Customer Analytics

What is it?

Customer Analytics is a way of getting insights about the customer behaviour based on data analysis. No two companies are the same and do not have the same customer, but data can show you the right way to boost your business.

Decision

Customer Data

Insight

Competitive Advantage

Analytics Tools

Profit

The 5 Pillars
Of Customer Analytics

1. Business Analysis

Customer analytics is not just applying statistical methods within data analysis. It is a continuous process. It starts with business analysis that explores, defines the problem and suggests the approach to solve it.

2. Data

The basis of any analysis are data. Yet the data source may vary - we know transaction data, data from core systems, transcriptions from speech to text, big data and others. Data help you reveal the patterns and connection, understand your customers’ behaviour and set more accurate marketing strategies.

3. Data Science

Data Science is a field that links data analysis and business insight with the purpose of correct understanding and analysis of any business problem, e.g. increased customer churm. The process of in-depth analysis is called Data Mining. The main approach of Data Science for structured and unstructured data are visualization, statistical and text analysis, machine or deep learning.

4. Data Visualization

The graphical data view and the interactivity - visualization - are essential to make a quick decision. For example, if a store manager wants to know how many customers come into store at what time, “heat map“ (type of visualization) gives him more clear information than pivot table.

5. Action

Any obtained analytical insight is useless if it’s not applied in practice. Customer Analytics outcomes provide among others the base of target group definition for marketing automation, e.g. the use of insight to create a loyalty program or a personalized offer.

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