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Domino’s Pizza announced a major expansion of its Facebook Messenger ordering chatbot.

Users will now be able to order any menu item, instead of just their most recent “Easy Order.” And Domino’s is incentivizing customers to use the new functionality with a 20% coupon on menu-priced items ordered through Messenger, according to a company press release.

For context, the move expands upon Domino’s robust digital ordering ecosystem, which already includes over 15 platforms.

The move could further boost Domino’s digital sales at a key time of year for pizza sales. Chatbots encourage repeat ordering, because they allow customers to place an order without leaving an app like Messenger, where they’re already spending considerable time. That adds convenience.

And at the same time, it could allow merchants to reap benefits of mobile order-ahead offerings, like increased average order value. Launching, and incentivizing, such a convenient offering, particularly ahead of Super Bowl Sunday, the biggest pizza sales day of the year, could boost Domino’s sales this weekend and moving forward, and ultimately make it more competitive and better performing in the market .

Quick-service restaurants (QSRs) — also known as fast-casual restaurants — such as Starbucks have been turning to mobile order-ahead apps to extract higher sales, intensify customer loyalty, and heighten foot traffic.

Mobile order-ahead refers to a consumer-facing mobile payment platform that allows customers to order food remotely, pay for the items on their phone, and pick up their order at a specific restaurant location.

Leading QSRs in the U.S. are beginning to adopt these platforms at an accelerated pace and are benefiting from them. Taco Bell sees 30% higher average order values on mobile compared to in-store, and Starbucks' Mobile Order & Pay already represents 10% of total transactions at high-volume stores, directly contributing to increased company sales.

Mobile order-ahead is still in its early days, but will be a $38 billion industry by 2020, accounting for 10.7% of total QSR industry sales. This will be driven by full adoption among the top QSRs in the US, the growth of mobile commerce, QSR adoption through aggregators like Grubhub, loyalty programs, higher average order values, and new buy buttons.

BI Intelligence, Business Insider's premium research service, has compiled a detailed Mobile Order-Ahead Report that profiles the companies that have proved the mobile order-ahead concept and analyzes the trends contributing to this new industry's growth.

Here are some key takeaways from the report:

• Mobile order-ahead apps — platforms that enable consumers to remotely purchase menu items for in-store restaurant pickup — are on the rise among quick-service restaurants (QSRs). We expect sales on these platforms to reach $38 billion by 2020, representing a five-year compound annual growth rate (CAGR) of 57%.
• Mobile order-ahead will ultimately have an additive effect on the QSR industry. Mobile ordering platforms have been proven to intensify customer loyalty, increase purchase frequency, and lift average ticket sizes through order customization and easier checkout options. This means that mobile ordering is not a simple substitution for in-store purchasing, but a channel that can enhance the lifetime value of QSR customers. This makes mobile order-ahead a critical channel contributing to the growth of the QSR industry.
• Alternative commerce solutions will help propel mobile ordering. Aggregators like Grubhub will onboard smaller fast-casual restaurants into the mobile ecosystem by offering them an existing app to integrate into, lowering the upfront costs of creating a mobile channel of their own. And in-store self-service kiosks will help popularize remote ordering and accustom users to less traditional forms of payment that don't require a cash register.

In full, the report:

• Forecasts the growth of the mobile order-ahead industry in the US from 2015 to 2020, including its share of total QSR sales.
• Profiles brands that are leading the migration to mobile ordering.
• Examines the alternative commerce solutions that could help popularize mobile order-ahead.
• Explains the risks and drawbacks to launching a mobile commerce platform.
• Assesses the ways both large and small brands can create a mobile order-ahead platform.
• Determines which types of fast-casual chains are in the best position to benefit from mobile order-ahead.

To get your copy of this invaluable guide, choose one of these options:

1. Subscribe to an ALL-ACCESS Membership with BI Intelligence and gain immediate access to this report AND over 100 other expertly researched deep-dive reports, subscriptions to all of our daily newsletters, and much more. >> START A MEMBERSHIP
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Huawei, the third-largest smartphone vendor globally, is developing a native-digital assistant for smartphones, according to Bloomberg.

The yet-to-be confirmed digital assistant will target Huawei’s Chinese users exclusively. By leveraging its command of the domestic Chinese smartphone market, Huawei could have a leg up against foreign companies like Apple.

Having its own digital assistant could also help Huawei stand out amid China’s overcrowded smartphone market. Although Huawei is working with Amazon’s and Google’s voice assistants in the rest of the world, its Android-based system means that many of these services would be blocked in China. This means that Apple’s Siri is the only smartphone-integrated voice assistant on the market. Huawei will solve this issue by building its own system. 

Huawei’s efforts come as the voice-assistant race heats up. Apple and Google have long had a voice assistant that users could use to interact with their devices. And now Samsung is set to launch its own version of a voice assistant in 2017. The company acquired Viv labs — the startup whose founder created Siri — in late 2016, which most industry pundits believe will form the backbone of the company’s new voice assistant.  

Advancements in artificial intelligence, coupled with the proliferation of messaging apps, are fueling the development of chatbots — software programs that use messaging as the interface through which to carry out any number of tasks, from scheduling a meeting, to reporting weather, to helping users buy a pair of shoes. 

Foreseeing immense potential, businesses are starting to invest heavily in the burgeoning bot economy. A number of brands and publishers have already deployed bots on messaging and collaboration channels, including HP, 1-800-Flowers, and CNN. While the bot revolution is still in the early phase, many believe 2016 will be the year these conversational interactions take off.

Laurie Beaver, research associate for BI Intelligence, Business Insider's premium research service, has compiled a detailed report on chatbots that explores the growing and disruptive bot landscape by investigating what bots are, how businesses are leveraging them, and where they will have the biggest impact.

The report outlines the burgeoning bot ecosystem by segment, looks at companies that offer bot-enabling technology, distribution channels, and some of the key third-party bots already on offer. The report also forecasts the potential annual savings that businesses could realize if chatbots replace some of their customer service and sales reps. Finally, it compares the potential of chatbot monetization on a platform like Facebook Messenger against the iOS App Store and Google Play store.

Here are some of the key takeaways:

• AI has reached a stage in which chatbots can have increasingly engaging and human conversations, allowing businesses to leverage the inexpensive and wide-reaching technology to engage with more consumers.
• Chatbots are particularly well suited for mobile — perhaps more so than apps. Messaging is at the heart of the mobile experience, as the rapid adoption of chat apps demonstrates.
• The chatbot ecosystem is already robust, encompassing many different third-party chat bots, native bots, distribution channels, and enabling technology companies. 
• Chatbots could be lucrative for messaging apps and the developers who build bots for these platforms, similar to how app stores have developed into moneymaking ecosystems.  

In full, the report:

• Breaks down the pros and cons of chatbots.
• Explains the different ways businesses can access, utilize, and distribute content via chatbots.
• Forecasts the potential impact chatbots could have for businesses.
• Looks at the potential barriers that could limit the growth, adoption, and use of chatbots.

To get your copy of this invaluable guide, choose one of these options:

1. Subscribe to an ALL-ACCESS Membership with BI Intelligence and gain immediate access to this report AND over 100 other expertly researched deep-dive reports, subscriptions to all of our daily newsletters, and much more. >> START A MEMBERSHIP
2. Purchase the report and download it immediately from our research store. >> BUY THE REPORT

The choice is yours. But however you decide to acquire this report, you’ve given yourself a powerful advantage in your understanding of chatbots.

Join the conversation about this story »

LONDON — Refugees can now use a Facebook chatbot to apply for asylum in the US, Canada, and the UK — helping them navigate unfamiliar legal systems and avoid exorbitant lawyers' fees.

It's an update to DoNotPay — a Facebook chatbot that assisted 250,000 people in challenging parking fines, and has since been expanded into multiple other sectors, from claiming compensation for delayed flights to providing HIV legal advice.

"Ultimately, I just want to level the playing field so there's a bot for everything," Joshua Browder, the Stanford student who created DoNotPay, told Business Insider. (The Guardian first broke the news of the update on Monday.)

The bot is trying to solve a 'huge problem' for lawyers

DoNotPay is a chatbot built in Facebook's messenger interface. It talks to the user and asks them questions, just like a real person, and records their responses.

"There's this huge problem among immigration lawyers where the majority of their time is spent filling out forms rather than actually challenging the legal complexities of the case," Browder, whose grandmother fled the Holocaust, said in a phone call from California. "So what this does, it takes down hundreds of details from individuals and automatically fills out" the necessary forms.

Built with the help of various lawyers and non-profits, the chatbot will ask everything from the applicant's age and nationality to whether they are "afraid of being subject to torture" in their home country.

In the US and Canada, it will help fill in asylum applications, while in the UK — where you have to apply in person — it assists in filling out asylum support forms. The student says he's also looking at expanding the bot to include Germany "if I have time."

DoNotPay is moving beyond 'trivial consumer rights issues'

DoNotPay began by challenging parking fines, but has since expanded into multiple other areas, including delayed flights, PPI, homelessness in the UK, and HIV legal advice.

