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So, you want to use your data…

“What can I do with my data…?”

This is a question we commonly across when dealing with both clients and new prospects, who have more than likely heard that “data is the new oil”, and they know they’re sitting on heaps of it; so why wouldn’t they want a chance at a way of increasing their revenue?

Whilst we know that data can provide very valuable and in the future will become most businesses’ greatest asset, to implement technologies such as artificial intelligence and machine learning you must go on a journey with your data. Here we take a look at where’s a good place to start and where you can go with the resources you may or may not currently have within your business…

Look at your current data…

Begin by taking a look at your current data. Can you identify where and how you store and collate your data? For example, this may be as simple as within an excel spreadsheets, or maybe it’s across multiple databases on premise or in the cloud (if it’s stored in a database, you’ll need to ensure you can access the data!).

Then, evaluate what you want to achieve with your data, and decide whether its current location is suitable for these goals. If you want to implement business intelligence or anything further whereby you need to query live data instantly, excel may not be good enough and you may need your data hosted online somewhere, through a web app or database. Alternatively, you may need to re-evaluate your goals if this is not something that can easily be changed within your business.

Finally, see if your data sources complement each other. What I mean by this is, are they integrated and talking to each other? Are your marketing and sales teams separated into different silos including their data, or are their system synchronised so data can easily be passed between the two without need for rekeying information. Integrating all your systems is key to utilising data insight, as it ensures there’s only one ‘version of the truth’ for all your data.

Interrogate your data…

Now that you’ve identified, collected and have access to your data, it’s time to start putting it to work. To begin this process, you should identify what sort of insights you want to get out of your data, and the best way in which this can be represented. Whether this is through fancy dashboards such as Power BI or Tableau, online reports such as R Shiny or KnitR, or through email reports such as SSRS, choose that which is most likely to be beneficial to your business goals.

Once you’ve decided which form of reports you’re after it’s time to implement them. There may be a couple of ways to go about this depending on your business situation. If you’ve got the skills and resources in house then this shouldn’t be too much of a problem. Integrate your chosen solution with your data, play around with what visuals you’d like to see in your reports and you’re there! If you don’t have the in house skills however, you can either hire someone for this role or more conveniently, outsource this to software developers who specialise in this type of work.

Look into the future…

Now that you can see what your data is telling you from reports and dashboard that you’ve setup, you can look at using artificial intelligence with your data, specifically machine learning and predictive analytics. Using your historical data, using machine learning algorithms you can find out the ‘why’ behind your business and certain business questions. For example, a client recently identified a certain segment of customers, which they had previously ruled out, had the greatest number of registrations from a marketing campaign, and they found out why. Discovering data like this can be invaluable to organisations like yours.

Then, using machine learning, you can adapt your current campaigns to try and predict and prescribe what you’re after in the future. If you can identify certain verticals within your data that have a strong effect on customer buying emotions, you can alter these within your campaigns and predict which are likely to be more successful, leading to a greater return on your business. Here, using predictive, analytics, you can answer the ‘what if’ questions.

Take aways…

The most important thing to take away from today is that using your data is progressive; you cannot utilise machine learning and predictive analytics if you don’t first have business intelligence, which you can’t take advantage of if you don’t have all your data integrated in accessible, online systems. Start by looking at your data, comparing it with what you want to achieve and work it from there.

Secondly, you don’t have to do all of this alone. Many companies we talk to try to implement these strategies alone and often come across hurdles. Whether it’s finding that off the shelf software doesn’t work for you, you can’t quite get your reports to pull from the correct data sources or your machine learning algorithms need additional tuning, outsourcing work to data specialists is always a viable option.