2.06. What role for spreadsheets?

In this sheet we take over the basics! The possibilities offered and often overlooked by the most basic and widespread tool in cultural equipment are explored: the spreadsheet.

Disclaimer / Warnings:

  • This sheet addresses Artificial Intelligence (AI), a field currently experiencing rapid expansion at the time of writing. The evolution of this technology may outpace our ability to update this page.
  • Generative AI is a probabilistic tool that makes errors: its results and outputs should be reviewed carefully.
  • If you use generative AI to analyze personal data, make sure to anonymize it in order to comply with the GDPR.  

Although sophisticated tools exist and are increasingly being deployed in the cultural sector, many professionals continue to rely on spreadsheets such as Excel or OpenOffice to analyze their customer data. Why is that? Quite simply because these tools are simple, flexible, relatively accessible, and powerful - even though they are most often used below their full potential.

Spreadsheets are not an outdated solution; on the contrary, they are the starting point of an informed data strategy that allows one to move confidently toward more complex tools if needed. Indeed, understanding how these tools work also enables those who want to go further in data analysis to build their skills in order to make more informed choices later on.  

A valuable basic tool offering unparalleled flexibility

  Spreadsheets make it possible to process, analyze, and visualize data in a personalized way. Their structure of information in columns and rows allows for a practical approach to data "logic." They stand out for the great freedom they offer users in terms of data organization and adaptation to the specific needs of structures. Users can thus determine the indicators they consider relevant for analyzing interactions with the public. From there, it is possible to create personalized tracking tables, perform sorts and filters, and develop charts without depending on a predefined system.

Spreadsheets also allow for the construction of simple dashboards from other data sources, provided that these sources are also well structured. Working with spreadsheets requires teams to take responsibility for data processing, to clearly formulate objectives in order to avoid producing useless tables, and to set up a data logistics framework prior to any data analysis project.

In summary, spreadsheets provide a way to become familiar with data usage and to conduct agile analysis for manageable data volumes and fully customized uses-provided that objectives are clearly defined and the creation of oversized tables or weekly indicators that ultimately serve no one is avoided.  

An ally for developing 'data literacy'

Too often seen as simple grids for storing numbers-or even used merely for formatting (full of colors with no analytical value or merged cells that complicate data processing)-spreadsheets are frequently underused.

Yet they offer advanced functionalities for processing and analyzing data. For example, search and filter functions, calculation formulas, macros, or pivot tables allow for in-depth analysis. Learning how to use these features gives users control over the data available within their organization. This learning process also requires building new skills: it involves thinking about data structuring and the knowledge one wants to extract. What information is most important? How should it be sorted, organized, analyzed? This initial rigor facilitates a smoother transition to more complex tools, if needed, and helps to evaluate the promises of off-the-shelf marketing and CRM (Customer Relationship Management) tools in light of the actual needs of the teams.

To fully leverage their capabilities, it is essential to centralize all relevant data. This raises the question of export functionalities from the various tools containing data (ticketing software, mailing platforms, social media). Provided these can be exported in a usable format (well-structured raw data, open formats such as CSV), these data can offer valuable insights into spectator behavior: frequency of attendance, most effective communication channels, favorite types of shows, average baskets, audience segments based on engagement, etc.

Using spreadsheets allows cultural professionals to better understand their data and, in doing so, to develop a true data culture, which is valuable regardless of future choices in digital tools. It is a stage for reflection that enables deeper exploration, experimentation, evaluation, and identification of the most relevant indicators for the specific organization.  

A springboard toward advanced data management

By keeping control over their data and making full use of the tools at their disposal, each cultural organisation can make strategic choices that are relevant and tailored to their actual needs.

For those seeking to optimise their analyses, it's possible to combine the capabilities of spreadsheets with generative artificial intelligence tools. These tools can automatically generate well-structured Excel files from raw data, suggest interpretations of your data, and save considerable time in formatting and structuring. Once the data is properly organised, it becomes easier to analyse audience interactions, segment spectators based on their behaviours, and identify trends. Particular care should be taken to anonymise the data contained in the file in order to comply with GDPR obligations (for example, by using temporary identifiers to link AI analyses to spectators after the research is completed).

A next step? Integrating structured data into Business Intelligence (BI) systems to automate certain analyses and produce more complex dynamic dashboards. These dashboards allow you to track performance indicators such as attendance, ticket sales, or the effectiveness of communication campaigns. By combining these various tools, it becomes possible to build tailor-made analyses, create visual dashboards, and identify spectator behaviours.

Using spreadsheets also helps teams clarify their needs: by identifying the most useful data and the processes required, it informs the choice of any professional tool to be adopted later. For small organisations, or those that cannot or do not wish to invest yet in an expensive data management software, a spreadsheet is also the best way to carry out a proof of concept (POC). By testing collection and analysis methods, they can assess which types of data are most relevant and which comparisons or cross-analyses are most useful for achieving their goals. This approach helps validate assumptions before committing to the purchase of a more sophisticated and costly tool.  

To go further

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