Tech media around the world are following Ipiphany™ and our AI journey

How Big Data Can Make Australasia Big Money

Source: Forbes

"Auckland-based software company Touchpoint Group recently announced its new AI program called Ipiphany™, aimed at helping enterprises gain deeper insight on the 'Why,' behind consumer behavior..."

As big data continues to shape the landscape of not only software development, but the enterprise as a whole, Australasian companies have been accomplishing great things in the space. From Auckland's world-first cognitive behavior based AI program Ipiphany™ to companies such as Movio, there are numerous advantages to understanding how to make the most out of one's data when operating at scale in the enterprise.

Auckland-based software company Touchpoint Group recently announced its new AI program called Ipiphany™, aimed at helping enterprises gain deeper insight on the 'Why,' behind consumer behavior. Combining machine learning with language processing and advanced analytics, Ipiphany™ utilizes the power of big data to work with large volumes of customer data in order to create actionable items that enterprises can then act upon. By uploading millions of angry customer conversations into Ipiphany's databases, Touchpoint Group is ultimately hoping to understand the ins-and-outs of customer conflict, utilizing the data it processes across streams to help determine the most likely outcome in certain scenarios.

"Companies know how important stream processing is for their ability to create reactive customer environments-and make their own business decisions moment to moment-but it's a difficult thing to do."

-- Doug Henschen, Vice President and Principal Analyst at Constellation Research.

Australasia's use of big data solutions in the enterprise has resulted in a renewed focus on not only finding more efficient ways to store data, but how Australasian enterprises can get the most out of information they are collecting.

Movio is yet another Auckland organization utilizing big data to help its users better understand their customer base. To accomplish this, it offers campaign management and data analytics software for film studios, distributors, and exhibitors. Seeking to increase efficiency when working with big data at scale, Movio has made use of tools such as as Apache Kafka, Docker, and Prometheus in its recent transition to a microservice-based infrastructure. "Features are often very hard to remove once added. Identifying problematic features (or feature designs) before they are implemented is essential to avoiding costly baggage in a system. The limitations imposed by Kafka queues help guide us to well designed systems. While they can be frustrating when you're trying to rush out an urgent feature, they are often appreciated in the long run," wrote Movio developer Braedon Vickers.

The key to understanding why big data matters is what it unlocks: insights. Without actionable items delivered in real-time, companies are left in the dark as to the issues that matter to their customers. Real-time stream processing with tools such as Apache APA +2.00% Kafka allows for companies to create applications that not only display data, but allow for targeted actions to be taken based on the user information collected. "We see more and more organizations embracing real-time data and stream processing, and Kafka is at the heart of that shift," said Jay Kreps, one of Kafka's co-creators and the CEO and co-founder of Confluent.

Through collecting user data unique to their specific use cases, many Australasian businesses are now able to understand more than ever what truly drives their customer's purchases, feedback, and behavior. In the case of Movio and Touchpoint Group, big data has changed the scope of what can be accomplished with a different approach to creating data-based software solutions. When it comes to using information for better business outcomes, one must remember that it is not enough to merely collect data and house it in a never-again-seen offshore silo. Ultimately, data is only as useful as the connections it helps enterprises to create.

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We've Made Machines Smart--And Now We're Making Them Angry

Source: Popular Science

Phone calls to automated customer service lines inspire a unique brand of ire. Now a New Zealand-based digital marketing company is creating a robot that can mimic our uniquely human wrath in order to help companies better field calls from angry customers.

The project is called Radiant, named for a computer dreamed up by sci-fi writer Isaac Asimov that could predict the future of the human race. Over the next six months, data scientists will craft the artificial intelligence robot using thousands of irate customer calls to some of Australia's biggest banks When completed, the AI will be able to react irrationally to customer service reps' well-intended efforts to calm it down and will likely be capable of hanging up on the agent and spewing vitriolic curses and names.

So far more than $400,000 has been pledged to the project. And though the immediate goal is to help banks train their customer service reps, Digital Trends wonders if this model is merely a stepping stone to more sophisticated versions of artificial intelligence that will be able to field our calls themselves, no matter the horrible names we yell at it.

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Machine learning project aims to find out what angers customers

Source: CMO

The project, which is being funded by Touchpoint, will use srtificial intelligence on big data to better understand how organisations can improve customer experience

A new artificial intelligence project aimed at identifying the brand behaviours and practices that irritate customers the most is being launched in Australia and New Zealand.

Called Radiant, after a supercomputer created by sci-fi author, Isaac Asimov, in the 1950s, the six-month project is being positioned as one of the largest machine learning projects of its kind. It will simulate millions of customer interactions using big data to better understand what company behaviour patterns are leading to negative customer experiences.

The project is being backed by a $500,000 investment from customer engagement consultancy and software vendor, Touchpoint Group. The company has also spent the last two years building the massive data set on customer interactions required.

Touchpoint said Radiant will create virtual customer discussions using thousands of different experience variables and a data set based on millions of real life, anonymous interactions between irate customers and large Australian companies. Data scientists in Australia and New Zealand will generate these different discussions using the big data sets to develop more accurate predictive customer behaviour models.

"Radiant will be searching for behavioural patterns that typically suggest moments of risk or opportunity when interacting with customers," explained Touchpoint Group's CEO, Frank van der Velden. "Effectively, it will be constantly running 'what if' scenarios, to see if a particular scenario is likely to enrage or benefit the customer.