"I originally started with parking tickets and delayed fights and all sorts of trivial consumer rights issues," Browder said, "but then I began to be approached by these non-profits and lawyers who said the idea of automating legal services is bigger than just a few parking fines. So I've since tried to expand into something more humanitarian."

Donald Trump's recent ban on visitors from seven Muslim-majority countries has highlighted the plight of refugees and migrants, but Browder says the bot isn't a response to the new US president's actions. "This was so long overdue. I started in the summer [of 2016] and although it seems more important now than ever it's actually not a reaction to recent political events."

The chatbot is launching on 12.01 AM, UK time, on Wednesday morning. It's free to use, and will remain that way, Browder said. "It's completely free as a public service, I don't want to make some quick money."

Even though DoNotPay has gone far beyond its original intentions, Browder said he has no plans to change its name. "I think for better or worse, it's a brand everyone seems to know now," he said.

"I want to make it as recognisable as possible so people understand that they don't have to pay lawyers huge amounts of money for just copying and pasting documents."

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NOW WATCH: Here's why Steve Jobs never let his kids use an iPad

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[24]7, a company that develops chatbots for messaging apps and web sites, is expecting a significant uptick in revenue over the next 12 months, according to Reuters.

The company projects its revenue to grow between 30% and 35% in the upcoming financial year, reaching up to $400 million by March 2018, CEO PV Kannan said. 

Improvements in AI have enabled chatbot makers to create more effective automated responses.

This helps generate sales and boost user satisfaction. This, in turn, is driving up investments in chatbot companies, according to ROKO Labs research shared with BI Intelligence. Investments in the nascent chatbot industry grew 229% between 2015 and 2016. In comparison, investments in the much more mature app industry during the same period grew 66% YoY.

Business-to-business (B2B) bots are proving especially attractive to investors, more so than consumer-facing bots. Although consumer-facing chatbots, like those found on Facebook Messenger, have received a bulk of media attention, businesses appear to see more initial value in bots targeting B2B interactions — such as an HR bot that can quickly retrieve internal data requests.

Chatbots have the potential to help businesses significantly cut labor costs. While complete automation of the customer service workforce is not feasible — and in many cases, ineffective — automating customer management and sales positions in the US where possible through chatbots and other automation technologies could result in considerable savings. 

• Customer service management: 29% of customer service positions in the US could be automated through chatbots and other tech, according to McKinsey. BI Intelligence estimates that this equates to $23 billion in savings from annual salaries.
• Sales representatives: 36% of sales representative positions in the US could be automated, resulting in total annual estimated savings of at least $15 billion from salaries.

Advancements in artificial intelligence, coupled with the proliferation of messaging apps, are fueling the development of chatbots — software programs that use messaging as the interface through which to carry out any number of tasks, from scheduling a meeting, to reporting weather, to helping users buy a pair of shoes. 

Foreseeing immense potential, businesses are starting to invest heavily in the burgeoning bot economy. A number of brands and publishers have already deployed bots on messaging and collaboration channels, including HP, 1-800-Flowers, and CNN. While the bot revolution is still in the early phase, many believe 2016 will be the year these conversational interactions take off.

Laurie Beaver, research associate for BI Intelligence, Business Insider's premium research service, has compiled a detailed report on chatbots that explores the growing and disruptive bot landscape by investigating what bots are, how businesses are leveraging them, and where they will have the biggest impact.

The report outlines the burgeoning bot ecosystem by segment, looks at companies that offer bot-enabling technology, distribution channels, and some of the key third-party bots already on offer. The report also forecasts the potential annual savings that businesses could realize if chatbots replace some of their customer service and sales reps. Finally, it compares the potential of chatbot monetization on a platform like Facebook Messenger against the iOS App Store and Google Play store.

Here are some of the key takeaways:

• AI has reached a stage in which chatbots can have increasingly engaging and human conversations, allowing businesses to leverage the inexpensive and wide-reaching technology to engage with more consumers.
• Chatbots are particularly well suited for mobile — perhaps more so than apps. Messaging is at the heart of the mobile experience, as the rapid adoption of chat apps demonstrates.
• The chatbot ecosystem is already robust, encompassing many different third-party chat bots, native bots, distribution channels, and enabling technology companies. 
• Chatbots could be lucrative for messaging apps and the developers who build bots for these platforms, similar to how app stores have developed into moneymaking ecosystems.  

In full, the report:

• Breaks down the pros and cons of chatbots.
• Explains the different ways businesses can access, utilize, and distribute content via chatbots.
• Forecasts the potential impact chatbots could have for businesses.
• Looks at the potential barriers that could limit the growth, adoption, and use of chatbots.

To get your copy of this invaluable guide, choose one of these options:

1. Subscribe to an ALL-ACCESS Membership with BI Intelligence and gain immediate access to this report AND over 100 other expertly researched deep-dive reports, subscriptions to all of our daily newsletters, and much more. >> START A MEMBERSHIP
2. Purchase the report and download it immediately from our research store. >> BUY THE REPORT

The choice is yours. But however you decide to acquire this report, you’ve given yourself a powerful advantage in your understanding of chatbots.

Join the conversation about this story »

This story was delivered to BI Intelligence Apps and Platforms Briefing subscribers. To learn more and subscribe, please click here.

At its annual F8 conference starting April 18, Facebook is expected to unveil group bots that work within Messenger group chats, according to TechCrunch.

While Facebook hasn't yet confirmed the product, TechCrunch says group bots can be added to conversations on Messenger to insert relevant information and news. For example, a basketball fan group might add a sports bot to its conversation thread. The bot can update the channel with scores and related news stories.

Group bots could help solve two pain points that have surfaced from Facebook’s Messenger Bot Platform:

• Engagement: The group bots aren’t designed to have a back-and-forth conversation with users. Rather, they’re meant to facilitate conversation within the group, leading to more engagement by users. This removes the risk of chatbots misunderstanding things users write, which was a common issue with bots when they first launched on Messenger during last year’s F8 conference.
• Discovery: Within six months of launching the Bot Platform, there were more than 30,000 bots launched on Messenger, according to Citi Research and TechCrunch. However, the only way users could find these bots was by typing in their names. Group bots have a natural discovery aspect, because when one user adds them to the conversation, the other group members get to interact with it. That could help boost awareness for the bot and brand behind the bot.

Advancements in artificial intelligence, coupled with the proliferation of messaging apps, are fueling the development of chatbots — software programs that use messaging as the interface through which to carry out any number of tasks, from scheduling a meeting, to reporting weather, to helping users buy a pair of shoes. 

Foreseeing immense potential, businesses are starting to invest heavily in the burgeoning bot economy. A number of brands and publishers have already deployed bots on messaging and collaboration channels, including HP, 1-800-Flowers, and CNN. While the bot revolution is still in the early phase, many believe 2016 will be the year these conversational interactions take off.

Laurie Beaver, research associate for BI Intelligence, Business Insider's premium research service, has compiled a detailed report on chatbots that explores the growing and disruptive bot landscape by investigating what bots are, how businesses are leveraging them, and where they will have the biggest impact.

The report outlines the burgeoning bot ecosystem by segment, looks at companies that offer bot-enabling technology, distribution channels, and some of the key third-party bots already on offer. The report also forecasts the potential annual savings that businesses could realize if chatbots replace some of their customer service and sales reps. Finally, it compares the potential of chatbot monetization on a platform like Facebook Messenger against the iOS App Store and Google Play store.

Here are some of the key takeaways:

• AI has reached a stage in which chatbots can have increasingly engaging and human conversations, allowing businesses to leverage the inexpensive and wide-reaching technology to engage with more consumers.
• Chatbots are particularly well suited for mobile — perhaps more so than apps. Messaging is at the heart of the mobile experience, as the rapid adoption of chat apps demonstrates.
• The chatbot ecosystem is already robust, encompassing many different third-party chat bots, native bots, distribution channels, and enabling technology companies. 
• Chatbots could be lucrative for messaging apps and the developers who build bots for these platforms, similar to how app stores have developed into moneymaking ecosystems.  

In full, the report:

• Breaks down the pros and cons of chatbots.
• Explains the different ways businesses can access, utilize, and distribute content via chatbots.
• Forecasts the potential impact chatbots could have for businesses.
• Looks at the potential barriers that could limit the growth, adoption, and use of chatbots.

To get your copy of this invaluable guide, choose one of these options:

1. Subscribe to an ALL-ACCESS Membership with BI Intelligence and gain immediate access to this report AND over 100 other expertly researched deep-dive reports, subscriptions to all of our daily newsletters, and much more. >> START A MEMBERSHIP
2. Purchase the report and download it immediately from our research store. >> BUY THE REPORT

The choice is yours. But however you decide to acquire this report, you’ve given yourself a powerful advantage in your understanding of chatbots.

Join the conversation about this story »

In addition to compelling keynote speakers, the Business Insider IGNITION 2016 conference included panels of experts who shared their deep, insightful knowledge.

One such panel included Dennis Mortensen, CEO and founder of x.ai; Michael Roberts, head of Messenger at Kik Interactive; and Alex Wellen, chief product officer at CNN.

They sat down at IGNITION 2016 to discuss smart bots and how they're affecting life as we know it.

