First steps when analyzing a company's data
The thing you need to understand as completely as possible is how they expect a data analysis to enable them to achieve their objective. They are a business, so their overall objective is likely related to maximising profit. However, there will be a more immediate objective underneath that heading. To maximise profit you can either reduce costs or increase sales. In turn, to increase sales you can increase the number of customers or increase the amount of sales to each customer etc.

The question then turns on how you can use data science to perform one those objectives.

For example, questions that can almost be answered with data science could be 'how do I better identify potential customers?' or 'how do increase existing custmers' spend?' These are still very high level questions, but they are the sort of questions that you need to have in mind as you start to do your descriptive stats etc.

Bear in mind that this is an iterative process and it is completely normal to start off in a fuzzy sort of area. At this stage it is almost the case that having a question in mind is a McGuffin - it will kick things off, but it may not be the question you end up answering.

The CRISP-DM process is a process that has been built for data mining that discusses how to iteratively use results from analyses and models to increase your understanding of the customer's situation, and hence drive the development of a better business objective for use in a data science project.