"The problem with analysing both staff and customer behaviour is that there are so many different variables that could come into play. Many businesses are often left scratching their heads wondering what went wrong, let alone how to fix it. The end goal of Radiant is to automate identification of these root causes and related issues, and to prioritise and recommend actions across different areas of a business."

Van der Velden told CMO Touchpoint is partnering with a large bank on the project and is looking to do two things: Firstly, to work through what is technically possible, and secondly, to understand commercially where the real value lies.

"This is a very practical exercise - it's about where we can make the greatest gains around improving customer experiences," he said.

Van der Velden cited rising interest across A/NZ organisations in how to lift customer experience.

"The challenge for companies with large customer bases and lots of room for improvement is that it can take quite a while - years - to turn the company operationally to achieve an optimal level of performance," he said. "We're trying to help tackle a problem for these companies, which is loads and load of data, and use machine learning to come up with recommendation engines they can use, especially at the front-line, to respond to systemic issues quickly."

The more transparent the information is to the frontline and staff, the most things can change, van der Velden added.

As well as what angers customers the most, the project will also look at where positive experiences have occurred to better understand instances where companies have delighted or surprised consumers.

"These are often the seeds of opportunities where a business can differentiate itself in the market by consistently delighting customers in ways no easily visible to competitors," van der Velden said. "One of the key objectives of radiant is to automatically detect these situations, and to allow both risks and customer opportunities to be quickly acted on."

Touchpoint is hoping to use the research findings to extend the capabilities of its enterprise customer experience software offering, TouchpointCX, as well as to deliver non-industry specific benchmarks and best practices around customer engagement.

Radiant takes its name from the 'Prime Radiant' supercomputer created by Asimov more than 60 years ago, that could predict the future behaviour and development of humanity through the analysis of history, sociology and mathematical statistics.

Touchpoint is a NZ-based business that launched in 2001 with a focus on customer experience software and consultancy services. It opened its doors in Australia in 2007 and has a client base including ANZ, Spark, AA Insurance and Westpac.

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How Angry AI Will Train Telemarketers to Handle Angry Real People

Source: Smithsonian

"The robot apocalypse will come with the howling fury of an angry customer service call"

There's a special kind of zen required of those who work in customer service. Now, a company in New Zealand wants to design a computer program that can mimic the hatred of angry callers in order to help those same customer representatives deal with riled up customers.

The project is named Radiant, after a supercomputer in Isaac Asimov's Foundation series that could predict the future. While the real-life Radiant won't be quite so omniscient, its designers at the technology firm Touchpoint hope it will be able to accurately simulate millions of angry customers to help companies figure out what makes people fly off the handle, writes Michael Bingemann for The Australian. They'll spend the next six months feeding Radiant reams of data collected on people at their worst.

Radiant works by examining data from the worst of the worst customer service calls and determining what factors and experiences could set someone off in any given scenario. Touchpoint is working with one of Australia's biggest banks and several insurance companies and telecommunications firms that are supplying the customer service data that is embittering Radiant towards everyday life. By the time the program is up and running, Radiant will be able to react angrily and irrationally to telemarketers and customer service representatives-in-training who will have to try and calm the computer down. They hope to complete the program by the end of the year.

The wrathful robot comes at a high price though: so far about $400,000 has already been invested in Radiant's development. But if it works, it might make your next angry phone call to a company go just a little bit smoother.

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Researchers Aiming To Build 'World's Angriest Robot': Prelude To Judgement Day?

Source: Tech Times

Touchpoint Group, a New Zealand artificial intelligence company, is currently developing the world's angriest robot under the project name Radiant, after the supercomputer featured in the Foundation series of science fiction novels by author Isaac Asimov during the 1950s.

Radiant aims to assist telecommunications and insurance companies, as well as big banks, in dealing with angry customers.

The new artificial intelligence research project, with a $500,000 investment from the Touchpoint Group, is being programmed along with inputs from one of Australia's big four banks. The bank is sharing with the computer scientists collections of real-life customer interactions that have been recorded over the past couple of years, including some customer service data from participating telcos and insurance firms.

Data researchers from New Zealand and Australia will devote the following six months in uploading the collected dataset into the platform and continue modifying its adaptive algorithms with a realistic expectation that it could present before the year ends.

After the programming has been finished, Radiant would do simulations of the compiled angry customer interactions so that the contributing companies could comprehend and analyze the source of the explosive behaviors along with the triggering factors for such outbursts. With all these data, the companies hope to improve their policies and processes for better and improved customer service.

The program Radiant would continuously test "what if" scenarios to check if a specific scenario could be a probable cause to benefit or enrage the customer," Frank van der Velden, chief executive of the Touchpoint Group, stated.

The research would assist in the complex task of interpreting how consumers were impressed by the various products, processes, policies, systems and personnel they communicated with that could cause them to reach their breaking point.

Van der Velden mentioned that the Radiant AI software would be appealing to any establishment that had to work with customer service complaints.

Companies don't have the numbers of staff to go through this manually. It's very difficult. Take a bank for example; they receive a hell of a lot of data every day. But it gets to a point where that dataset grows so large that it becomes meaningless unless you can interpret it. That's where Radiant will fit in," he added.

"The end goal is to build an engine that can recommend solutions to companies-and we're talking about the people at the frontline here-how they can improve particular issues that customers are facing," Van der Velden concluded.

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