Tell us about your interaction with smart technologies like AI and Cloud-based computing platforms.

As a consumer of technology, I see how smart technologies and Cloud-based computing platforms are being used every day. When I see predictive suggestions on email or simple courtesies coming through on the next actions such as our CRM or other tools that we’re using I can see the real power and I think there are three key areas that it facilitates. It increases collaboration between team members. I also think that it allows for better communication across teams and with customers. And then, finally, I think it enables better outcomes.

At Adoreboard, we’re lucky in that we get to experiment quite a bit with our own technology and we’re applying the potential of AI to different problems. There has been a number of initiatives where Adoreboard has taken other types of data and transformed it into a more appealing or a really unique data form that that is aimed at improving consumption and ease of use of technology.

How did you start in this space? What galvanized you to start at Adoreboard?

My experience working in corporate communications allowed me to see the problem that organizations face when they make big bets and big decisions to anticipate the needs of consumers usually in the absence of data.

Or, by using rudimentary approaches to understanding customers such as NPS which sets a customer as a number of sentiment analysis which isn’t granular enough. Sentiment puts your customer’s opinion into tidy buckets of positive-negative or neutral. By observing the ineffectiveness of these initiatives in improving both customer and employee experience it put me on a journey to discover how by looking at emotion you can really understand how customers feel and why.

I had the privilege of working with some global brands like Hewlett-Packard where I was seeing how they were thinking about the future of analytics and that inspired me to think about this. So, I was coming at it from a problem perspective, experiencing the problem myself and quantifying the frustration of not really understanding how customers feel leading to organizations making ineffective decisions that impact customers.

The great thing is that I brought that problem to Queen’s University, a world leader in emotion research. I teamed up with a team of Data Scientists and the problem and solution came to fruition. That’s essentially how we created Adoreboard.

What is Adoreboard and how it transforms Data Analytics for Marketing, Sales and Human Managers?

Adoreboard is a platform that gives Marketing, Sales, and Human Experience Managers a way to measure and what matters: human emotion. We’re giving decision-makers the ability to consume what we call Decision Ready Insights which is essentially the bridge from raw data to business answers.

By ingesting all the data from all areas of an organization and applying root cause analysis through our framework to go from a high-level view of a brand to competitor benchmarking and SWOT. The data is analyzed over 8 emotion indexes that can be broken down into 24 different emotions. Key themes and topics driving each emotion are pinpointed and laid out in the product. The analysis allows you to quickly identify the things you need to improve and build upon and also the things that are working well in your organization.

We have a technology platform and a team of human experience professionals who are helping improve the experience in all areas of the organization.

How do you bring AI, Human Experience and Emotion AI together?

At its simplest form, we are taking a philosophical stance on this emerging space of both customer and employee experience. We’re taking it from the viewpoint of the customer and how they view their experience when they interact with a brand, product, service or employer. That’s the bigger idea of Human Experience or HX.

We are unifying all these experiences by providing a proven framework invented by Data Scientists at Queen’s University to measure what was previously unmeasurable. We are providing a way to enable people to understand human emotion. Artificial Intelligence is a facilitator to this understanding by translating any textual input into emotional intensity and with that emotional intensity, you can pinpoint specific emotions the customer or employee is feeling.

What is the Future of Customer Analytics for IT, SaaS and Cloud Vendors?

I think the future is about making decisions easier for the end-user. How the software helps the end-user make better decisions about their customers or employees.

I think the way to do this is to facilitate the consumption of insights and analytics in a way that enables the decision-maker to quickly connect their business context to the insight to allow them to make a decision. I think that the closer that you can get I.T., SaaS and Cloud vendors closer to enabling people to make decisions. That ultimately is driving real business impact.

How big is your AI and Product Development team?

We are lucky to have a small but focused Artificial Intelligence and Product Development team. As a Queen’s University spin-out we have access to some of the world’s leading thinkers and researchers in Artificial Intelligence and user experience. We have a small but rapidly growing AI and product team who typically have studied to doctoral level and have some industry experience.

We invest quite heavily in research and development. We have usually one or two active projects with academic collaborators with the goal of improving our Analytics and Artificial Intelligence. We’ve been privileged to benefit from government-led initiatives such as the Knowledge Transfer Partnership to embed that knowledge from a university into our business.

Tell us more about your Emotion AI and Experience platform and the kind of data it ingests from various sources?

Our emotion AI and experience platform is called Emotics. It is an online software platform designed with business decision-makers in mind and accessible across all areas of the organization. It has the simplicity and good user experience for strategy and decision-makers but the detail and robustness that Data Scientists and analysts would expect from a powerful Data Analytics platform.

We’re allowing organizations to essentially take a 360 view of their customer, employee or human experience by integrating any textual data into our system. Data can come from social media, Net Promoter Score, CSAT, product reviews, Glassdoor, or any other textual input. This also allows users to make links between the emotional experience and the kind of operational outputs such as time etc.

We also integrate with tools that our target audience is already using. For example, you can automatically connect Zendesk to pull in textual data from your customer service area or Survey Monkey to pull in any open-ended answers and we have a really exciting roadmap of integrations and for all of the software platforms that already capture data that isn’t being unlocked in terms of emotion analysis and insight.