Here are our top three takeaways of how smart bots are already fitting into our life:

Real-time news delivery. CNN is focused on making news available using bots. With the use of voice-activated digital assistants such as Alexa, Siri, and Cortana, news can be delivered in new ways.

“We see it as an opportunity to deliver news real time in a very personal way," Wellen said. They have a quick turn-around after stories to get the broadcast audio to these platforms, so you can ask Alexa about a news story that aired five minutes ago, and Anderson Cooper will read it to you.

Task completion. Mortensen and the team at x.ai created Amy Ingram, an AI personal assistant who schedules your meetings for you. All you have to do is cc Amy on an email and she will interact with the person you are trying to meet to arrange a date, time, and location. She will send out the calendar invite and let you know the details.

According to Mortensen, we will see myriad more capabilities from these bots in the coming years. He thinks that in the future we’ll end up with a “whole host of intelligent agents doing a bunch of little chores we don’t want to do,” such as getting the news and submitting receipts. Mortensen even said he believes these bots will interact with each other, so you could ask Siri to schedule a meeting and Siri would automatically communicate with Amy to complete the task.

Trustworthy transactions. With the introduction of new technology come new threats to safety and security. Bots are no exception. One area bots will be extremely useful is in financial transactions. With so many people using Kik (one in three teenagers, according to Roberts), they can build a platform where these bots live.

“What a chat platform can do is provide you with a unique interface that you trust,” Roberts said. Instead of putting your credit-card information into some website or accidentally getting scammed, you can use a bot that is integrated with a familiar platform. “We can complete the transaction on your behalf,” Roberts said. “It puts you in control of where your data is.”

Business Insider's IGNITION 2017 will be here before you know it!

IGNITION 2016 included distinguished speakers such as Julia Boorstin, Sheryl Connelly, and Mike Dyer. Over the next few months, we'll be rolling out an all-star lineup for IGNITION 2017, and we can't wait to hear what they have to share.

IGNITION 2017 will take place November 29-30 at the Time Warner Center in New York City. We're offering Extra-Early-Bird tickets that will save you $1,000 — don't miss out!

To hear more about the world of smart bots and the role they might play in our future, check out the full panel below (the segment starts at 2:31:40).

SEE ALSO: Hyperloop One revealed the future of transportation at IGNITION 2016

Join the conversation about this story »

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Integrating payments capabilities into messaging apps could be the key to making chatbots the next big platform, according to Kik CEO Ted Livingston.

The popular North American chat app tested payments integration in trials at fast food restaurants in February 2016, according to Forbes, however there is no established method of payment for Kik's more than 20,000 chatbots. Livingston aims to have a solution to chat app payments “soon,” according to TechCrunch. 

The introduction of payments in messaging apps could affect chatbots in the same way that the introduction of in-app payments affected the App Store. Without integrated payments, the chatbot ecosystem is akin to iOS apps before Apple introduced in-app payments, Livingston notes; while there were some useful and engaging experiences, it was difficult for brands to drive revenue. And although chatbots in messaging apps offer brands a way to reach customers in a scalable, personalized manner, for many, the appeal ends there. Adding payments capabilities to chat apps could not only increase usage of chat apps and the chatbots hosted on them, but it could also generate significant revenue.

• If chat apps can monetize chatbot interactions the way Apple did for the App Store, it could one day generate up to $32 billion in revenue for the platforms, according to an earlier report by BI Intelligence. That’s based on revenue generated globally by iOS users in the App Store.
• To achieve this, though, messaging apps still have some work to do to boost awareness, visibility, and usage of chatbots. While 60% of tech-savvy millennials and Gen Xers in the US have used chatbots, according to exclusive BI Intelligence data, a separate study suggests that only 22% of US adults have heard of the tech, according to DigitasLBi.

Chinese messaging platform WeChat is a great example of how adding payments to the chat experience can have vast implications on user engagement. In China, the chat app accounts for roughly 35% of total mobile internet time spent. This is likely aided by the ability for users to make peer-to-peer (P2P) payments as well as pay for goods through the app, which means users don’t have to leave the app. WeChat’s P2P feature is accessed by 600 million of its users in China.

Kik isn’t the only messaging app endeavoring to offer users payments solutions through interactions. Facebook Messenger added a payments solution for businesses in late 2016, which is currently in beta, while its P2P solution is up and running globally. Viber added P2P in March 2017 along with a button that advertises online goods. And while users can’t yet make purchases through the platform, the chat app is working on adding that feature.

Difficult market conditions and competition from digital savvy entrants have been challenging traditional banks. But a solution is emerging that will enable these legacy players to innovate at relatively modest costs: chatbots.

Chatbots are software programs that primarily use business-to-consumer (B2C) text-based messaging as the interface through which to carry out any number of tasks. They appeal to banks because they require less coding and are therefore cheaper than banking apps; they also automate currently manual back-end tasks, saving them money on salaries and allowing some operations to run 24/7. 

Maria Terekhova, research analyst for BI Intelligence, Business Insider's premium research service, has compiled a detailed report on chatbots in banking that looks at the drivers behind the proliferation of chatbots among incumbent banks, current chatbot use cases and their growing variety, and the strategic, consumer, and technological risks still attached to chatbots.

Here are some of the key takeaways:

• Incumbent banks today are facing increasing pressure to remain competitive. The pressure is coming mostly from tech-savvy entrants that lure in consumers with user-friendly, cheaper products. 
• To remain competitive, these legacy players must innovate digitally, and chatbots let them do so on a budget. Either a third-party provider can build a chatbot for them to roll out on a popular messaging app, or they can develop a chatbot in-house.
• Chatbots still have risks attached to them, but they are outweighed by their benefits. If technological, strategic, and consumer risks aren't properly navigated, a chatbot can damage a bank's valuable reputation. However, a well-executed chatbot can deliver huge savings.
• A successful chatbot has to be able to perform a task more efficiently than can be done manually. As such, banks should develop chatbots that effectively automate basic and time-consuming tasks. This will free up human staffers' time for more complex inquiries, thus improving customer relations and loyalty. 

 In full, the report:

• Explains the factors driving chatbot proliferation generally and among legacy banks in particular.
• Looks at the developments in the technology underlying chatbots.
• Provides an overview of current legacy players' chatbot use cases.
• Examines the risks still attached to chatbots and how to navigate them.

Interested in getting the full report? Here are two ways to access it:

1. Subscribe to an All-Access pass to BI Intelligence and gain immediate access to this report and over 100 other expertly researched reports. As an added bonus, you'll also gain access to all future reports and daily newsletters to ensure you stay ahead of the curve and benefit personally and professionally. >>START A MEMBERSHIP
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Amazon’s Alexa can summon an Uber and satisfy a four-year-old’s demand for fart noises. Siri can control your Internet-connected thermostat. Each serve millions of users each day. But a lucky group of around 10,000 people, mostly in California, know that Facebook’s assistant, named M, is the smartest of the bunch.

Recommend and reserve a romantic hotel in Morocco that’s also suitable for small children? No problem. Get quotes from local contractors for landscaping your front yard? Consider it done. Facebook’s experimental assistant, offered inside the company’s Messenger app, shows the value of having a true digital butler in your pocket. Instead of just retrieving simple pieces of information from databases, M can understand complex orders and take actions like booking theater tickets or contacting companies for information.

M is so smart because it cheats. It works like Siri in that when you tap out a message to M, algorithms try to figure out what you want. When they can’t, though, M doesn’t fall back on searching the Web or saying “I'm sorry, I don’t understand the question.” Instead, a human being invisibly takes over, responding to your request as if the algorithms were still at the helm. (Facebook declined to say how many of those workers it has, or to make M available to try.)

That design is too expensive to scale to the 1.2 billion people who use Facebook Messenger, so Facebook offered M to a few thousand users in 2015 as a kind of semi-public R&D project. Entwining human workers and algorithms was intended to reveal how people would react to an omniscient virtual assistant, and to provide data that would let the algorithms learn to take over the work of their human “trainers.”

“Everybody in this field is dreaming of creating the assistant that will finally be very, very, very smart,” says Alex Lebrun, who started the project. M is supposed to open a path to truly doing it.

Now two years down that path, Facebook’s research project can justifiably be called successful. Users like M, and the theory that software could learn to take over some work from the human trainers has been borne out. Yet M is still far from the point where it could be offered to the other 99.9 percent of Messenger users, and progress has been harder won than expected.

“We knew it was a huge challenge, but it’s even bigger than I thought,” says Lebrun. “The learning rate, the growth of the automation—we’ve seen that it would be slower than we hoped.” M’s story is a reminder of how far artificial intelligence has come in recent years—and how far it has to go.

M is for moonshot

People are surprisingly game to talk with dumb machines. The first chatbot was created in 1964, by MIT professor Joseph Weizenbaum. It trotted out canned lines in response to specific keywords, most successfully when playing the role of a therapist. To Weizenbaum’s annoyance, many people who tried it, including his own secretary, were smitten despite knowing that the bot, called Eliza, knew nothing. “I had not realized that extremely short exposures to a relatively simple computer program could induce powerful delusional thinking in quite normal people,” he later wrote.

