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Our expertise

Data Analytics

Customers entrust us to perform Data Analysis, Data Science, Machine Learning and Blockchain Data Analysis for their projects. We are a group of data savy analysts and engineers that can perform the full needed end-to-end data engineering, data analysis, machine learning modeling and deployment to the desired customer environment. We have vast experience in a range of different sectors such as IT, Marketing, Health, Media, Telco, etc.

  • Data Analytics & Reporting

  • Data Platform Development

  • Machine Learning & Data Science

  • Natural Language Processing

  • Prompt Engineering with LLM’s

Digital Marketing

If you're looking to grow your business online, our Digital Marketing Consulting service is here to help. We offer expert advice on e-commerce marketing, as well as strategic marketing consulting to help you develop a comprehensive digital marketing plan. Let us guide you through the ever-changing landscape of digital marketing and reach new levels of success.

  • Strategic Marketing Consulting

  • E-commerce Marketing

  • Market Research EU & APAC / Market Trends Research

  • Social Media Commerce

  • Influencer Marketing Campaigns

  • Marketing Report & Analytics

Web3 Solutions

We have offered solutions for multiple Layer 1 blockchains, Dapps and NFT projects. Whether it is building developer ecosystems, Dapp full stack development, blockchain data analytics, blockchain research or community management, we offer services that can cover the full range of blockchain consulting services that is needed to launch a Web3 project.

  • On-chain Data Analytics

  • Blockchain Development

  • Digital Collectibles (NFT)

  • Decentralized Finance (DeFi)

  • Blockchain Technical Content

  • Developer Relations & Ecosystem

Client Stories

Read more about our Customer Success Stories

Cross-border Marketing
 

A Hong Kong publicly listed fashion/beauty e-commerce company wanted to expand to the Dutch speaking market.

 

They already had some global presence in markets such as Asia, The US, and the larger European countries, however they did not have any

presence yet in the Dutch speaking countries.

This is where our consultant helped them with cross-border marketing services.


First, an extensive market research of the current fashion/Beauty market in Belgium and The Netherlands was provided to understand the competitor landscape and their USP.

Next, we decided the go-to-market strategy by providing localization services, strategic marketing plans including omni-channel marketing solutions, influencer search, SEO/SEA.

Finally after going to market, we also provided marketing analysis and reporting services to monitor ongoing objectives and goals. 

We managed to double the company's revenue in the Dutch market, even considering the economic impact of Covid during that time.

Digital Trends Analysis

While industrial robots are already an established value in production environment automation, service robots are now also increasingly being used as first contact with people. Service robots have the potential to take customer experience to the next level.

 

It is however of great important to analyze how employees work together with these service robots, as they will be the first contact point with the customer.

Our consultant has conducted research on service robots for for The AI Lab of VUB (a Belgian University). The purpose of this qualitative research was to understand the potential impact of service robots to frontline employees in China.

Using the Job Demands-Resources model (JD-R), which provides insights into how employees experience their work.

To investigate the effects service robots had on employees and their organization, we made a comparative study based on 24 employee interviews, where half of the employees had already worked with robots and the other half not. 

Blockchain Data Analysis

A top 10 blockchain asked us to help them perform on-chain data analysis. They had just rolled out a newly developed feemarket module (similar to EIP-1559 on Ethereum) and had to analyze their new gas usage. 
 

We performed on-chain analysis to investigate the impact and trade-offs of different blockchain gas parameter settings in order to determine the most optimal gas settings.

 

Using public blockchain data we make data-driven decisions that benefit both applications and users on chain.

Blockchain Docs

A well-known and popular Layer-1 blockchain asked us to perform a full revamp of their main technical docs website. As they had grown from a small team to a global team within 6 months, their docs had become increasingly difficult to maintain

the layout was not scalable and on top of that they wanted to add new features such as localization and easier open-source contributions. We decided to fully redesign a new docs website in Docusaurus, a framework now widely popular amongst bigger open-source projects,

restructuring all of the technical content and making it easier to add new blockchain developer guides and tutorials. The developers and community were largely positive about these new docs, that were now ready to scale to multiple languages, engineering teams and easier to contribute to.

Personalized News Receommendations

A large news media enterprise in Belgium and The Netherlands wanted to develop a news application that was able to provide real-time personalized news recommendations based on user selected interest topics.
 

We developed this real-time personalized news recommendation engine by having it match user profiles with news articles based on their past reading behavior and fine-tune it by allowing user's to specify the topics they were most interested in.

The result was a new popular news media app able to provide personalized recommendation to users. On top of this we built a full fledged data analytics and ML platform, ready to power the most promising AI use cases by using cutting-edge technology.

Marketing Propensity

We designed a marketing Machine Learning model that aimed to engage customers with the greatest propensity score. The first step was to gain an understanding of financial banking data
 

and speaking to the stakeholders to be able to create and select the most important features based on domain knowledge. After performing extensive feature analysis and selection, we compared different Machine Learning models.

Based on the most important classifier metrics such as F1-score and including business requirements. The result was a balanced propensity classification model that was able to predict customer propensity with a significant higher accuracy

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