Before you start collecting and analyzing data from different sources, you need to have a clear idea of what questions you want to answer and what goals you want to achieve with your KPI reporting. This will help you focus on the most relevant and meaningful data, avoid unnecessary complexity, and align your data sources with your business objectives. For example, if you want to measure customer satisfaction, you might want to combine data from surveys, reviews, social media, and CRM systems. If you want to optimize your marketing campaigns, you might want to integrate data from web analytics, email marketing, and sales platforms.
Once you have defined your key questions and goals, you need to select the data sources and formats that will provide you with the information you need. Depending on the type and scope of your KPI reporting, you might have to deal with different kinds of data, such as structured, unstructured, qualitative, quantitative, internal, external, etc. You also need to consider the availability, reliability, and compatibility of the data sources, as well as the costs and benefits of accessing them. For example, if you want to use data from third-party platforms, you might have to pay for subscriptions, use APIs, or export data in specific formats.
After you have collected your data from different sources, you need to clean and prepare it for analysis. This means that you need to check the quality, accuracy, and completeness of your data, as well as identify and resolve any issues, such as missing values, duplicates, outliers, errors, inconsistencies, etc. You also need to transform and standardize your data so that it can be easily combined and compared across different sources. For example, if you have data from different time zones, currencies, or units of measurement, you need to convert them to a common standard.
The next step is to integrate and analyze your data using the tools and methods that suit your needs and preferences. There are many options available for data integration and analysis, ranging from simple spreadsheets and charts to advanced software and algorithms. The choice depends on the complexity, volume, and variety of your data, as well as the level of detail, insight, and automation you want to achieve. For example, if you have a small amount of data from similar sources, you might be able to use Excel or Google Sheets to create formulas, pivot tables, and basic visualizations. If you have a large amount of data from diverse sources, you might need to use a specialized tool like Tableau, Power BI, or Qlik to create dashboards, reports, and interactive visualizations.
The final step is to visualize and present your data in a way that communicates your findings and recommendations effectively. This means that you need to choose the right type of visualization for your data, such as charts, graphs, maps, tables, etc., and design it with the principles of clarity, simplicity, relevance, and consistency. You also need to consider your audience, purpose, and context when presenting your data, and use techniques such as storytelling, highlighting, annotations, captions, etc., to make your data more engaging and persuasive. For example, if you want to show trends, patterns, or relationships in your data, you might use line charts, bar charts, or scatter plots. If you want to show proportions, distributions, or segments in your data, you might use pie charts, histograms, or heat maps.
Just remember, the key is to adapt your KPI communication to different stakeholders. Use various elements to make your data easy to understand and interpret and to convey the relevant background, insights, and implications of your KPIs.