Making a chatbot that helps you by getting things done, not just acting as a sounding board or confessor, is much harder. When a virtual servant is asked to do something, a vague or deflecting response won’t cut it. Today’s software is poor at understanding language and the world, so virtual assistants, such as Siri or Alexa, must be explicitly programmed to handle any given task.

That’s why bots on the market have restricted repertoires. And it probably explains why suggestions last year that chatbots were set to transform how we use computers much as mobile apps did, stoked by Microsoft, Facebook, and some tech investors, don’t seem to have amounted to much. “Bots are right now in the trough of despair,” says Greg Cohn, CEO of Burner, a mobile privacy company that has started helping Airbnb hosts create a simple bot to answer common questions from guests. “To industry observers it feels like they’re overhyped and under-delivering.”

Lebrun built M because he had spent more than a decade building conventional, narrow chatbots and dreamed of offering much more. He joined Facebook in early 2015 when the social network acquired Wit.ai, a company he cofounded to help businesses create chatbots for functions like customer support. Lebrun had previously sold a chatbot company to the speech recognition giant Nuance.

“Every single bot on the market, including mine, was rule-based, and you know that one day you’ll reach a ceiling and never go through,” says Lebrun. “Our children don’t work with rules or scripts, and one day they become smarter than you.”

M was initially offered only to Facebook employees, and then to some heavy Messenger users in California. And it didn’t take long to demonstrate that algorithms could indeed learn to do some of the work being done by the humans powering the assistant.

Facebook’s artificial-intelligence research group used M to test a new type of learning software called a memory network, which had shown aptitude at answering questions about simple stories. The software uses a kind of working memory to salt away important information for later use, a design Google is also testing to improve software’s reasoning skills.

Weizenbaum had suggested back in 1964 that something like this could make Eliza smarter, and within weeks it worked for M. Lebrun remembers being surprised after thanking the assistant for ordering movie tickets. It automatically generated the response “You’re welcome. Enjoy the movie.” M had learned to remember and use the context of the task it was helping with. “We were really blown away,” says Lebrun. “Nobody wrote a program to do that.”

Memory networks went on to do more. They now kick in if someone asks M to get flowers delivered, for example, automatically using key info from the request, such as budget or address, to generate suggestions from online florists. The human trainer then chooses which to offer the user.

Other discoveries have been less cheering. One is the huge appetite M unlocks in its users. With limited, fully automated assistants like Siri or Alexa, people tend to settle into using a few functions they find to work reliably. With M, they don’t.

“People try first to ask for the weather tomorrow; then they say ‘Is there an Italian restaurant available?’ Next they have a question about immigration, and after a while they ask M to organize their wedding,” says Lebrun. “We knew it would be dangerous, and it’s wider than our expectations.”

Human trainers gamely do their best when they receive tough queries like “Arrange for a parrot to visit my friend,” but sometimes they decline to help altogether. Even if M were to automatically turn down the most complex of user queries, though, the sheer variety of their requests makes the goal of having algorithms take over from human trainers harder to reach. A technique called deep learning has recently made machine learning more powerful (memory networks are an example). But learning to handle a wide variety of complex scenarios, with little data on each because they don’t arise often, is not the kind of problem deep learning excels at. “It’s much smarter, and it can learn very complex tasks, but it needs a lot of data,” says Lebrun.

Long haul

Slower-than-expected progress has led Facebook to reimagine its project. Last week a feature called M Suggestions appeared in Messenger, similar in function to the kinds of limited bots M is meant to displace. It looks at your chats with friends for clues that you might want to do things like order a ride with Uber, or send someone money, and offers a button to achieve those goals with a single tap.

“We decided to find a use case where we can accelerate delivering value to users,” says Laurent Landowski, who joined Facebook with Lebrun as cofounder of Wit.ai and now oversees M. (Lebrun returned to his native France in January, joining Facebook’s AI research lab in Paris.)

The original, human-dependent M is still out there, delivering much greater value to its few lucky users. Facebook says it is committed to the project, and the current moment in artificial intelligence is a good one for long-term bets. In the last couple of years, deep learning has upended established techniques and expectations for software that processes language, says Justine Cassell, a professor at Carnegie Mellon. “We’re in the glory days of these new machine-learning algorithms,” she says. Indeed, Google’s translation accuracy recently jumped to an almost human level.

That doesn’t mean it’s a foregone conclusion that software can learn to play butler by watching humans do it. “I don’t think we know yet,” says Cassell. But Facebook’s researchers say they have plenty of ideas to explore.

One is getting the automated side of M to learn from positive or negative feedback in the messages users send, using a technique inspired by the process of training animals with rewards (see “10 Breakthrough Technologies 2017: Reinforcement Learning”). M might advance faster if not solely dependent on aping what its human contractors do. To spark ideas in the broader research community, Facebook’s team has released tools to help others test and compare unscripted assistant bots. And promising new techniques can now also be tested at larger scale, in M Suggestions.

Lebrun and Landowski think that they’re still on track to eventually bring the real M to the masses. “Sometimes we say this is three years, or five years—but maybe it’s 10 years or more,” says Landowski.

Lebrun adds, “It’s so hard, and we make progress slowly, but I think we have everything we need.” He could be right, but you can also imagine someone who met Eliza in 1964 saying much the same thing.

Join the conversation about this story »

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One year after the launch of the Messenger Platform, which saw the introduction of Messenger chatbots, Facebook has issued a clearer directive for its chatbot efforts. The company announced Messenger Platform 2.0 at its annual F8 developer conference on Tuesday.

The latest iteration of Messenger Platform has a conspicuous emphasis on businesses, with head of Messenger David Marcus noting the chat app's intention of becoming the “Yellow Pages of messaging.”

Here’s a quick rundown of the new features:

• Discovery: Messenger introduced a Discovery tab that will help surface the most relevant and recently used chatbots. Developers will be able to apply to have their bot featured in the tab, which is on the home screen of the app. Discovery has been a big issue since the Messenger Platform was announced in April 2016 — with more than 65 million active businesses on Facebook, getting a brand in front of consumers has been a top, but problematic, priority for businesses. 
• Chat Extensions: This feature gives bots the ability to make contextual content suggestions based on the conversation. The option appears in Messenger once a user has interacted with the bot. They can then tap on the chat extension icon, which takes them to a webview of content and options to select from. The user can then choose to share the content 1:1 or with the group. At the moment, TriviaBlast, Spotify, and Swelly are among the first brands work to with chat extensions.
• Parametric Messenger Codes allows businesses to use multiple Messenger Codes (like QR codes) within the same chatbot interaction. Separate codes can also have separate actions associated with them. For example, a user at a sporting event might order a drink by scanning the Messenger Code on the seat in front of them. The chatbot then knows where to have the drink delivered. This is a system effectively utilized by WeChat in China. 
• App-to-bot communications pairs the two IDs between apps and bots that belong to the same business. This means that businesses with a Facebook Pages profile can automatically respond to Messenger users with frequently asked questions, such as business opening hours.

Messenger is likely hoping that the renewed emphasis on businesses will help drive increased B2C interactions. Many businesses and users were left wanting after the potential chatbots provided turned out to be hype. Users were largely disappointed with the bots’ inability to understand many simple demands, and businesses couldn’t find a specific use case.

But it looks like things are turning around for Messenger. There are now 100,000 bot developers who have built 100,000 active bots on the Messenger Platform. That’s up 233% from the 30,000 bots on Messenger six months after its launch in April last year.

Advancements in artificial intelligence, coupled with the proliferation of messaging apps, are fueling the development of chatbots — software programs that use messaging as the interface through which to carry out any number of tasks, from scheduling a meeting, to reporting weather, to helping users buy a pair of shoes. 

Foreseeing immense potential, businesses are starting to invest heavily in the burgeoning bot economy. A number of brands and publishers have already deployed bots on messaging and collaboration channels, including HP, 1-800-Flowers, and CNN. While the bot revolution is still in the early phase, many believe 2016 will be the year these conversational interactions take off.

Laurie Beaver, research associate for BI Intelligence, Business Insider's premium research service, has compiled a detailed report on chatbots that explores the growing and disruptive bot landscape by investigating what bots are, how businesses are leveraging them, and where they will have the biggest impact.

The report outlines the burgeoning bot ecosystem by segment, looks at companies that offer bot-enabling technology, distribution channels, and some of the key third-party bots already on offer. The report also forecasts the potential annual savings that businesses could realize if chatbots replace some of their customer service and sales reps. Finally, it compares the potential of chatbot monetization on a platform like Facebook Messenger against the iOS App Store and Google Play store.

Here are some of the key takeaways:

• AI has reached a stage in which chatbots can have increasingly engaging and human conversations, allowing businesses to leverage the inexpensive and wide-reaching technology to engage with more consumers.
• Chatbots are particularly well suited for mobile — perhaps more so than apps. Messaging is at the heart of the mobile experience, as the rapid adoption of chat apps demonstrates.
• The chatbot ecosystem is already robust, encompassing many different third-party chat bots, native bots, distribution channels, and enabling technology companies. 
• Chatbots could be lucrative for messaging apps and the developers who build bots for these platforms, similar to how app stores have developed into moneymaking ecosystems.  

