Audience And Data Management
Market research data reporting transforms raw data into actionable insights, empowering brands to refine strategies and gain a competitive edge. Multivariate analysis decodes complex relationships considering multiple variables for a deeper understanding of business dynamics.
With our market research data reporting tools, you gain insights through live dashboard updates covering crucial metrics such as field status summaries, quotas, demographics or insights from key performance indicators at various touch points across various geographical data.
Our market research reports offer a broader perspective to ensure a comprehensive understanding of your information landscape. We use data reporting tools like SQL Server, PowerBI and Tableau to visually represent your results, making them easily understandable. Additionally, we employ SAS, RStudio, Python and SPSS for comprehensive data management and analysis to meet your specific needs.
Our multivariate market research analysis reporting helps businesses to test hypotheses, make assumptions and hold future predictions by finding patterns and correlations among multiple brand and category data points, providing a deeper understanding of the dynamic scenario. In market research, it establishes the cause and effect using a set of KPIs to explain or predict and understand meaningful patterns within datasets.
Through predictive analytics, we enable the analysis of historical data trends, facilitating the forecasting of future market behaviors. Going beyond regression analysis, multivariate assesses the complex interplay of variables, providing a nuanced understanding of the factors influencing market trends and consumer behavior. Using conjoint analysis, we help businesses understand the perceived value customers assign to various components or services and therefore, determine pricing, product configurations and bundling packages.
After checking the relevance of the data to the objectives, different data analysis techniques can be deployed to uncover patterns and relationships between the performing variables. One of the methods, interdependence, concises the size of the dataset by combining various attributes/variables meaningfully. The highly correlated variables are grouped together. For example, customer service effectiveness, product liking and product recommendation could be combined into a single factor as customer experience.
Drawing from over 100 data points provided by more than eight million consumers across 40 sectors in 40 countries, we integrate business survey information with diverse behavioral data to generate robust forecasts. The data sets range from current buying/consumption behavior, trends, category performance and future outlook.
One of the methods, dependence, uses probabilistic models where the prediction of outcomes is the central theme. It helps us understand the relationship between multiple predictor variables and the predicted variable, which helps us estimate future outcomes. For example, what would the sales look like over time given the media spends, the reach of sales personnel, catchment, etc., or predict binary outcomes such as the likeliness of customer claims in the insurance sector given their age, health condition, occupation, among others.
We effectively apply multivariate data analysis to address key business questions pertaining to purchasing patterns, pricing, refining product offerings etc. Our customer segmentation mechanisms, supported by advanced statistical models, enable precise categorization of consumers, facilitating targeted marketing initiatives.
Our product and service optimization methods have aided businesses in fine-tuning their offerings, aligning them strategically with constantly changing and competing market demands. Through marketing mix modeling, we provide insights to optimize promotional strategies and predict the efficacy of different marketing channels. We deep-dive to understand linchpins versus secondary drivers of consumer preference to identify critical factors influencing consumer choices.
Our expertise in machine learning, predictive analytics, statistical modeling, intelligent automation, streaming analytics, computer vision, natural language processing (NLP), reinforcement learning (RL) and deep learning (DL) help us meet quality research and analysis requirements to fulfill client demands. Our capabilities span a diverse range of cutting-edge technologies, enabling us to deliver innovative solutions tailored to the unique needs of businesses.
Our Market Research Data Reporting and Multivariate Data Analytics capabilities contribute to the holistic understanding of past events, assessing current situations and making informed predictions for the future in dynamic business scenarios
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