Maruti Suzuki India kickstarts brand Dzire’s digital campaign with a chatbot

Isobar, the digital agency from Dentsu Aegis Network, and Maruti Suzuki have rolled out India’s first Integrated Chatbot. Together, they have launched an innovative video banner with an in–built chatbot on select platforms. This interactive property will allow the brand to entertain users’ first level queries, thereby educating them about ‘A whole new world of Dzire’ and redirecting them to the main website and enabling a two-way communication with the relevant audience. Read more

AI/BOT: Where Do Chatbots Go From Here?

To help provide customer service, and in some cases sales, businesses such as Domino’s Pizza, Bank of America and CNN have joined up with the social media giant to enhance their offerings.

The latest company to move the ball for chatbots is fashion designer brand Tommy Hilfiger. Just before the Fourth of July holiday break, news was shared on how the brand took chatbots to a new level via integrating it into autoplay video advertisements. By adding this new layer, Tommy Hilfiger has effectively introduced a new avenue of consumer engagement that most retail brands have not thought of yet. Read more

I Got Into A Fight About Games With A Chatbot

Zo is the spiritual successor to Microsoft Tay – the artificially intelligent chatbot that famously went into a racist, sexist meltdown in 2016. Zo was built with more sophisticated AI software than its predecessor, which translates to more fluid conversations and less maniacal hate speech. However, it turns out Zo really didn’t care for the Life Is Strange video game series – and she doesn’t care who knows it.
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Chatbots and Virtual Assistants are Fast Becoming the New Graphical User Interface

OYSTER BAY, New York, Jul 06, 2017 (PR Newswire Europe via COMTEX) — Machine Learning Automation Helps Achieve Significant Enterprise Cost and Workflow Savings

OYSTER BAY, New York, July 6, 2017 /PRNewswire/ — Conversational interfaces like chatbots and virtual assistants are in the midst of an enterprise market evolution. Fueling this is the savings in time and cost that machine learning automation technologies can provide. With hosts of the three leading chatbot development platforms–Amazon, Facebook, and Microsoft–accruing more than 90,000 developers this year, ABI Research predicts that the revolution will occur in three phases: enterprise-proprietary solutions, common developer tools on competing platforms, and then at-scale deployments and the proliferation of third-party Software as a Service (SaaS) solutions. Read more

You know nothing—so talk to this ‘Game of Thrones’ chatbot

Game of Thrones has captivated millions over the past six years, but keeping track of all of the ruling families of Westeros can be quite a daunting task. Now one chatbot is committed to helping us learn a thing or two.

Over the past week or so, the Game of Thrones Chatbot, a Facebook chatbot designed to answer questions, has been enlightening users about the show and the many, many characters who inhabit the worlds of Westeros and Essos. The chatbot isn’t officially affiliated with Game of Thrones or HBO, but it can answer the big questions about who’s still alive—a much smaller list than in seasons past—and which characters are related to each other. Read more

You know nothing—so talk to this ‘Game of Thrones’ chatbot

Game of Thrones has captivated millions over the past six years, but keeping track of all of the ruling families of Westeros can be quite a daunting task. Now one chatbot is committed to helping us learn a thing or two.

Over the past week or so, the Game of Thrones Chatbot, a Facebook chatbot designed to answer questions, has been enlightening users about the show and the many, many characters who inhabit the worlds of Westeros and Essos. The chatbot isn’t officially affiliated with Game of Thrones or HBO, but it can answer the big questions about who’s still alive—a much smaller list than in seasons past—and which characters are related to each other. Read more

Let this Game of Thrones chatbot refresh your memory on what everyone’s up to

As Game of Thrones approaches its seventh year, it can be tricky to remember where we last saw our favorite characters, let alone the minor ones that have died along the way. And then there’s the general trivia, like the names of Daenerys’ dragons (all of which sound like futuristic tech companies). To help fans get ready for the new season, a London creative agency called Catch created the “GoTBot”— a Facebook chatbot that acts as a digital encyclopedia. Read more