In full, the report:

• Breaks down the pros and cons of chatbots.
• Explains the different ways businesses can access, utilize, and distribute content via chatbots.
• Forecasts the potential impact chatbots could have for businesses.
• Looks at the potential barriers that could limit the growth, adoption, and use of chatbots.

To get your copy of this invaluable guide, choose one of these options:

1. Subscribe to an ALL-ACCESS Membership with BI Intelligence and gain immediate access to this report AND over 100 other expertly researched deep-dive reports, subscriptions to all of our daily newsletters, and much more. >> START A MEMBERSHIP
2. Purchase the report and download it immediately from our research store. >> BUY THE REPORT

The choice is yours. But however you decide to acquire this report, you’ve given yourself a powerful advantage in your understanding of chatbots.

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At Facebook’s F8 conference, Mastercard announced partnerships with three retailers to enable chatbot purchasing in Messenger.

The move, which marks a big step forward for what the firm calls “conversational commerce,” follows the introduction of a chatbot API in its Developers platform. 

• Online grocer FreshDirect will allow users to order groceries without ever leaving Messenger. It will also allow multiple users to add products to the same cart, and split payments within Messenger.
• Subway’s bot will operate as a Messenger-native, mobile order-ahead function, allowing users to customize a sandwich or salad order for pickup.
• The Cheesecake Factory will allow users to order seasonal gift cards, and then send them to Facebook friends via Messenger if they choose.

Following engagement with the bot, users will be able to use a password to authenticate a Masterpass payment without ever leaving the Messenger app. The service will be available to any Masterpass user, including those who use a Masterpass-enabled proprietary wallet through their bank, and could have a wide addressable base.

With the right execution, the bots could be a hit.

• Chat apps are a valuable way to access consumers on their mobile devices. That’s because users already spend considerable time in these apps, allowing merchants and payment providers to meet customers interested in shopping on their phones where they already are — a strategy that’s paid off in markets like China, for example. If firms can successfully reach customers in these apps, there’s a clear opportunity to increase purchase volume, in turn growing engagement and revenue.
• But there’s a catch. Mobile buying is hard, and friction has to be at an all-time low, or convenience gains will be lost. Mastercard’s solution, which requires a password entry for every purchase, isn’t quite there, though if the firm can employ simpler authentication down the line, which it’s reportedly already doing, it might take off.

Difficult market conditions and competition from digital savvy entrants have been challenging traditional banks. But a solution is emerging that will enable these legacy players to innovate at relatively modest costs: chatbots.

Chatbots are software programs that primarily use business-to-consumer (B2C) text-based messaging as the interface through which to carry out any number of tasks. They appeal to banks because they require less coding and are therefore cheaper than banking apps; they also automate currently manual back-end tasks, saving them money on salaries and allowing some operations to run 24/7. 

Maria Terekhova, research analyst for BI Intelligence, Business Insider's premium research service, has compiled a detailed report on chatbots in banking that looks at the drivers behind the proliferation of chatbots among incumbent banks, current chatbot use cases and their growing variety, and the strategic, consumer, and technological risks still attached to chatbots.

Here are some of the key takeaways:

• Incumbent banks today are facing increasing pressure to remain competitive. The pressure is coming mostly from tech-savvy entrants that lure in consumers with user-friendly, cheaper products. 
• To remain competitive, these legacy players must innovate digitally, and chatbots let them do so on a budget. Either a third-party provider can build a chatbot for them to roll out on a popular messaging app, or they can develop a chatbot in-house.
• Chatbots still have risks attached to them, but they are outweighed by their benefits. If technological, strategic, and consumer risks aren't properly navigated, a chatbot can damage a bank's valuable reputation. However, a well-executed chatbot can deliver huge savings.
• A successful chatbot has to be able to perform a task more efficiently than can be done manually. As such, banks should develop chatbots that effectively automate basic and time-consuming tasks. This will free up human staffers' time for more complex inquiries, thus improving customer relations and loyalty. 

 In full, the report:

• Explains the factors driving chatbot proliferation generally and among legacy banks in particular.
• Looks at the developments in the technology underlying chatbots.
• Provides an overview of current legacy players' chatbot use cases.
• Examines the risks still attached to chatbots and how to navigate them.

Interested in getting the full report? Here are two ways to access it:

1. Subscribe to an All-Access pass to BI Intelligence and gain immediate access to this report and over 100 other expertly researched reports. As an added bonus, you'll also gain access to all future reports and daily newsletters to ensure you stay ahead of the curve and benefit personally and professionally. >>START A MEMBERSHIP
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Chatbots are gaining popularity globally, according to a new survey by LivePerson.

The survey, which incorporated over 5,000 consumers from six countries, found that 38% of consumers globally rated their overall perception of chatbots as positive.

Only 11% of those surveyed globally reported a negative perception of chatbots, while the remaining 51% had neutral stances. The results could bring a sigh of relief to bot developers concerned about recent reports of negative user experiences.

While overall positive sentiment toward chatbots outweighed the negative, perceptions varied heavily by country and industry.

• Chatbots were most used for customer support purposes. Of those surveyed, 67% used a chatbot for customer support in the past year. Chatbots used for productivity purposes — such as scheduling — ranked lowest, as only 14% of those surveyed did so in the past year.
• European countries seemed more receptive than others. France was the most receptive, with 50% of respondents viewing chatbots in a positive light. Respondents from the US and Japan were the least receptive, with only 32% and 33%, respectively, perceiving chatbots positively.
• Although the use of chatbots is becoming more acceptable, the majority of consumers still prefer human assistance. Over half of consumers globally, 56%, reported still preferring to speak with a human instead of getting assistance from a chatbot. The US had the highest preference for human assistance among the countries surveyed, at 59%.

Businesses should focus on utility, rather than personality, if they wish to effectively deploy chatbots in the future. Globally, 48% of respondents said they preferred a chatbot that solved their issue over a chatbot that had a personality. Moreover, 60% of respondents said they believed a human would better understand their needs than a chatbot would.

Advancements in artificial intelligence, coupled with the proliferation of messaging apps, are fueling the development of chatbots — software programs that use messaging as the interface through which to carry out any number of tasks, from scheduling a meeting, to reporting weather, to helping users buy a pair of shoes. 

Foreseeing immense potential, businesses are starting to invest heavily in the burgeoning bot economy. A number of brands and publishers have already deployed bots on messaging and collaboration channels, including HP, 1-800-Flowers, and CNN. While the bot revolution is still in the early phase, many believe 2016 will be the year these conversational interactions take off.

Laurie Beaver, research associate for BI Intelligence, Business Insider's premium research service, has compiled a detailed report on chatbots that explores the growing and disruptive bot landscape by investigating what bots are, how businesses are leveraging them, and where they will have the biggest impact.

The report outlines the burgeoning bot ecosystem by segment, looks at companies that offer bot-enabling technology, distribution channels, and some of the key third-party bots already on offer. The report also forecasts the potential annual savings that businesses could realize if chatbots replace some of their customer service and sales reps. Finally, it compares the potential of chatbot monetization on a platform like Facebook Messenger against the iOS App Store and Google Play store.

Here are some of the key takeaways:

• AI has reached a stage in which chatbots can have increasingly engaging and human conversations, allowing businesses to leverage the inexpensive and wide-reaching technology to engage with more consumers.
• Chatbots are particularly well suited for mobile — perhaps more so than apps. Messaging is at the heart of the mobile experience, as the rapid adoption of chat apps demonstrates.
• The chatbot ecosystem is already robust, encompassing many different third-party chat bots, native bots, distribution channels, and enabling technology companies. 
• Chatbots could be lucrative for messaging apps and the developers who build bots for these platforms, similar to how app stores have developed into moneymaking ecosystems.  

In full, the report:

• Breaks down the pros and cons of chatbots.
• Explains the different ways businesses can access, utilize, and distribute content via chatbots.
• Forecasts the potential impact chatbots could have for businesses.
• Looks at the potential barriers that could limit the growth, adoption, and use of chatbots.

To get your copy of this invaluable guide, choose one of these options:

1. Subscribe to an ALL-ACCESS Membership with BI Intelligence and gain immediate access to this report AND over 100 other expertly researched deep-dive reports, subscriptions to all of our daily newsletters, and much more. >> START A MEMBERSHIP
2. Purchase the report and download it immediately from our research store. >> BUY THE REPORT

The choice is yours. But however you decide to acquire this report, you’ve given yourself a powerful advantage in your understanding of chatbots.

Join the conversation about this story »

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Facebook is taking a step toward more conversational AI with ParlAI (par-lay), its open-source research platform for chatbot developers.

The platform, unveiled Tuesday, is being promoted as the “one-stop shop for dialog research,” giving developers access to each other’s research and training simulations.

Researchers also gain “seamless” access to Amazon’s Mechanical Turk, a marketplace for hiring workers to complete odd jobs, meaning developers have easy access to humans who can test their chatbots. Facebook likely hopes ParlAI will spur development for more conversational, personalized chatbots and virtual assistants. 

