Marketing Science & Advanced Analytics
Marketing-specialized data scientists use advanced modeling and digital technology to apply marketing science.
What is important as securing data is establishing an accurate marketing aim and securing execution power.
Derivation of meaningful analysis results from marketing data
Many companies are accumulating various marketing data, such as market, competitors, and customers. However, it is difficult to find business meaning beyond simple statistics. This is because the practical use of the analytic model is degraded as being immersed in the theoretical approach rather than the marketing purpose. Therefore, by having a clear marketing aim and an analytics operating system, you can continuously discover marketing insights that grow your business.
Securing systematic and rapid marketing execution power for analysis results
It is also not easy to connect the aforementioned business meaning to marketing utilization after finding it. The gap between data science and marketing leads to limited execution of the analysis results. Therefore, it is necessary to effectively promote marketing science by securing marketing science capabilities that can link analysis and execution.
Marketing Science & Advanced Analytics Consulting
Marketing-specialized data scientists use advanced modeling and digital technology to realize marketing science.
We implement proactive and advanced marketing by analyzing data from the customer’s perspective.
Marketing-specialized data scientists perform integrated analyze and model marketing data from the perspective of customers. Using AI algorithms and such, we conduct systematic analysis and operation to derive marketing insights with execution power.
- Marketing Data Modeling1Marketing data integration analysis based on effective execution guide suggestion
- Scientific marketing analysis based on AI algorithm2Preparing consumer sentiment big data forecast-based preemptive response system
- Online customer activity reinforcement analysis3Offering online business effective marketing/sales performance optimization insight
Understanding marketing perspective data analysis
Through a data scientist organization with experience in establishing and executing marketing strategies, we can execute data analysis in terms of business perspective, find meaningful insights, and develop marketing utilization scenarios.
Experience in analyzing multi-touch point customer data
We have experiences in integrating and analyzing data for each customer touch point such as marketing channels, eStore, and CS, and establishing marketing and business strategies based on this.
Holding various analysis methodologies for each goal
Depending on the nature of the analysis data and the analysis goal, we perform various natural language analysis, such as topic modeling, network analysis, and sentiment analysis, and analyze major trends and consumer perception structures in detail.
Systematic Analysis Algorithm
We secure analysis continuity and a system based on AI algorithms, such as deep learning and machine learning. Through this, we can prepare a preemptive response system based on big data prediction and suggest a standard operating guide for optimizing marketing activities.
Company A, a global electronic product manufacturer, was operating various marketing indicators within its online and offline sales and marketing channels. However, different numbers are obtained for the same marketing indicator for each channel, so they can be used individually, but integrated marketing insights have not been provided. In addition, company A analyzed each marketing indicator to establish an efficient marketing reinforcement plan to increase sales.
Services of S-Core
S-Core started to establish a standard system of marketing indicators for company A. We have established a system by identifying marketing indicators in operation for each channel and dividing them into diagnostic indicators and operational indicators. Through scientific statistical analysis modeling, we further analyzed the causal relationship between indicators, and also analyzed the relationship with the sales of company A. Based on the results, we established an efficient marketing indicator management system for each customer experience stage and suggested an operation guide.
1. Marketing Indicator Standardization[Hierarchy buildup based on marketing indicator causal relationship reinforcement analysis]Establish effective marketing indicator management system per Customer Experience Journey stageOffer standard operation guide for marketing activity optimization
2. Marketing Investment
Optimization[Simulation for cost optimization including marketing investment]Analyze return on investment over marketing/promotion activities via scientific static analysis modelingOptimize performance by providing optimized investment guide over marketing activities
3. Natural Language
Analysis[Social Trend Detection/ Relationship & Sentiment Analysis]Discover customer needs/trends by natural language analysis on global customer blog, product reviewsDetect main trend and analyze customer cognition structure in detail
In addition, we analyzed and modeled the effectiveness of marketing investments based on marketing science, and discovered consumer trends through natural language analysis of user reviews and blogs
Company A was able to expect the following effects by establishing a standard system based on marketing indicator analysis.
– Marketing: Increased ROI through efficient marketing execution
– Sales: Increased sales through marketing activity optimization
– Managed systematic marketing indicator