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Business LibreTexts

3.5: Working with data

  • Page ID
    36839
  • Reporting

    The process of becoming a customer-centric organisation does not end with gathering data. You need to report on that data to the people who will act on it, in a format that will actually be consumed. For example, if you give everyone a 27-page financial report filled with spreadsheets and nothing else, very few people will read or try to interpret it.

    You need to consider your audience: who is going to receive your data, and what format works best for them? The marketing team would receive different data to the managerial team, who would receive different data to the sales team, and so on. Make the data available, but communicate only what is relevant to that audience to facilitate their path to taking action.

    clipboard_e858078eb7844293b0212180c0b047a45.png
    Figure \(\PageIndex{1}\): The reporting pyramid. Examples of who needs to see what aspect of website analytics data

    Ideally, and while acting within the bounds of legal requirements, your organisation should place no restrictions on who can or cannot see existing data. Everyone in the company should have access in order to facilitate improvements. Make the data available to customer-facing staff as well as product designers, for example.

    Why is this so important? Why does every part of the organisation need access to the data you are giving them? Data takes the emotion out of decisions, moving the organisation toward a customer-centric viewpoint. Managers can no longer say, “I’m experienced in this field, so I know what to expect” because opinion no longer matters. Instead, look at what the data is saying to drive your personalisation strategy and deliver relevant customer experiences.

    Analysing data

    The data feedback loop should never stop after a report. If you want to be agile, you need to consume, interpret, and understand data and turn it into an effect that will result in an immediate reaction.

    You can read more about analysing data in the Data analytics chapter. For now, remember that the goal of analysing your data is to look for patterns such as similarities, trends, deviations, and any other relationship, and thinking about what those mean. This process can help you solve problems both on a small scale, at the level of websites and campaigns, and on a larger business-wide scale that you may not have realised you had.