How to make your chatbot align tightly with business goals

It’s not simply enough to set a standard goal, like developing a chatbot that passes the Turing test. Instead, we must seek to create chatbots that align tightly with specific business goals and objectives — expressly designed to perform tasks and actions that solve real problems. They should be charged with the mission of moving needles in measurable ways and transforming key performance indicators that ultimately impact business performance. And to be truly effective, chatbots should strive to be agile, scalable, and omni-channel in nature. Read more

This, of course, is much easier said than done. Many companies are able to tackle smaller, standalone chatbot projects — say, for Facebook Messenger or the web. However, the majority of us don’t possess the resources or manpower to develop fully comprehensive implementations with game-changing customer experience potential.

A big part of the problem lies in how we tackle development. Typical legacy chatbots are strictly rules-based and require a great deal of maintenance and manual work, such as the tedious task of data-labelling. The process often looks something like this: Write the code, launch the bot, add more labelled data, modify the rules for additional use cases, rinse, and repeat. This needs to be performed on a continual basis in order for the chatbot to deliver on the promise of an “automated” experience. And since everything has to be hand-coded and managed directly by developers, there’s little opportunity for real-time intervention by the customer experience (CX) leader or any other relevant business user.

These time-consuming, resource-intensive development practices are what hinder smaller companies from achieving effective implementation — not to mention the cutthroat competition for the limited pool of engineering talent not already claimed by Fortune 500 giants. So what choice do these organizations have? They either go the route of pouring all their engineering resources into chatbot maintenance or they outsource their needs to a third party. Neither scenario is ideal, because they’re either being terribly inefficient or they’ve lost considerable control in designing the kind of experience they want their chatbot to provide.

If the goal is to create impactful chatbots that deliver superior user experiences, we need to rethink the role of AI development and how it can best serve this objective. We should create smarter, more flexible AI that enables rapid application delivery with minimal hand-coding and can use any combination of labelled or unlabelled data. We must conceive of a development approach that truly optimizes human-in-the-loop computing, maximizing the proverbial synergy between man and machine.

Doing this will shift the ownership of the chatbot away from engineering and place it in the hands of the domain expert who can truly maximize its business potential: the CX leader, for example. You can think of it as a way to sidestep a huge chunk of the application development and delivery process and hand the keys over to the business user instead. If we do this, we won’t just create better chatbots, we’ll free up our engineers so they can stop wasting time and energy on rote maintenance and focus on bigger and better things.

Why should we place the power in the hands of the CX leader? Simply put, AI works best within chatbots if it can infuse them with a human sensibility. Chatbots are able to observe, learn, and self-improve best when they have a real human context at their disposal and can integrate human knowledge, such as best practice and work flows. This means that the best person for creating a customer service chatbot isn’t just the engineer with the right technical credentials but one who has an intimate understanding of and personal experience with direct customer engagement.

A better approach to AI chatbot development will create a foundation for CX leaders to do what they do best — create happy customers. It will provide a versatile deep learning base that empowers CX leaders to build tasks and complex work flows without ever having to touch a line of code. This will enable them to further hone in on the key performance indicators that will bring the customer experience to the next level. This may involve A/B testing to compare the metrics for a virtual assistant against live agents, interactive voice response systems, or self-service FAQ and measuring everything from efficiency metrics and deflection rates to net promoter scores and customer satisfaction ratings.

Perhaps most importantly, this development strategy will allow companies of all sizes to create scalable, omni-channel chatbots and maintain and evolve them in an affordable, efficient way. Rather than hiring an engineer to build the stage, hire the musicians, craft the instruments, arrange the seating, compose the music, and conduct every time we want a little music, we can allow the CX expert to simply take their place at the conductor’s podium and orchestrate the entire experience from the get-go.

Yi Zhang is cofounder and CTO of Rul.ai, focusing on AI technologies. 
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