How to get started with advanced data analytics

How to get started with advanced data analytics

Cameron Wall provides a standard formula to achieve your data analysis goals

data analytics

data analytics

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Customers are becoming more demanding as they change the way they interact with organisations; looking for faster, easier ways to engage, when and where it’s convenient for them.

If businesses aren’t meeting their demands, and managing the experience in a way that engages them, customers are moving to competitors that can.

Advanced analytics isn’t as daunting as it seems, start as you would with any business project; define your objectives and determine how you’ll achieve those.

Here's a standard formula you can use to achieve your data analytics goals.

1. Start small

Bite off just a little and show how quickly you can realise a business outcome that will resonate. If you are not currently using segmentation, then the insights from a ‘natural’ segmentation analysis will provide insight into your customer base.

A second stage is then to use advanced analytics to diagnose what the key drivers are of specific behaviours. Working through a proof of concept involves doing things differently based on insights that demonstrate value and increase confidence in an analytic approach.

2. Assess where you are on the analytics maturity curve

This is important to identifying the types of projects you are ready totackle. If you don’t have a strategy in place, get someone to help you formulate that view by engaging with both the business and IT areas of your organisation.

It’s likely that pockets of your business are using analytics in some form (a lot has been done with excel, but it’s not scalable or trustworthy much of the time).

3. Prepare for business change

In most cases, shifting to an advanced analytics driven environment requires significant business change. Ensure you have someone who can engage with your stakeholders and manage the business change for you. Advanced analytics is rarely an IT project, it’s a business problem being addressed using a technical approach.

4. Understand your data

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Understand what you have; what you don’t have; where you can access additional, useful data; how you can technically combine that into useable information; and ultimately, what will help set you apart from your competition.

You need to know what data should be collected and evaluated to get you the best business outcomes and how you’ll acquire and manage that once you do collect it. You’ll need to consider data protection and consumer privacy to ensure you’re compliant at all times.

5. Start with a strategy

As with all key business exercises, we can’t stress enough how essential a strategy is to confirming the current and future states that you’re looking for. In addition to your data strategy as outlined above, your analytics strategy must define the business problems you’re trying to solve.

You’ll need a clear set of analytics objectives and an understanding of the appropriate data analysis techniques that are required to meet those objectives. The aim is to separate the ‘signal’ (valuable data) from the ‘noise’ (irrelevant data) and then run analytics across the valuable data.

As Albert Einstein once said, information is not knowledge. What we now have however, is an accessible way to turn terabytes of information and data into knowledge and use that to change the way we operate.

This is a game changer; it’s a way to challenge the status quo and innovate while achieving business benefit along the way.

Cameron Wall is managing partner at C3 Business Solutions.

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