Five questions to drive data value

Five questions to drive data value

Companies can profit greatly from data analysis, but in the short term it can be a cost centre. How can marketers maximize its ROI?

Data has increasingly become the basis for many successful marketing campaigns. With the rise of personalization and emphasis on customer experience, data often provides a reliable way of ensuring your marketing is on target. CIM’s 2016 research reported that data-driven marketing is having an impact and informing decision-making in every business and every function across the sector.

However, it is important to remember that data should be practical for your organisation and therefore, determined by the insights you wish to draw from it. With copious amounts of data now available to marketers, where should you start? Here are five key questions to ask your data to ensure that it delivers ROI for your organisation.

1. What do you want to achieve with your data?

Knowing who and what your data is helping should be the basis for any information analysis. Firstly, you must consider who your data is for – is it going to help your organisation perform better, or is it going to measure the success of a recent marketing campaign?

Secondly, what are you trying to improve? SEO? PPC? Social media performance? Data must be collected with the end goal in mind, otherwise it is impossible to know which metrics are most relevant to your organisation. With knowledge of your objectives, the market and your customer, actionable insights can be achieved from gathering data. However, data should determine the action, rather than the action being determined by the data.

2. Does your data give a complete picture?

Most companies capture only a fraction of the potential value from data and analytics. The biggest barriers companies face in extracting value from data and analytics are organizational with people unable to understand and then draw value from data.

Before a business starts looking into utilizing its data, it needs to consider the 4V’s of big data – volume, variety, velocity and veracity. By understanding your data you can then look to fill potential gaps and start making the most of it.

Rather than think of data as a physical set of information, it can be more useful to regard it as a service that provides knowledge and support. Get the terms of service right, a view of what your best data is and any data strategy is more likely to deliver.

3. Is your data accurate?

The volume of data continues to double every three years as information pours in from digital platforms, wireless sensors, virtual reality applications, and billions of mobile phones. Data storage capacity has increased, while its cost has plummeted. Using analytics provides marketers with an unprecedented insight into customer journeys, buying patterns and potential customers.

But it’s important to remember that statistics can be misleading. ‘There are three kinds of lies: lies, damned lies, and statistics,’ so the old phrase goes. Many marketers will recognise the scenario where one segment of data is leapt upon as the key insight, while other (perhaps contradictory) data sets are ignored: the result being a skewed, incomplete picture. And that’s assuming you’ve acted quickly – in April, Adweek reported that 60% of all data is incorrect within two years, which may limit actions proposed from the analytics and distort the accuracy of your findings.

4. Does your data drive better business decisions?

Before collecting and analysing data, marketers should ask what the findings will mean for the business. Insights mean little if they can’t be acted on, and marketers need to know how the data they gather will be used, by asking questions such as: will the data improve CX or revenues? Can we use this data to gain consumer trust rather than arouse suspicion? How can we reach our core business objectives using this new level of insight?

Using advanced analytics to guide better decision-making can enable organisations to: increase revenue, decrease costs and become regulatory-compliant. For example, US telecom company Sprint used advanced analytics to “put real-time intelligence and control back into the network”, driving a 90 percent increase in capacity.

5. How much does your data cost?

Committing resources to building a business strategy from data analysis can be costly. While the whole organisation might profit from the insights in the long term, who will be paying for the technology, time and expertise in the short term? Is it solely marketing’s responsibility to deliver ROI from data, or can the cost be shared? If budgets are tight, what affordable options deliver the best value?

Data analysis doesn’t always need dedicated teams and expensive tools. Google Analytics, for example, delivers more than enough information for many companies exploring data for the first time.

While the term ‘big data’ continues to make the marketing headlines, remember that organisations already own ‘small data’ – from sales figures to web stats and email sign-up data. This can provide a wealth of information, with no outlay – so before you open the company cheque book, consider what data you already have.

For information on which data sets you should be focusing on, read Getting the most from marketing data

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