“The biggest challenge is to master both the AI technologies and the processes of valorizing them”

Viet Yen Nguyen

Interview with Viet Yen Nguyen, CTO of Hypefactors, a PR automation software company in Copenhagen

Hi Viet, what is your background, and what is your current role at Hypefactors?

My academic background includes a Bachelor’s and Master’s degrees in Computer Science from the University of Twente, and a PhD in Computer Science from the RWTH Aachen University.

I started my career in R&D for the European space industry. I took part in technology transfer projects where we applied recent theoretical advances from academia and demonstrated their applicability to upcoming spacecraft missions. Later on, I joined Fraunhofer, a German research organization where I participated in projects of similar nature in automotive, autonomous farming and the energy sector until I moved to the private sector.

Today I’m the CTO of Hypefactors, a SaaS doing reputation and media tech and helping brands and companies do that more effectively. H&M, parts of the United Nations, Volkwagen, Stark Group (a construction industry) and Sampension (pension funds) are some of the clients in our portfolio.

What responsibilities does your role carry with it?

Our company centers on four segments: data, AI, web and mobile. I drive all four from an engineering and product development perspective end to end. This includes day-to-day operations, as well as new business strategy planning and alignment.

What differs Hypefactors from other reputation & media automation software companies?

Hypefactors is a simple all-in-one solution for reputation and media management. This is incredibly important because many competitors are only point-solutions. We see that prospective users are dissatisfied with using dozens of different tools. They prefer to use only one that allows all aspects of their workflow to be simple and integrated.

What are the greatest challenges ahead for Hyperfactors when it comes to offering your customers analysis and developing your offer?

Throughout the years, we have become strong in multilingual and global analysis using machine learning and big data. We are extremely pragmatic in tackling those challenges, and we are used to making tough choices. Therefore, like academia, the majority of our effort goes into supporting significant use cases. Improved support for low-resource languages like Dzongkha or Welsh has shifted to the future.

What are the best applications of AI for the PR industry, and how does it benefit your customers?

We have over a dozen AIs in production, seeing a million requests per day for various purposes. Our reputation in AI is very user-visible; we assess whether the client’s brand, product or spokesperson is perceived as positive, neutral or negative within the context of a text. It’s trained to not only recognize sentiment, but also facts and cultural aspects that impact reputation. This is a step up from commonly deployed generic sentiment AIs.

The reputation is one single dimension that impacts all other parts of the business. A reputation peak is typically paired with supercharged KPIs on marketing, sales, financial and recruiting.

Have you recently, or do you plan to, release any new technology-based solutions?

We’re constantly improving the integration between our product features, as well as adding more media data and machine-learned information enrichments.

Our systems are on continuous deployment; our roll out strategy is to release incremental changes at least once a day. When you compare the changes on a day-to-day basis, the impact is minor. However, when you consider the accumulation and compounding of these benefits over a longer duration, let’s say months, the difference is night and day.

How do you think AI will change the PR industry in the next 5-10 years, and what are the greatest challenges?

I find it incredibly exciting to be in this industry at this time as there’s so much ground to cover. Take for example language — it’s been a fundamental barrier between people and cultures. AI and big data are breaking these barriers down. Today, thanks to ML translation, we can instantaneously read and understand the gist of articles posted in countries whose languages are completely foreign to us. This is especially important for multinationals, like H&M and Volkswagen. The same result was not tractable two decades ago.

In general, I think there’s a lot of time saving ahead for us by automating repetitive aspects of the work, like reporting and data curation. This enables our clients to spend more on the creative and strategic aspects of reputation and media management.

The biggest challenge is to master both the AI technologies and the processes of valorizing them: the execution. This is not the kind of execution traditionally seen in most businesses because you cannot apply tactics from engineering, financial, sales, and marketing management nor principles from any other business dimension to implement and apply AI in a successful way. In fact, it’s closer to attaining scientific excellence than to driving business ROI. The people mastering this holistically will make waves in the years to come. At Hypefactors, we are heading this wave with our talented team.

By Renata Ilitsky

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