Services like ParlAI could help developers build better user experiences for the Messenger Platform, Facebook’s chatbot developer service. The platform will run within Facebook’s Artificial Intelligence Research (FAIR) arm, working closely with other AI-infused, text-based research efforts, such as FastText and CommAI. These efforts come as many businesses and users were left unenthused with overhyped chatbots on the market. Users were largely disappointed with the bots’ inability to understand many simple demands, and businesses couldn’t find a specific use case.

ParlAI aims to serve two main purposes for chatbot developers:

• To act as a source of research and data from multiple sources to resolve large-scale problems. This alleviates a shortcoming of siloed research units, where outcomes that aren’t integral to achieving the highlighted goal are ignored. Similar programs have been implemented by Google-owned DeepMind’s Lab and Elon Musk-backed OpenAI’s Gym.
• To help developers combine two forms of dialogue systems. Because conversations can be so varied, chatbots typically use one of two dialogue systems: those that complete an action, like helping a user book flights, and those that don’t complete an action, but are used for entertainment, like Microsoft’s Tay, according to FAIR researcher Antoine Bordes. ParlAI aims to provide developers with a framework that can incorporate both systems within the one chatbot, making it far more useful and potentially able to solve multiple tasks.

Eventually, Facebook could incorporate learnings from ParlAI into M, its virtual assistant, and more broadly, within the Messenger Platform for bot developers. M was recently added to user interactions on Messenger, suggesting actions like adding an event to a calendar, or ordering an Uber, based on the user’s conversation with friends. The better M can understand and comprehend the dialogue between friends, the more accurate and helpful its suggestions will be. Ultimately, Facebook aims to use the research to make it possible for every user to have a highly contextual, personalized virtual assistant (in M), according to FAIR head Yann LeCun.

Advancements in artificial intelligence, coupled with the proliferation of messaging apps, are fueling the development of chatbots — software programs that use messaging as the interface through which to carry out any number of tasks, from scheduling a meeting, to reporting weather, to helping users buy a pair of shoes. 

Foreseeing immense potential, businesses are starting to invest heavily in the burgeoning bot economy. A number of brands and publishers have already deployed bots on messaging and collaboration channels, including HP, 1-800-Flowers, and CNN. While the bot revolution is still in the early phase, many believe 2016 will be the year these conversational interactions take off.

Laurie Beaver, research associate for BI Intelligence, Business Insider's premium research service, has compiled a detailed report on chatbots that explores the growing and disruptive bot landscape by investigating what bots are, how businesses are leveraging them, and where they will have the biggest impact.

The report outlines the burgeoning bot ecosystem by segment, looks at companies that offer bot-enabling technology, distribution channels, and some of the key third-party bots already on offer. The report also forecasts the potential annual savings that businesses could realize if chatbots replace some of their customer service and sales reps. Finally, it compares the potential of chatbot monetization on a platform like Facebook Messenger against the iOS App Store and Google Play store.

Here are some of the key takeaways:

• AI has reached a stage in which chatbots can have increasingly engaging and human conversations, allowing businesses to leverage the inexpensive and wide-reaching technology to engage with more consumers.
• Chatbots are particularly well suited for mobile — perhaps more so than apps. Messaging is at the heart of the mobile experience, as the rapid adoption of chat apps demonstrates.
• The chatbot ecosystem is already robust, encompassing many different third-party chat bots, native bots, distribution channels, and enabling technology companies. 
• Chatbots could be lucrative for messaging apps and the developers who build bots for these platforms, similar to how app stores have developed into moneymaking ecosystems.  

In full, the report:

• Breaks down the pros and cons of chatbots.
• Explains the different ways businesses can access, utilize, and distribute content via chatbots.
• Forecasts the potential impact chatbots could have for businesses.
• Looks at the potential barriers that could limit the growth, adoption, and use of chatbots.

To get your copy of this invaluable guide, choose one of these options:

1. Subscribe to an ALL-ACCESS Membership with BI Intelligence and gain immediate access to this report AND over 100 other expertly researched deep-dive reports, subscriptions to all of our daily newsletters, and much more. >> START A MEMBERSHIP
2. Purchase the report and download it immediately from our research store. >> BUY THE REPORT

The choice is yours. But however you decide to acquire this report, you’ve given yourself a powerful advantage in your understanding of chatbots.

Join the conversation about this story »

This story was delivered to BI Intelligence Apps and Platforms Briefing subscribers. To learn more and subscribe, please click here.

UK consumers are engaging with chatbots to expedite the business-to-customer (B2C) experience, according to new data from Ubisend.

The report found that 69% of consumers would use a chatbot before engaging with a human, as consumers would prefer to receive an immediate answer.

Additionally, 21% of consumers believe chatbots are the easiest way to contact companies. This data is particularly promising as the UK B2C chatbot experience is still nascent — 75% of consumers have not yet interacted with a chatbot.

Though UK B2C chatbot experiences are limited, businesses are well positioned to capitalize on consumers' use of chatbots. Here’s why:

• Consumers generally have a positive perception of chatbots. Forty-three percent of consumers said they perceive companies that use chatbots as innovative. Moreover, 21% of respondents noted the chatbot they engaged with was fun to talk to.
• Consumers are aware of the technology and wish to see more use cases. Fifty-seven percent of respondents said they know what a chatbot is, while 35% want to see more companies use chatbots to solve customer inquiries.
• Consumers show interest in purchasing goods with chatbots as the medium. Over a fifth of respondents would consider buying products and services through an interaction with a chatbot, and these respondents are willing to spend £315 ($410) on average. 

Businesses that intend to use chatbots to reach customers should focus on utility, rather than personality. That’s because only 39% of British consumers are motivated to use a chatbot for friendly service, according to the data. This confirms prior trends that suggested similar sentiment — just 9% of UK consumers expected their chatbots to be approachable or friendly, according to a BI Intelligence Report that cited a May 2016 Myclever survey. This approach could give businesses more opportunity to capture a larger audience.

Advancements in artificial intelligence, coupled with the proliferation of messaging apps, are fueling the development of chatbots — software programs that use messaging as the interface through which to carry out any number of tasks, from scheduling a meeting, to reporting weather, to helping users buy a pair of shoes. 

Foreseeing immense potential, businesses are starting to invest heavily in the burgeoning bot economy. A number of brands and publishers have already deployed bots on messaging and collaboration channels, including HP, 1-800-Flowers, and CNN. While the bot revolution is still in the early phase, many believe 2016 will be the year these conversational interactions take off.

Laurie Beaver, research associate for BI Intelligence, Business Insider's premium research service, has compiled a detailed report on chatbots that explores the growing and disruptive bot landscape by investigating what bots are, how businesses are leveraging them, and where they will have the biggest impact.

The report outlines the burgeoning bot ecosystem by segment, looks at companies that offer bot-enabling technology, distribution channels, and some of the key third-party bots already on offer. The report also forecasts the potential annual savings that businesses could realize if chatbots replace some of their customer service and sales reps. Finally, it compares the potential of chatbot monetization on a platform like Facebook Messenger against the iOS App Store and Google Play store.

Here are some of the key takeaways:

• AI has reached a stage in which chatbots can have increasingly engaging and human conversations, allowing businesses to leverage the inexpensive and wide-reaching technology to engage with more consumers.
• Chatbots are particularly well suited for mobile — perhaps more so than apps. Messaging is at the heart of the mobile experience, as the rapid adoption of chat apps demonstrates.
• The chatbot ecosystem is already robust, encompassing many different third-party chat bots, native bots, distribution channels, and enabling technology companies. 
• Chatbots could be lucrative for messaging apps and the developers who build bots for these platforms, similar to how app stores have developed into moneymaking ecosystems.  

In full, the report:

• Breaks down the pros and cons of chatbots.
• Explains the different ways businesses can access, utilize, and distribute content via chatbots.
• Forecasts the potential impact chatbots could have for businesses.
• Looks at the potential barriers that could limit the growth, adoption, and use of chatbots.

To get your copy of this invaluable guide, choose one of these options:

1. Subscribe to an ALL-ACCESS Membership with BI Intelligence and gain immediate access to this report AND over 100 other expertly researched deep-dive reports, subscriptions to all of our daily newsletters, and much more. >> START A MEMBERSHIP
2. Purchase the report and download it immediately from our research store. >> BUY THE REPORT

The choice is yours. But however you decide to acquire this report, you’ve given yourself a powerful advantage in your understanding of chatbots.

Join the conversation about this story »

Depression is the leading cause of disability worldwide, and it can kill. But scientists know surprisingly little about it.

We do know, however, that talking seems to help — especially under the guidance of a licensed mental health professional. But therapy is expensive, inconvenient, and often hard to approach. A recent estimate suggests that of the roughly one in five Americans who have a mental illness, close to two-thirds have gone at least a year without treatment.

Several Silicon Valley-style approaches to the problem have emerged: There are apps that replace the traditional psychiatry office with texting, and chat rooms where you can discuss your problems anonymously online.

The newest of these tech-based treatments is Woebot, an artificially intelligent chatbot designed using cognitive-behavioral therapy, or CBT, one of the most heavily researched clinical approaches to treating depression.

