Data Analytics Sydney & Melbourne Implementation Services

To make the best use of data analytics solutions, we need to understand the how and why of data collection.

As a data analytics company and specialists in MS data analytics, we want our clients to get the most out of their data. But to do that, we need to be crystal clear about why the data is being collected first. Once we do that, we can focus on collection methods and analysis techniques that bring you the results you’re looking for. 

Collecting huge amounts of data — which happens a lot more frequently than it should, simply because we can —without a plan in place is like going to the grocery store and throwing a bunch of random items in your trolley, then trying to assemble meals from them. You can do it, but wouldn’t it be better to go shopping armed with a list based on the meals you intend to cook? 

Wringing the most out of your data is just like that; you don’t want to be left with holes or wasting time processing data you don’t need. When we apply data analytics solutions, we want them to be specific, well planned, and useful for your company’s unique needs. 

What does your business want to accomplish?

Thinking about the desired end result, what would you like your data and data analytics to accomplish? It’s often wisest to start with a goal in mind and work backwards from there. Say your business wants to launch a new product. What kind of data would facilitate that? You would want to know things like:  

  • How much it costs to make your product 
  • What the market rate for such a product would be 
  • How much profit the product will yield 
  • The amount competitors are charging for similar products 
  • Stores that carry products similar to yours 
  • Retail outlets where you already have a relationship 
  • Customers who are buying products of yours similar to the new one 
  • Where those customers get information about the product type 
  • Places where you could promote the product 

Before even getting into data analytics, you would likely need to do some targeted data collection and decide how to use the information most effectively. At Antares, we help our clients with these issues every step of the way. 

The applications of data and data analytics are boundless today

You’d probably be amazed at the limitless applications for data analytics today. As well as launching new products and services, like in the scenario above, you can use data analytics to locate potential customers and convert them to existing ones. And your current customers can become more loyal and add more of your products or services to their experience. 

Data analytics is particularly helpful in marketing segmentation. You’ll know exactly which party needs what information, and you can target email campaigns and advertising accordingly. Data analytics eliminates wasted time and money whilst improving results. 

Do you sometimes feel like your business’s decision-making could be sounder? If you feel like you’re guessing too much of the time, you can remove much of the doubt with decisions based on hard data. Likewise, you’ll be able to forecast trends and finances better, whether for your own company or across your entire industry. 

Data analytics isn’t just for selling and obtaining clients

Internally, data analytics can be just as helpful as it is in attracting customers and selling goods and services. You can solve performance problems and improve processes with data analytics, again reducing waste and making better use of your budget.  

When it comes to managing employees and building staff, data analytics can be just as helpful. You can use data thoughtfully to see where you’re getting the best results, where employees are needed, and who might be better suited to different departments or positions.  

Contact us today for the data analytics solution you’ve been missing!

Frequently asked questions

  • What is data analytics?

    Data analytics is the process of taking raw data, whether quantitative or qualitative, and using it to answer questions pertinent to your business. When executed properly, data analytics can help your business achieve its goals by assisting you in creating tactics from start to finish along the way. 

    There are different subcategories of data analytics. Descriptive analytics, for example, looks at trends and historical events. Advanced analytics uses both traditional statistics and newer technology like machine learning to provide new insight into the data collected. 

    Historically, data was collected by hand and processed manually, which was incredibly time-consuming and naturally had many limitations. Nowadays, however, computers have allowed us to analyse massive amounts of data in minimal time, and there are data analytics companies, like Antares, that perform analysis for other businesses. 

  • What can data analytics be used for?

    The uses of data analytics today are virtually unlimited. As discussed above, understanding why you are collecting data can influence how you obtain it, what you collect, and how it is analysed. 

    Examples of where data analytics can be used include: 
    – Product development
    – Planning and launching new products and services
    – Event planning and execution
    – Finding and converting potential customers
    – Improving customer retention
    – Segmenting marketing and nurture campaigns
    – Conducting evidence-based decision-making
    – Tracking trends
    – Financial reporting and forecasting
    – Solving performance problems
    – Managing employees and recruitment

  • What is data in data analytics?

    The data we use in data analytics can take many forms. Primary data comes directly from the source, such as from your customers or potential customers. Secondary data, on the other hand, is not firsthand data. Examples of secondary data include reports of competitor figures, some industry reports, news, and data acquired from paid third-party services, like lead generation companies. 

    Data can also be qualitative and quantitative. Quantitative data refers to objective information with a numerical value. Examples include your clients’ income information or revenue from your various sales outlets. Conversely, qualitative data is more subjective in nature. It might be something like your customers’ preferences for certain foods or non-numeric reviews of your service. 

    Examples of data sources include: 
    – Web forms
    – Surveys
    – Reviews
    – POS systems
    – Focus groups
    – Contests
    – Apps
    – Event attendance
    – Social media
    – User profiles
    – Interviews
    – Website behaviour
    – Direct observation

  • What is the difference between data analysis and data analytics?

    Data analysis and data analytics are similar but not quite interchangeable terms. Data analysis is a subcomponent of data analytics. Data analysis is the process of working with data: arranging and examining it to derive useful information. For instance, data analysis in research might examine the efficacy of medications or the comparative energy efficiency of various types of fuel. 

    Data analytics is the science that encompasses data analysis. It also includes the collection, organisation, and storage of data, as well as the many tools and techniques utilised to obtain and work with data, such as Microsoft data analytics. 

    As data analytics specialists, Antares can assist your business with both data analysis and the other aspects of analytics. When you collaborate with us, you get the benefit of the entire discipline of data analytics, not just one piece. We are confident this will create better desired results for your business in the long run. Contact Antares today to learn more. 

Scroll to Top