We support the design of validation methods and the implementation of data analysis for discovering and solving business challenges in a data-driven manner. This includes the development of statistical analysis and machine learning algorithms that are used in practice.

Common Challenges:
Businesses accumulate data on customers and operations but lack clear methods for utilizing this data effectively.
Despite adopting BI tools to advance DX (digital transformation), there is a shortage of data science experts, leading to inadequate problem setting and ineffective analysis.
While there is a vision for resolving business challenges based on practical experience, the lack of quantitative and objective verification impedes the advancement of solutions.

Support Services:
Our experienced data scientists address such business challenges through data analysis, achieving improvements such as enhanced customer resolution, visualization of business processes, market trend analysis, and demand forecasting. Our analysis employs a wide range of methods, from traditional statistical causal inference to advanced AI and machine learning algorithms, including LLM and generative AI technologies. We provide support in selecting the optimal model from these options. Moreover, we offer unique data utilization and modeling approaches that are thoroughly tailored to your business challenges and market trends, not limited by conventional statistical and machine learning modeling techniques.

Our approach to discovering and resolving issues through data analysis is structured around the following four processes:

1. Issue Analysis and Goal Setting:
In the initial step, we deeply understand your business goals and the challenges you currently face. During this phase, by clarifying your expectations and requirements, we set specific project goals and hypotheses.

2. Data Preparation:
Next, we collect the necessary data for validating the hypotheses and constructing algorithms. This involves integrating information from various data sources in addition to the data you already possess, preparing for analysis.

3. Algorithm Development and Model Construction:
We conduct analyses using the best-suited statistical and multivariate analysis methods for your business. At this stage, we utilize machine learning and artificial intelligence technologies to develop algorithms that extract meaningful insights from the data.

4. Model Implementation and Effectiveness Verification:
Finally, we implement the developed model into your business environment and test the model’s performance. Based on the results of how effectively the model addresses your challenges, we make necessary adjustments to the model.

• Data-Driven Decision Making: Solve business challenges directly through data-backed product development and business process transformation.
• Insights into Market Trends: By modeling market and customer trends, you can quickly respond to changes and maximize business opportunities.
• Cost Reduction: Identify and reduce costs within business processes to support the long-term success of your business.
• Improved Customer Satisfaction: Enhance the customer experience by modeling the needs and personas of your clients' customers.