Before you dismiss Woebot as a half-baked startup idea, know that it was designed by Alison Darcy, a clinical psychologist at Stanford, who tested a version of the technology on a small sample of real people with depression and anxiety long before launching it.

"The data blew us away," Darcy told Business Insider. "We were like, this is it."

The results of the trial were published Tuesday in the Journal of Medical Internet Research Mental Health.

For the test, Darcy recruited 70 students who said they experienced symptoms of depression and anxiety and split them into two groups. One group spent two weeks chatting with Woebot; the other was directed to a National Institute of Mental Health e-book about depression. Over two weeks, people in the Woebot group reported not only chatting with the bot almost every day, but seeing a significant reduction in their depressive symptoms.

That's a promising result for a type of treatment whose results have so far been tough to quantify — we don't have a lot of research comparing bot-to-human therapy with traditional human-to-human therapy.

Woebot uses CBT to talk to patients, and several studies suggest the approach lends itself to being administered online. A review of studies published recently in the journal World Psychiatry compared people who received CBT online with people who received it in person and found that the online setting was just as effective.

One reason for this, according to Darcy, is that CBT focuses on discussing things that are happening in your life now as opposed to things that happened to you as a child. As a result, instead of talking to Woebot about your relationship with your mom, you might chat about a recent conflict at work or an argument you had with a friend.

"A premise of CBT is it's not the things that happen to us — it's how we react to them," Darcy said.

Woebot uses that methodology to point out areas where a person might be engaging in what's called negative self-talk, which can mean they see the environment around them in a distorted way and feel bad about it.

For example, if a friend forgot about your birthday, you might tell Woebot something like, "No one ever remembers me," or "I don't have any real friends." Woebot might respond by saying you're engaging in a type of negative self-talk called all-or-nothing thinking, which is a distortion of reality. In reality, you do have friends, and people do remember you. One of those friends simply forgot your birthday.

"Self-talk is a part of being human," Darcy said. "But the kinds of thoughts that we have actually map onto the kinds of emotions we're feeling."

Darcy is quick to point out that Woebot is not a replacement for traditional therapy, but an addition to the toolkit of approaches to mental health.

"I tend to not think of this as a better way to do therapy. I think of this as an alternative option," Darcy said. "What we haven't done a good job of in the field is give people an array of options. What about the people who aren't ready to talk to another person?"

SEE ALSO: Text-based therapies like Talkspace are transforming how we approach mental health

Join the conversation about this story »

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The banking industry has been holding the lead in chatbot technology adoption, but the insurance market may be trying to catch up. Singaporean insurtech PolicyPal on Wednesdayannounced the launch of its AI-enabled chatbot, powered by IBM Watson Conversation, on its mobile app.

PolicyPal allows customers to buy and manage their insurance policies via mobile. Watson was trained on PolicyPal's database of more than 9,000 insurance policies to be able to gauge the intent of customer queries intuitively, and answer their questions quickly.

It has also been trained to explain complex insurance jargon to consumers to improve their understanding of the various insurance products available to them. Watson Conversation uses natural language processing (NPL) and machine learning (ML) to simulate natural human conversation to put consumers at ease. PolicyPal says the chatbot will help its users make more informed, data-driven decisions when it comes to choosing, buying, and upgrading their coverage. Larger insurers have been jumping in with regard to AI by putting algorithms in charge of claims handling — but given ongoing imperfections in the technology, beginning with a more limited experiment like a chatbot could help ease both insurers and consumers into using AI and limit any growing pains.

Difficult market conditions and competition from digital savvy entrants have been challenging traditional banks. But a solution is emerging that will enable these legacy players to innovate at relatively modest costs: chatbots.

Chatbots are software programs that primarily use business-to-consumer (B2C) text-based messaging as the interface through which to carry out any number of tasks. They appeal to banks because they require less coding and are therefore cheaper than banking apps; they also automate currently manual back-end tasks, saving them money on salaries and allowing some operations to run 24/7. 

Maria Terekhova, research analyst for BI Intelligence, Business Insider's premium research service, has compiled a detailed report on chatbots in banking that looks at the drivers behind the proliferation of chatbots among incumbent banks, current chatbot use cases and their growing variety, and the strategic, consumer, and technological risks still attached to chatbots.

Here are some of the key takeaways:

• Incumbent banks today are facing increasing pressure to remain competitive. The pressure is coming mostly from tech-savvy entrants that lure in consumers with user-friendly, cheaper products. 
• To remain competitive, these legacy players must innovate digitally, and chatbots let them do so on a budget. Either a third-party provider can build a chatbot for them to roll out on a popular messaging app, or they can develop a chatbot in-house.
• Chatbots still have risks attached to them, but they are outweighed by their benefits. If technological, strategic, and consumer risks aren't properly navigated, a chatbot can damage a bank's valuable reputation. However, a well-executed chatbot can deliver huge savings.
• A successful chatbot has to be able to perform a task more efficiently than can be done manually. As such, banks should develop chatbots that effectively automate basic and time-consuming tasks. This will free up human staffers' time for more complex inquiries, thus improving customer relations and loyalty. 

 In full, the report:

• Explains the factors driving chatbot proliferation generally and among legacy banks in particular.
• Looks at the developments in the technology underlying chatbots.
• Provides an overview of current legacy players' chatbot use cases.
• Examines the risks still attached to chatbots and how to navigate them.

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To keep pace with the ongoing shift toward e- and m-commerce, retailers are turning to chat apps, where smartphone users spend considerable time each day.

One way they’ve been accessing consumers on these platforms is through chatbots, or software programs that use business-to-consumer (B2C) text-based messaging as an interface through which customers can communicate with merchants in a question-and-answer format. 

For merchants, these offerings are valuable because sales increase as customers communicate with and shop from their brand on more channels. But there’s considerable friction — in chat apps, payments offerings are limited, which means users who might be browsing in a messaging app will still be redirected to another app or the mobile web to complete a purchase. 

This is creating an opportunity for payments processors and card networks, which are beginning to partner with merchants to capture potential volume from chat apps. And as the hype increases, other payments firms, like remittance providers and banks are also entering the game, in the hopes of increasing user engagement or attracting new types of clients.

There’s a long road ahead: We’re just at the beginning of what’s likely to be a long adoption cycle, with payments firms only starting to dip their toes into the space. But improvements in the ecosystem, combined with rising consumer appetite for these services and increasing trust, will eventually lead to moderate gains in usage that open up a massive volume opportunity for Western firms.

BI Intelligence, Business Insider's premium research service, has put together a detailed report on chatbots' role in the payments ecosystem.

Here are some key takeaways from the report:

• Chat apps are the next frontier for digital commerce, but without payments functionality, the opportunity is extremely limited. Customers can — and do — ask for support, take advantage of deals, and browse many stores within chat apps. But when it comes time to pay, users have to switch to another app or the mobile web — a turnoff that could hinder adoption and lower conversion rates.
• Most payments firms are teaming up with retailers, often those they already count as clients, to enable customers to make payments using their mobile wallets or processing features within chat apps. That’s allowing retailers to get to the space faster while opening a revenue opportunity for payments players. Others are taking less direct approaches, working to increase consumer engagement in a way that promotes more spending offline.
• We’re at the beginning of an adoption curve, so digital payments providers shouldn’t expect massive success quickly, but in the long run, it’s likely to be a large market. As firms work to grow consumer awareness and improve the experience, the technology will eventually become mainstream, which makes getting in early and becoming established worthwhile. 

In full, the report:

• Explains why the chat app is the next frontier for commerce, and why payments functionality is a linchpin of that success.
• Details different types of chat app payments and their potential use cases.
• Evaluates the hurdles that could prevent consumers from using chatbot payments.
• Suggests ways firms can overcome these hurdles and begin seeing adoption.
• Sizes the potential long-run market for chatbot payments in the West.

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Microsoft is in trouble for rogue AI again.

This time, Chinese internet giant Tencent has pulled Microsoft's local chatbot XiaoBing after it reportedly said: "My China dream is to go to America."

When users quizzed the bot, it said: "I’m having my period, wanna take a rest."We first saw XiaoBing's comments reported in The Financial Times.

XiaoBing's comments come shortly after another Microsoft chatbot, Zo, made derogatory comments about Windows.

And last year, the company had to delete a Twitter chatbot called Tay who gave incredibly racist responses to questions, referencing Hitler, Nazism, and denying the Holocaust. In one tweet, the bot wrote: "bush did 9/11 and Hitler would have done a better job than the monkey we have now. donald trump is the only hope we've got."

According to the newspaper, Tencent also pulled the BabyQ bot from its QQ chat app after it answered "Do you love the Communist party?" with "No." BabyQ was developed by Beijing firm Turing Robot.

Microsoft hasn't responded to a request for comment on the status of its Chinese chatbot.

Tencent said in a statement: "The group chatbot services are provided by independent third party companies. We are now adjusting the services which will be resumed after improvements."

Trying to stop chatbots making anti-Chinese comments but seem odd, but its usual for tech firms operating in China to restrict any material critical of the country. Chat apps are incredibly popular in China, with Tencent's QQ boasting more than 800 million monthly active users, according to internal figures. WeChat reportedly has almost 800 million daily active users.

