Bad data is bad business. Indeed, organisations believe poor data quality to be responsible for an average of $15m each year in lost earnings, according to research by Gartner. Here we reveal the cost of bad data and why it might be time to clean up your act.
Since GDPR, some marketers are refusing to touch third party data with a barge pole. But is that fair? We speak to industry insiders and data privacy experts to find out the level of risk and how it can be sourced safely and responsibly.
Data as a Service Market was valued approximately at USD 8.7 billion in 2018 and is anticipated to see a growth rate of more than 30% over the forecast period 2019-2026 according to Market Research Future.
The growth of data and its strategic importance to organisations of all sizes has thrust the issue of data quality into the spotlight. Our new whitepaper – in collaboration with data and insight specialists, REaD Group – examines the scale of ‘bad data’, its implications for businesses and what can be done about it.
“The old adage ‘garbage in, garbage out’ has never been more true or more important for businesses. Good quality data means better business decisions, better marketing and more profitable relationships.”
– Jon Cano-Lopez, CEO, REaD Group
Organisations’ believe that inaccurate customer data costs them, on average, six per cent of their annual revenues, according to the Royal Mail. Perhaps more worryingly, over a third are not even sure how much it costs them.
Tackling this problem should be a business priority. In light of the GDPR, clean data is no longer a preference for companies wanting to improve their ROI: it’s now a business fundamental.
In this 22-page whitepaper, you will learn about:
1. The data quality challenge for businesses today: The cost of bad data, its scale and how clean data has become essential in today’s economic and regulatory climate.
2. How to build a data-aware organisation: Learn how to develop into a mature, data-informed organisation, and how this provides the bedrock for maintaining clean data.
3. How to get clean: The key constituents of a data clean-up operation: The 7 essential data cleansing activities which will transform your data streams into a trusty source of insight.
4. How to stay clean: The future of data cleansing: Effective data cleansing methodologies are set to become increasingly important as new technologies emerge which rely on good data.
5. The key questions to ask your data provider: Discover whether your data providers are providing you with accurate, up-to-date and legally sourced data by asking these 8 key questions.
Download the whitepaper below and rid your company of the scourge of bad data!
Trust in digital advertising is at an all-time low thanks to various data misuse scandals and the public’s growing awareness about how their data can be exploited. While GDPR can be seen as the regulators big stand on behalf of consumers, the industry itself should be taking a proactive approach too. So what should advertisers and vendors do? Ben Humphrey suggests five key areas where they should take action.
It’s been a few months since the GDPR came into force and still confusion remains. Fiona Salmon takes us through some of the key mix-ups which are leading data management companies to unnecessarily jettison user data. She also outlines a key lesson to learn from the recent ICO ruling and identifies the one key area where companies are consistently letting down consumers.