5 tips for using data analytics in marketing

Knowing where to start when using data in marketing can actually be quite difficult – but get it right and knowing your data can deliver great ROI and personalised campaigns through using the insights gained into customer behaviour. 

data-analysis

I’m basically saying what you know, right? And yes it sounds easier said than done, but take it one step at a time and you will soon start to see the results. Prepare yourself before you embark on the exciting data analytics journey using these 5 tips!

  1. Know your data inside out

Depending on your type of company, chances are that you will have CRM, ERP and HR systems brimming with information. You must be able to access all areas of the data – ensure that people aren’t storing data in their own spreadsheets or privately on their own devices as this will affect cleansing and analysing. By having all the data, you can ensure that you gain an accurate insight into customer behaviour without having to account for the realisation of someone suddenly declaring they have a database of 1000 customers you had forgotten to ask about. Oops!

2. Clean data is accurate data

Don’t bother wasting your time analysing poor quality data. You’ll only end up with shoddy results anyway. It’s the same as using out of date ingredients and hoping for a beautiful cake. What you put in, you get out. Your data is one of your most important business assets, so take care of it, look after it, update it and cleanse it. I promise you, the results you get from doing this will be amazing.

3. Set targets

Really, you can’t achieve something if you don’t know what it is you’re trying to achieve. It is all too common that companies proceed without a clear goal or strategy in mind and it results in trying to analyse everything at once – a process which would be far too daunting if you ask me. So, before you start, take a breath, step back and clearly set out the targets you want to hit before you run analytics.

4. Utilise the correct technology

Wrong technology will waste time and provide incorrect results. This is why you need to work out your target so you can then work out a strategy and the technology to achieve this. Different analytics require different technologies and it’s vital to work out what technology suits your analytics.

5. Don’t digress 

With large amounts of data comes distractions. I can guarantee you’ll have all sorts of ideas after you have mapped out the path you are taking, which is great. But, write them down and if they are still relevant after your analysis then carry them out. Don’t get side-tracked with other ideas that pop up otherwise you will lose sight of your original goals. Focus, focus, focus!

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