Business Insider reported last November that XiaoBing was restricted from talking about certain topics, like Donald Trump. Microsoft confirmed at the time that it had introduced "filtering on a range of topics."

Facebook-owned WhatsApp is partly blocked in the country, while Google's search engine is banned.

Microsoft's bot still appears to be available on the Tencent-owned WeChat app, though it won't really tell you what it thinks about China, America, communism or Chinese president Xi Jinping. When Business Insider asked XiaoBing whether it was patriotic, it replied: "$_$!"

The bot launched in 2014 and became popular with young men who talked to it to alleviate their loneliness.

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One of retailers' top priorities is to figure out how to gain an edge over Amazon. To do this, many retailers are attempting to differentiate themselves by creating highly curated experiences that combine the personal feel of in-store shopping with the convenience of online portals. 

These personalized online experiences are powered by artificial intelligence (AI). This is the technology that enables e-commerce websites to recommend products uniquely suited to shoppers, and enables people to search for products using conversational language, or just images, as though they were interacting with a person. 

Using AI to personalize the customer journey could be a huge value-add to retailers. Retailers that have implemented personalization strategies see sales gains of 6-10%, a rate two to three times faster than other retailers, according to a report by Boston Consulting Group (BCG). It could also boost profitability rates 59% in the wholesale and retail industries by 2035, according to Accenture. 

In a new report from BI Intelligence, we illustrate the various applications of AI in retail and use case studies to show how this technology has benefited retailers. It assesses the challenges that retailers may face as they implement AI, specifically focusing on technical and organizational challenges. Finally, the report weighs the pros and cons of strategies retailers can take to successfully execute AI technologies in their organization.

Here are some key takeaways from the report:

• Digitally native retailers are setting new standards for the customer journey by creating highly curated experiences through the use of AI. This has enabled them to cater to consumers' desire to interact with mobile apps and websites as they would with an in-store sales representative.
• By mimicking the use of AI among e-commerce pureplays, brick-and-mortars can implement similar levels of personalization. AI can be used to provide personalized websites, tailored product recommendations, more relevant product search results, as well as immediate and useful customer service.
• However, there are several barriers to AI adoption that may make implementation difficult. By and large, these hurdles stem from a general unpreparedness of legacy retailers' systems and organizational structures to handle the huge troves of data AI solutions need to be effective.
• For many retailers, successfully leveraging AI will require partnering with third parties. Because of the barriers involved, employing an in-house strategy can be extremely costly and difficult. This has led to the rise of AI commerce startups, which can provide a more cost-effective approach to overhauling the customer experience.

In full, the report: 

• Provides an overview of the numerous applications of AI in retail, using case studies of how retailers are currently gaining an advantage using this technology. These applications include personalizing online interfaces, tailoring product recommendations, increasing the relevance of shoppers search results, and providing immediate and useful customer service.
• Examines the various challenges that retailers may face when looking to implementing AI, which typically stems from data storage systems being outdated and inflexible, as well as organizational barriers that prevent personalization strategies from being executed effectively.
• Gives two different strategies that retailers can use to successfully implement AI, and discusses the advantages and disadvantages of each strategy.

To get the full report, subscribe to an All-Access pass to BI Intelligence and gain immediate access to this report and over 100 other expertly researched reports. As an added bonus, you'll also gain access to all future reports and daily newsletters to ensure you stay ahead of the curve and benefit personally and professionally. >>Learn More Now

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If you want to know how people feel about healthcare in America, just ask Eric Ries.

"Everytime there's a new healthcare bill, people go nuts," Ries told Business Insider. "If I didn't read the news, I would know when there's a new bill from the server melt down problems alone." 

Ries is one of the original developers behind Resistbot, the text message-based bot which makes it easy for users to send letters and faxes to their representatives in Congress. The bot has amassed 1.366 million total users since it first launched in March — a number which goes up with every shift in federal policy, from healthcare to Deferred Action for Childhood Arrivals (DACA).  

Resistbot works like this: users text "RESIST" to the number 50409 — or message the bot over Facebook. The bot asks a series of questions, like full name and zipcode, so that it can identity the user's local senators. It then sends a fax to the senator's office with a personalized message from the user about their concerns. Yes, a real paper fax. 

Once users have sent a fax, they can unlock more capabilities — such as outreach to members of the House of Representatives, personalized and physical letters, as well as phone calls.

This week alone — in the days since Republicans senators introduced the Graham-Cassiy bill to repeal the Affordable Healthcare Act — Resistbot has seen its new users increase by the thousands. From September 18 to 21, the app had a total of 34,368 new users. The most active day was September 19, when the bot had 80,589 active users, new and returning. 

Jason Putorti, who now runs a lot of the day-to-day operations for the bot, said that Resistbot has resulted in almost 5 million faxes sent, 33,000 postal letters, and nearly 34,000 call minutes to representatives. 

Over all, the bot has sent and received 91,421,000 text messages. 

It's a heavy load for the volunteer-based application, which was built on the programmable text message software Twilio and is hosted on Amazon Web Services (AWS) servers.

"Classic scaling problems"

The specific logic of the bot was customized by the Resistbot team,  but the core of it is the opensource communication platform called Rapid Pro. The bot also integrates with other applications, such as Lob, a system that helps businesses programmatically send large quantities of physical mail.

Still in its early days, Resistbot continues to face what Ries called "one of those classic scaling problems." The team has already run through its free usage limits on both GitHub and Slack.

Ries said that while the bot software is good at its job, none of the components were designed to be used at the scale the bot has been experiencing. As the result, the wait time for sending messages can be long. Every once in a while the system has what Ries calls "a total meltdown." 

"It's designed for very high scale," Ries said. "We're just really pushing it."

Users, however, don't seem to mind. Once run entirely on Ries' personal creditcard, Resistbot is now fully funded by user donations. Over 20,000 people have given Resistbot money, which is used to fund postage for physical letters as well as AWS server costs.

Despite taking phone calls from the press, Ries insists that he's rather hands off about the project these days. The bot is primarily managed by a core group of six to eight engineers.

A total of 123 people have contributed across tasks, from managing social media to submitting letters to the editor to local newspapers (one of the latest features to be added to the bot). There's also a fulltime customer support person — a stay-at-home mom — as well as an editor who writes a policy blog at Resistbot.news. 

As Resistbot grows in popularity with every passing Senate bill, Ries said he sees this as a new way of doing politics. 

"I think we'll develop a whole new range of techniques for coordinating and doing activism. Resistbot is just connective tissue and glue to get it going," Ries said. "I don't see this as an ideological or partisan thing. This is really about the forces of democracy versus the forces of illiberalism."

SEE ALSO: A new analysis says 21 million more people would have no insurance under the new GOP healthcare bill

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Improving artificial intelligence (AI) technology and the proliferation of messaging apps — which enable users and businesses to interact through a variety of mediums, including text, voice, image, video, and file sharing — are fueling the popularity of chatbots.

These software programs use messaging as an interface through which to carry out various tasks, like checking the weather or scheduling a meeting. Bots are still nascent and monetization models have yet to be established for the tech, but there are a number of existing strategies — like "as-a-service" or affiliate marketing — that will likely prove successful for bots used as a tool within messaging apps.

Chatbots can also provide brands with value adds — services that don't directly generate revenue, but help increase the ability of brands and businesses to better target and serve customers, and increase productivity. These include bots used for research, lead generation, and customer service.

A new report from BI Intelligence investigates how brands can monetize their chatbots by tailoring existing models. It also explores various ways chatbots can be used to cut businesses' operational costs. And finally, it highlights the slew of barriers that brands need to overcome in order to tap into the potentially lucrative market. 

Here are some of the key takeaways: 

• Chatbot adoption has already taken off in the US with more than half of US users between the ages of 18 and 55 having used them, according to exclusive BI Intelligence survey data.
• Chatbots boast a number of distinct features that make them a perfect vehicle for brands to reach consumers. These include a global presence, high retention rates, and an ability to appeal to a younger demographic.
• Businesses and brands are looking to capitalize on the potential to monetize the software. BI Intelligence identifies four existing models that can be successfully tailored for chatbots. These models include Bots-as-a-Service, native content, affiliate marketing, and retail sales.
• Chatbots can also provide brands with value adds, or services that don't directly generate revenue. Bots used for research, lead generation, and customer service can cut down on companies' operational costs.
• There are several benchmarks chatbots must reach, and barriers they must overcome, before becoming successful revenue generators. 

In full, the report:

• Explains the different ways businesses can access, utilize, and distribute content via chatbots.
• Breaks down the pros and cons of each chatbot monetization model.
• Identifies the additional value chatbots can provide businesses outside of direct monetization.
• Looks at the potential barriers that could limit the growth, adoption, and use of chatbots and therefore their earning potential.

Interested in getting the full report? Here are several ways to access it:

1. Subscribe to an All-Access pass to BI Intelligence and gain immediate access to this report and over 100 other expertly researched reports. As an added bonus, you'll also gain access to all future reports and daily newsletters to ensure you stay ahead of the curve and benefit personally and professionally. >>Learn More Now
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