Data analytics is being increasingly used by major organisations to attract new customers, serve existing customers more efficiently and improve overall performance. If you own or manage a small business, you probably already collect plenty of data that can be used to answer questions you may have about your business.

Data analytics involves questioning your business, or its environment, and using data to drive action. Small businesses use data too, and can benefit from bettering their analysis of it. Almost every business tracks the amount of time spent on each project and tracks their expenses to see where money is being spent.

As an example, customer segmentation is a powerful data analysis tool that gives business owners a way to manage different groups of customers. By analysing transaction data, we split all of the customers into like-minded groups. From here, you can create services that best target each segment and then send more targeted advertising.

Grouping customer segments

Analysing this data can yield useful insights, but so too can collecting data of other types. For instance, determining where your customers come from and how they find your business can help target future marketing opportunities. Tracking hours worked on projects can assist in predicting the time spent on future projects – and help determine if you need to hire a new employee to help with the workload.

Analysis solutions come in two major types:

  • The first is the one-off report where a question is asked, data is collected and a report written that addresses the question. An example might be to analyse the current state of the market, with a view to determining whether prices will rise or fall next year.
  • The second major type of analysis solution is ongoing tracking, whereby data is collected on an on-going basis to track something of interest. For example, you could track the time that an item is stored in your warehouse before being shipped or sold. Tracking this metric over time will give you up-to-the minute information on how well you are utilising your space. Interventions, like having a sale on slow-moving items, can be tracked too, to see if they have a major impact on performance.

Analytics can also help automate complex tasks. For instance, if you survey your users, you can use text mining to automatically discover topics people are talking about. Likewise, you can also track your social media pages and automatically flag any complaint to make sure you can respond quickly. I’ll cover each of these two types of analysis, and more, in upcoming posts.

The key to finding good analytical opportunities is not to think about the data you do (or don’t) have, but the pressing questions that drive your business. In this way, data analytics doesn’t replace a manager or director of a business – it can’t – what it can do though, is to help them answer questions and to find new questions to ask. Starting with the question first allows you to determine what data you should be collecting, and how to analyse that data to give you the answers you need.

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