Interview with Gábor Bundschuh, Head of Development & Innovation at D-TAG Analytics Inc, a media intelligence company in the US.

Hi Gábor, what is your background and what is included in your current role at D-TAG Analytics?

I have been working with different Information retrieval related solutions for more than 30 years and I have relatively strong experience in AI/ML/NLP tools, data and information management.

D-TAG’s main goal is to support the decision making challenges of companies as effectively as possible. We have a self-developed solution for analysing any type of unstructured, textual contents, especially social media posts and/or documents.

In what ways does D-TAG Analytics differ from other companies?

At D-TAG we are trying to identify the special demands of our potential customers in industries we consider very important, such as pharma, insurance, and banking. Our solution covers both legacy type data sources and social media; it is a hybrid solution for heterogeneous data.

With the help of a well-configured and sophisticated data pipeline and fine-tuned NLP background processes, we enrich the data to be analysed effectively, and turn them into information.

The final goal is to have information instead of bits and bytes.

What are your greatest challenges ahead at D-TAG Analytics, when it comes to serving your customers and developing your offering?

The fine tuning of data (effective data enrichment and metadata handling) is a particular challenge because the quality of data is the most important prerequisite of the analytics. The clarity of the collected data and the quality of the data (metadata) enrichment process are the key points of our approach. Based on data with good enough metadata backgrounds, we can use efficient taxonomies, topic management, entity extractions, and other means in order to be able to discover a large amount of information and — very importantly — to give further ideas to the customers about what they are searching for or what they can be interested in. With the help of this information, we cannot only answer predefined questions, but we can also use the results to formulate new questions and get answers to them very quickly and efficiently.

All customers come with a different level of knowledge. What is important when taking on a new customer?

The starting point in a project is standing on the same page with our customer. At the same time, we want to give them as much experience and knowledge we have as possible, and explain how a typical information retrieval or analytics solution works, what the information is trying to show, and how they can understand it. I think that beyond the predefined business requirements, it is also important to give new ideas based on some “hidden information” we were able to discover.

When it comes to the actual data behind the media intelligence you do, what kind of data or media not currently used can be interesting in the future?

Most solutions on the market are able to handle any kind of data format coming from any kind of repositories, on premise or cloud based. On the one hand, handling the rich media content (picture, voice, video) effectively is still a challenge, especially in the case of special languages. We are continuously trying to find ideas and tricks in order to improve the quality of the speech to text processes. On the other hand, it is very important to improve the quality of AI/NLP/ML related processes, because as I have already mentioned this can be the token of the excellent results. The level of a successful automation will depend on the granularity and complexity of business demands.

Can the entire process of media intelligence be automated in the future?

I think that the short answer is yes, but the detailed, longer one is no. The basic elements and the processes around important milestones of the information management pipeline can be almost fully automated, the level of the automatisation will increase, but the detailed nuances will still play important roles, and will use ML capabilities. But they require manual corrections, improvements and considerations as well.

How do you think the media intelligence industry will change in the next 5-10 years, and what are the greatest challenges and excitements ahead?

The quality of the analytics will increase, the range and type of customers and end users will expand, and at the same time, the tasks will be more varied.

Changing customer needs pose an increasing challenge to us which won’t be easy to handle from professional nor from other points of view, although technology will also continue to evolve in the meantime as well.

Understanding the relation between the existing data contents and the customer’s business needs will remain one of the most important tokens of a successful project. Technology will help to understand this relationship more deeply.

By Peter Appleby

Interview with Ivor Bihar, COO of Mediatoolkit, a media intelligence company in Croatia.

Hi Ivor, what is your background and what is included in your current role at Mediatoolkit?

I’ve been working on Mediatoolkit since the company’s beginnings in 2014. Currently, I’m Mediatoolkit’s Chief Operations Officer leading and growing the company’s teams including sales, product development, design, and marketing across the various stages of the company’s development. Since we began, Mediatoolkit has grown from two to over 50 people, with the goal to achieve 80% growth in employee numbers in 2022.

What differentiates Mediatoolkit from other media intelligence companies?

