Business Research

Innolead International focuses on how organizations can and are operationalizing analytics to derive business value. It provides an in-depth survey analysis of current strategies and future trends for embedded analytics across both organizational and technical dimensions, including organizational culture, infrastructure, data, and processes. It looks at challenges and how organizations are overcoming them and offers recommendations and best practices for successfully operationalizing analytics in the organization.

Basic data compilation and segmentation will tell what happened, but advanced analytics techniques provide tools to tell why it happened (diagnostic), what will happen (predictive), and what your company should do about it (prescriptive). Get beyond the shallow data analytics and start seeing what big data analytic, advanced modeling, and data visualization can do.

Data analysis should not just tell what has happened already but should give an idea of what to expect. No, predictive modeling is not a crystal ball, but it’s as close as market research can get. Get an idea of what’s coming in terms of product sales, in-store and online traffic, and branding changes.

In Market Research, collecting the data is only half the battle. The analysis stage is where quantitative abstractions become useful intelligence, but the path to insights forks many times along the way, and it really takes an expert to know which direction to go.

Data collection, no matter how precisely planned and executed, can never go perfectly. There will always be a few bad data points in any data set. As part of any analysis program, we clean your set to remove suspicious and inaccurate data, guaranteeing you only see the most relevant results.

When it comes to running analyses, we custom build our solutions so we will not try to force your data into our favorite model (we don’t even have a favorite, we love them all). Instead, our advanced analytics team will find the right data analysis model for you. Whether this means running strict correlations, regressions, or descriptive statistics, it all comes down to your specific needs. And it gets even more complicated from there. Within regression models, for example, one must choose between linear and logistic, and decide if they will use a forest or decision tree model. And don’t even get us started on parabolas. Long story short: data analysis is some complicated stuff, but we are pretty great at it.