What are the best practices to identify customer behavior patterns in BI?

1-First rule you should follow in the analysis is "What do you want to achieve from this data ,what is your end goal " 2- Then the second step is what data is in hand, and what are KPIs to be considered. 3-Explore the KPIs in consideration of business goals, customer satisfaction, preferences, and behavior. 4-Gather your analysis, visualize, share, and present 5- Take Feedback and Improve the overall model with business needs, now you will be able to gain insights.

Align your customer behavior analysis objectives with broader business goals. Establish baseline metrics to measure the current state of customer behavior. This provides a reference point for evaluating the impact of any changes or interventions. Set benchmark targets for each metric. Benchmarks can be based on industry standards, historical performance, or aspirational goals. Keeping the target realistic is very important.

Understand what behaviors matter most - churn, purchases, engagement? Utilize transaction logs, website visits, surveys, loyalty programs. Standardize formats, handle missing values, ensure data quality. Group customers based on shared traits or behaviors (demographics, purchase history). Track metrics over time to identify seasonal trends, growth patterns, or anomalies. Explore relationships between variables (price sensitivity, product affinities, referral sources). Leverage charts, graphs, and dashboards to effectively communicate insights.

Analytical models are simplifications of reality. They can be constructed to understand, explain, or predict aspects of the real world (like customer behavior), but they cannot represent its full complexity. Recognizing this limitation is crucial for avoiding overconfidence in the accuracy and applicability of model outputs. It encourages a continuous process of testing, learning, and refining. This perspective also fosters a more nuanced approach to decision-making, where models are seen as one of many tools in the BI toolkit, complementing, rather than replacing, expert judgment, experience, and critical thinking.

Communication is a key to being a successful BI and BA expert. Selection of a type of visualization should be based not only on the data type, but also on the stakeholders needs, understanding and skills. For eg. Different visualizations should be used for different data sets, data domains and different stakeholder demands.