Since the beginning, we’ve been developing our proprietary online media monitoring technology that tracks more than 100 million online sources in any language across 250 locations in real time. This is the major differentiator.

It’s our goal to enable customers to make better business decisions based on relevant information from the media delivered by Mediatoolkit. Our whole organization focuses on helping PR and Media Monitoring professionals in any industry to gain value through using Mediatoolkit.

What are your greatest challenges ahead at Mediatoolkit when it comes to serving your customers and developing your offering?

Standing out in a crowded market is a challenge for every provider in our space. We’re laser-focused on delivering the best possible experience and continuing to expand the coverage of the ever-expanding number of sources that grows daily.

Educating our customers on what to do with the data we provide is always a challenge, but we want to make sure that clients receive the full value of Mediatoolkit.

Have you recently, or do you plan to, release any new technology-based solutions that will add to or improve the services you offer your clients?

We’re focused on market and user research to ensure that the features we deliver consistently are in line with user expectations, and that they solve real problems. Our focus is also on educating our customers and the market about PR topics: vanity metrics, connecting their PR effort with their company’s results, setting and measuring PR KPIs and the other usual suspects.

We’re also developing a new product that will combine media monitoring and machine learning to enable Disaster Warning System powered by artificial intelligence.

All customers come with different levels of knowledge. What are the most common misconceptions that your clients have regarding what media intelligence can give them?

Media intelligence capabilities are still not well-known throughout all industries, and we often get very different requests. Some companies look at media monitoring as a niche and a small part of their PR or marketing efforts, while others, in contrast, see it as the solution to all their problems.

So far, the most common misconception is that media intelligence is a magic bullet that you set up just one time. Many don’t realise that regular effort must be put into media intelligence if you are to get relevant results and adapt to changing circumstances and contexts of companies and the markets they operate in.

When it comes to the actual data behind the media intelligence you do, what kind of data or media not currently used can be interesting in the future?

We are in an industry that is always hungry for more sources of information, and we have to keep up with new platforms and ways people share content online. Organizations, however, are facing issues with large volumes of data they are unable to process and drive insights from.

If we drill down to a source level, one of the examples of underutilised sources is definitely Reddit. It’s still not recognised enough, and many customers don’t consider it. On the other hand, TikTok is becoming more and more important, but its impact remains to be seen when it comes to media monitoring.

Privacy around the use of social data is an emerging challenge. How do you think that will affect the media intelligence industry?

Just like social media platforms are working to protect users’ data privacy, we also need to ensure compliance with changes and educate our clients on the importance of respecting privacy. We take data privacy very seriously. It’s our responsibility, but also a challenge, to continue increasing our database of tracked sources without compromising an inch of anyone’s privacy. It is challenging to consider all the regulations, but it’s a necessity that cannot and will not be avoided.

If the future holds anonymised and aggregated content, building trust around the technology that provides insights on top of that data will become an even bigger challenge for the industry.

Is there a specific mouthwatering case that you know of where media intelligence has played a crucial role for a client?

Mouthwatering cases are where clients immediately see substantial business benefits and a quick return on their investment. The most common use cases that our customers use Mediatoolkit for are crisis management, campaign, brand monitoring, competition analysis, and sentiment tracking.

The most recent example that wowed us is a market research company that, prior to using Mediatoolkit, had to spend two months of their projects creating a hypothesis about the markets they are researching. After implementing Mediatoolkit, that process took only two days.

Cases like this are the ones that continue to push us to deliver relevant and timely information to help our clients make better business decisions.

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

It’s not news that the amount of data available on the internet grows exponentially. Companies have been going digital for years now, with the recent pandemic pushing this trend further. With these two factors combined, the ability to track and monitor online media is becoming crucial to big brands and smaller businesses wanting to expand their business and deliver exceptional customer experiences.

Additionally, the industry has focused solely on the coverage and getting more and more sources and data. The situation is shifting; we should all focus on interpreting the data and enabling customers to make data-driven decisions. The ones that will succeed in the future will develop technology that understands data as humans do while being able to analyse what is relevant and what can make a lasting impact on the business.

By Peter Appleby