Forget big data, the real challenge is dead data

By John Joyce

Big data has been a well-used term over the past six months or so to explain the huge explosion in information we’ve seen in recent years. In fact the growth has been so significant, that we actually it necessitated the invention of a new term to quantify it – the term zettabyte represents one billion terabytes, but was only invented two years ago. Since that point, the growth of data has continued at an incredible rate. More than 90 per cent of the world’s data has been created in the last 12 months alone, but this rate of growth shows no sign of slowing down.

As a result, many have suggested that this amount of data is so large and complex that it is challenging to both make sense of, and to work with.

But the real issue here is the integrity, quality and accuracy of the data – rather than the volume.

Indeed, the success of any customer interaction or marketing campaign is dependent on the contact information an organisation has in its database. Clean, accurate and comprehensive customer and prospect data is fundamental to any sales or marketing campaign or customer management strategy. It can deliver a range of benefits for businesses but most importantly it can help boost an organisation’s sales and increase the value of its customers.

In practice though, poor data quality means that for many businesses, a large proportion of their marketing campaigns never reach the correct recipients. Out of date information means company resource is wasted on targeting customers whose profiles no longer exist, which not only costs the business in terms of ineffective marketing, it also results in lost leads and affects customer relationships.

All too often, organisations collect customer information in silos. They fail to house, analyse or harvest it centrally meaning there is no unified view of the customer, or their contact details. Indeed, just 18 per cent of businesses have a single view of their customers.

The impact dead data is having on businesses is becoming increasingly more pronounced. Not only has the uncertain economic climate placed extra pressure on marketing and customer management campaigns to deliver effective results, data itself is becoming outdated at an increasingly rapid pace.

The rise of dead data

A customer’s information is liable to change at any point for a variety of reasons. They may move house, change mobile numbers or marry. Every year, 750,000 people are born, while 600,000 die. One million move house.

Indeed, address data in particular becomes out of date very quickly. Some studies suggest it degrades by around 10-15 per cent each year, driven by the fact Royal Mail’s Postal Address File (PAF) makes 4,500 changes to its database every day. Changes to phone numbers are also startling. The UK Telephone Number Database is typically updated between 30,000 and 70,000 times, 6 days per week.

Added to this, the channels available to marketing teams have broadened to include many new avenues – digital and social media to name just two – for reaching customers and prospects. This means even more contact data is available, which in turn adds complexity to the data quality challenge. Indeed, we’ve found that very few businesses have accurate email addresses for their clients. Recent GB Group research revealed that on average only 19 per cent of customer records held an email – and none of these have been formally validated.

The information contained on an individual customer’s profile becomes out of date very quickly – so multiply this across an entire organisation and the whole database risks being inaccurate. The cost to business is significant. It’s been estimated that incorrect delivery addresses alone cost online UK businesses around £146 million every year, with last Christmas costing UK businesses over £132 million in missed or lost deliveries. Contrast this with an estimated cost of 10p to capture clean and accurate data at the point of registering customers, and you realise just how much money goes down the drain.

Maintaining data quality

With information changing on a daily basis, maintaining a healthy and accurate database is a continuous task. To combat on-going data decay, organisations must cleanse or clean their records. This involves an automatic batch process of correcting or removing information that is inaccurate, out of date or incomplete – such as validating that the phone numbers held on file are still live, and not out of order or disconnected. Equally, the solution should be able to flag up information that has been wrongly formatted. Sometimes human error can be just as much to blame for the problem: some estimates suggest that 37 per cent of business data is inaccurately stored because it has been incorrectly keyed in to the system.

But ensuring the quality and integrity of data doesn’t stop there. Completeness and accuracy is paramount – so not only should data be cleaned to ensure it is correct, it should also be enhanced, or appended, at the same time. This process involves adding extra data – such as mobile phone numbers, landline numbers, fax numbers, email addresses and credit history – to customer records, building a more accurate customer profile and enabling a more informed view of their identity, preferences and method of engagement.

The risk of information overload

While the importance of data accuracy should never be overlooked, getting the right solutions in place now is critically important for the future. With the rise of big data, networks and databases overflowing will soon be overflowing with information. According to IDC, the average enterprise will need to manage 50 times more information by the year 2020 while a recent McKinsey report predicts we’ll see a 40 per cent growth in data each year.

If these predictions are correct, organisations are likely to start seeing a significant rise in both the number of customers on their database (as more people come online), and a rise in the amount of data available about each customer – while the data itself will change at an increasing rate. If businesses are to reap the rewards of this, they must ensure they have fundamental data cleansing processes in place first to avoid further headaches as information matures. Only that way will organisations grow, profit and succeed.

About the author

John Joyce is Marketing Services director at GB Group. This involves leadership of the DataCare and Marketing Services businesses within GB Group’s Data Solutions business unit. John has worked for the company for just over five years and is based in Cheshire.

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