doesn’t have to be perfect to be entertaining.
Beyond the consumer app, the team behind Hugging Face has written a couple of research papers about artificial intelligence. It’s clear that the startup plans on building a great team of engineers when it comes to natural language conversations. The team will double over the coming months.
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Microsoft acquires conversational AI startup Semantic Machines to help bots sound more lifelike
Microsoft announced today that it has acquired Semantic Machines, a Berkeley-based startup that wants to solve one of the biggest challenges in conversational AI: making chatbots sound more human and less like, well, bots.
In a blog post, Microsoft AI & Research chief technology officer David Ku wrote that “with the acquisition of Semantic Machines, we will establish a conversational AI center of excellence in Berkeley to push forward the boundaries of what is possible in language interfaces.”
According to Crunchbase, Semantic Machines was founded in 2014 and raised about $20.9 million in funding from investors, including General Catalyst and Bain Capital Ventures.
In a 2016 profile, co-founder and chief scientist Dan Klein told TechCrunch that “today’s dialog technology is mostly orthogonal. You want a conversational system to be contextual so when you interpret a sentence things don’t stand in isolation.” By focusing on memory, Semantic Machines claims its AI can produce conversations that not only answer or predict questions more accurately, but also flow naturally, something that Siri, Google Assistant, Alexa, Microsoft’s own Cortana and other virtual assistants still struggle to accomplish.
Instead of building its own consumer products, Semantic Machines focused on enterprise customers. This means it will fit in well with Microsoft’s conversational AI-based products. These include Microsoft Cognitive Services and Azure Bot Service, which the company says are used by one million and 300,000 developers, respectively, and its virtual assistants Cortana and Xiaolce.
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TechCrunch’s Messenger bot gets smarter and more conversational
We’ve teamed up with Chatfuel and Bitext to add Bitext’s NLP Middleware to the TechCrunch Messenger bot. This enhanced version adds functionality for conversational interaction, improved natural language understanding, and unique features like negation understanding. Lea’s live event assistant for Messenger makes buying tickets easier
Buying event tickets online isn’t a great experience. Sites like Ticketmaster are the default, but are difficult to use and expensive. A startup called Lea wants to offer a more modern experience by combining event search, discovery, seat selection and payment all in a single application that works right in Facebook Messenger. Read More
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Silent Echo lets you chat with Alexa over Slack
Want to chat with Alexa via Slack? A new bot called Silent Echo now makes that possible. The idea is that there are times when you want to interact with Amazon’s virtual assistant, Alexa, but you don’t want to do it by voice. For example, if things are too noisy in the room for Alexa to properly hear you, or, alternately, if you need things to be very quiet. The service… Read More
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Starbucks unveils a virtual assistant that takes your order via messaging or voice
Starbucks is embracing the trend towards voice-based computing with the launch of a new feature in its mobile app called My Starbucks barista, which allows customers to order and pay for their food and drinks just by speaking. This includes being able to modify their drink order, as if they were speaking with a barista in real life. Additionally, the company is launching a skill for the… Read More
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