We find the answers hidden in your data

Data consisting of seemingly random numbers can be deciphered with the help of data analytics.

We dig into data to find what our customers are looking for. Innolink’s analytics solutions for knowledge-driven leadership provide answers to questions such as:
How should we allocate our development investments?
How can we increase sales?
How can we improve customer experience?
How can we retain our current customer base?
How can we utilise our data?
Where can we find new customers?
How should we present our findings?

Even though the methods may be complex, utilizing the results of data analytics must be easy. Our data analytics combines survey data with practical market understanding and our customers’ own business data. Together these form a whole that allows for a comprehensive view of the business problem at hand. This helps us provide easy-to-understand results with customer-friendly visualisation and explanations in plain language.

Innolink’s data warehouse contains approximately 2.8 million survey replies to different indicators from all industrial fields. The source data consist of over 1,600 surveys, for which more than 880,000 decision-makers and consumers have submitted their replies. As a result, we have a massive amount of comparable data, which can be used as a baseline for evaluating new survey results.

Solutions for all data challenges

Analyses aims to understand the past and see what has already happened – data analytics is the tool for understanding why something happened and what will happen next.

CUSTOMER PATH ANALYSIS

We use data analytics to identify situations that can either deepen a customer relationship or compromise it. By combining customer evaluations with sales data we can model, for example, the likelihood of a customer continuing or terminating the customer relationship in different situations.

CLUSTER ANALYSIS

Cluster analysis helps to identify customer groups and typical customer profiles. While some conclusions can be drawn based on, for example, age and educational level, these are often insufficient predictors of customer behaviour and thus any segmentation based on these metrics is bound to be less than optimal. We can use data analytics to understand what the major behavioural differences between customers are and how they can be grouped based on these differences. Clustering can be carried out based on, for example, consumer habits or values. An improved understanding of customers can be used, among other things, to improve product development, marketing, and sales.

LOCATION ANALYSIS

Clustering based on geographic location is a tool used to evaluate the geographic distribution of certain phenomena and to reveal regional areas most in need of development.

CAUSE AND EFFECT ANALYSIS

Cause and effect analysis is used to determine what is important for the current objective and how a specific outcome is reached. The analysis reveals which issues need to be focused on in order to most efficiently further the current goal.

ATTENTION POINT ANALYSIS

The purpose of attention point analysis is to distinguish the most significant development targets from a larger number of measures contributing towards a certain goal. For any objective, such as improving customer satisfaction or increasing sales, there are usually several promoting factors. Attention point analysis can be used to identify the measures that are most essential for achieving these objectives.

EQUAL PAY REPORT

Companies that employ a minimum of 30 persons must conduct an equal pay audit every 2–3 years as a part of their equality plan. In the equal pay report, the company’s pay structures are visualised according to i.a. personnel groups, gender and age. A statistical model is created of the gender pay gap, illustrating which parts of the potential pay gap can be explained by normal background factors such as personnel structure and which cannot.

INDUSTRY, MARKET OR COMPETITION REPORT

With the help of combined analyses, our economists will shed light on the state of your industry, draw up market forecasts, and make comparisons between competitors.
We use all available statistical data in the preparation of the reports, and, if need be, the data is complemented with results from surveys tailored to your needs.

COMPETITIVE BENCHMARKING

We will find out how your company is situated within the industry and how it compares against main competitors. We use analytical models to illustrate the current state of your company and provide you with tools for improving your business performance.
Innolink’s data warehouse contains approximately 2.8 million survey replies with respect to different indicators, collected from over 880,000 decision-makers and consumers in all industrial fields.

Our experts

Analytics

Matti Paavonen

Business Director, Analytics

Analytics

Janne Palkama

BI Analyst

Analytics

Jyri-Matti Kallionpää

Chief Technology Officer

Analytics

Jussi Jousmäki

Director, Data and Analytics

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