How should young technology professionals train themselves to work better with Automation and AI-based tools?

I think that the biggest thing that technology professionals can do is to experience what it’s like pre-automation to understand the pain points of the user. This way they should understand how their work will impact the end-user. Focus on the value first and work backward as opposed to coming up with a solution and trying to reverse that into a problem.

It’s something that we as a company do, we embed our developers and engineers in other areas of our business for a period of time so they get to witness and view what our customers are experiencing and the pain points that we’re trying to solve. The engineers are then best placed to make decisions about how they go about making those improvements with the customer in mind.

What is the biggest challenge to link Brand Empathy with Customer Experience and still retain competitive values in 2019? How does Adoreboard make it impactful for brands?

There is no doubt that the experience that organizations and brands create will be a competitive advantage in not only 2019 but for t years ahead. I think the biggest challenge is the ability to focus on what’s important and the ability to prioritize the experience in terms of friction points but also to accelerate those areas that are generating what we call ‘magic and differentiation’ for the business.

I think that the challenge is understanding the needs of your customers and the goals that they want to accomplish and not getting in the way of that. I think the temptation is to over-engineer the experience and to get in the way of the customer when the actual reality for the customer is that your brand, product or service is transactional. People don’t wake up in the morning thinking about banks they’ll only be concerned about a bank if they can’t withdraw money from an A.T.M.

So maybe banks should be boring? There is no need for them to really think about themselves as something different than providing that that basic service. However, in this new digital environment, we’re seeing disrupters such as Monzo and others really rethink the experience by prioritizing what matters most to the customer. I think Adoreboard really helps the prioritization of those decisions based on friction and magic within data and to link the intensity of how your customer feels and why.

We use Plutchiks Wheel of Emotion as a framework when measuring emotion intensity. For example, our Trust Index moves from acceptance to trust to the admiration or the Anger Index moves from annoyance to anger to rage. This provides an insight into the action that the customer is likely to take depending on the intensity of emotion they are feeling.

The Good, Bad and Ugly about AI you have heard or predict

When I think about AI, I think about the phrase “almost intelligent” which always gets a bit of a chuckle, but I do think that we should view AI as a facilitative technology as opposed to a “solve-all” technology, especially when it comes to stuff that really makes us human.

I think there has been a rush for organizations to label themselves as AI, when in fact they’re not using Artificial Intelligence in its true sense. I think that we know AI will be a force for good in terms of simplifying experience and improving lives. For example, the release of connected cars that can predict traffic and predict if the driver is going to be late by being connected to the drivers’ calendar.

I think about AI as facilitative as opposed to the more drastic versions. I think of course there’s going to be breakouts in terms of AI completely transforming industries and our lifestyles and life, but I do think that that it’s being talked about as one of these technologies that has promised but not necessarily always delivered.

What is your opinion on “Weaponization of AI/Machine Learning”? How do you promote your ideas?

Almost every technological development has the potential to be weaponized. Education is key. Whilst our technology is not likely to be weaponized, we think that it’s really important for Adoreboard to take leadership in the whole area of AI and Machine Learning. We’re doing this by establishing a Human Experience Academy in association with Queens University where we’re not only looking at and the broad areas of Human Experience from the perspective of the employee and customer experience we’re also looking at it from the perspective of AI.

We think that AI should be a force for good. We’ve done collaborative projects where we’re trying to move the discourse forward on bigger societal issues and by using AI. For example, we’ve collaborated with Rice University to try to understand the impact of mood expressed online on obesity rates in the US. We were able to predict what states would have increased the obesity rates based on that insight.

What AI, ML and SaaS start-ups and labs are you keenly following?

I am a keen reader of MIT Media Labs they always publish and share interesting insights and developments in the industry. Another Belfast based start-up B-Secur is doing some really amazing things in AI and biometrics. They are able to get interesting and what could be life-saving insights from the human heart.

What technologies within AI/NLP and Cloud Analytics are you interested in?

The development of AI and NLP starting to understand more how people think and act is really exciting. I think if you look at the history of text analytics, we started off with really brittle approaches like a “bag of words” when if the word appeared you know we’d be able to assign it into positive, negative or neutral but we’ve now breakout technologies and AI that use a different semantic approach looking at the meaning and looking at the key emotions linked to that.

I think the future is around natural language generation and how technology has been developing in recent years. The impact it will have on the AI world is massive.

As a Tech Leader, what industries you think would be fastest to adopting Analytics and AI/ML with smooth efficiency? What are the new emerging markets for these technology markets?

I think the fastest industries are going to be the ones that have the most to gain by adopting these technologies. The criteria would be that industries that are highly competitive or where some form of insight can really help an organization. I think areas such as FMCG and those types of markets are really going to be important and I think that traditional industries like insurance and banking can also benefit.

What’s your smartest work-related shortcut or productivity hack?

I don’t really have a “smart” hack but I would say keep it simple, drink water and stay hydrated. It also helps to balance out all the caffeine.

Tag the one person in the industry whose answers to these questions you would love to read:

I would love to see Alan Foreman, the CEO of B-Secur’s answers!

Thank you, Chris! That was fun and hope to see you back on MarTech Series soon.