October 19, 2020

Using Data Science to Grow Business – Real Cases

Data science
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We’ve been running a popular webinar series where we discuss real-life examples of how companies have used data science to grow their business.

The series has now wrapped up, so we’re presenting you with a recording of the last event and some key points that were raised.

AI and data science are buzzwords that can be difficult to attach to practise but the real-life examples discussed by our panel demonstrate the potential of data science and frame it in a context that is easier to approach.

Panellists for the last event, at the end of September were:

  • Dr Tim Drye, Chair, Data Analysts User Group (DUG) – Previously Data IQ Data Scientist of the Year, a member of the Office of National Statistics advisory panel and member of the Data Council for the DMA. Tim is a human population specialist and uses data to identify customer and prospect insight and understanding.
  • Gary Cole, CEO, Lumilinks – Formerly of Rackspace, where he reinvented the Acquisition unit and was part of the team that launched Rackspace’s expansion of managed services with AWS & Microsoft Azure. Gary is the Founder of Lumilinks with a goal to create automation via API’s that make businesses more efficient to improve revenues and margin.
  • George Toursoulopoulos, CEO, Synetec – George started off at EDS as a programmer before founding and successfully exiting Focus Technologies. He is now helping Synetec’s clients deliver business-critical software solutions.
  • Julian Roberts, Head of Marketing, ESET – Julian is a results oriented marketing and communications professional with extensive experience in building successful businesses internationally. Julian shared some of his experiences as an end-user currently going through the Data Science journey being discussed.

Watch here


The discussion started with how you can facilitate the end user in making strategic decisions using data. Clearly, data analytics is required.

George elaborated on how you can use data analytics to improve investment decision making in finance. Fund managers are able to look at a bigger data sets and make better deals. Data science expands your universe because you are no longer limited by human capabilities and capacities.

From theory to practice

The panel discussed how applying data analytics involves marrying different types of data from different sources into a common language to gain an overview.

Julian gave an example of how he examined the impact of geography and peer networks on consumer behaviour. He understood the potential of peer-to-peer advocacy in certain areas. He was able to harness that information and apply very targeted communications in those areas. The fine targeting meant that he did not need to spend huge amounts of money to build brand.

As a result, media efficiency has increased over 30% in the test area. While media spend is much lower, marketing communications is becoming more effective. The campaign has been so successful that it will be spread across a larger geographical area in the future.

George explained an example involving Argentex, a foreign exchange company. Their processes involve a lot of regulation, recorded calls, various data sources, and what data science does is that it transforms them all data into a standardised format that can be used to get actionable insights. An example of such actionable insight is: How do we predict a customer is about to leave? What action do we need to perform to retain them?

Strategy is now embedded in the Argentex DNA. As a result, turnover has more than doubled in the last 12 months.

Where to start?

The panel agreed that you should start exploring possibilities by determining the things that are the most important to you. You need to define your key business problem because AI applications will look very different for different companies. Set that as a challenge to the people who are trying to facilitate solving your problems.

Gary brought up the fact that Research & Development projects, such as an investment in data analytics and AI, have tax implications. R&D tax credits can make IT consultancy cost-neutral. With all the benefits the outcomes are likely to have, the possibilities of data analytics and AI are worth exploring.


Towards the end of the webinar, a question from the audience inquired as to what kind of return on investment ESET got with the geographical data science trial.

Apparently, the investment represented only 2-2.5% of the annual advertising budget. ESET will continue to operate on the same spend level while further improving marketing efficiency.

Watch the recording above to catch all the details, as well as further examples.

Are you interested in exploring the possibilities of AI and data analytics? Get in touch and we can tell you how it will boost your operations.

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