Can you rely on the customer data held in your business systems? Is customer loyalty decreasing and you don’t know why? Do you wonder if your communications get to the intended recipient? Do you question the accuracy of your reports?
2017 has been dubbed ‘the year of the customer’ and it is estimated by 2020 customer experience will overtake price and product as the key brand differentiators. Even though most recognise the importance of data and analytics in building credibility and relationships with customers, less than a third (21%) of UK businesses have confidence in their customer data.
This infographic highlights the findings from our unique study into how businesses manage their data. Below we examine the implications of poor data quality for your busines…
Data volumes are exploding and it is estimated 2.5 exabytes of data is produced every day – an equivalent to 90 years of HD video! So it’s not surprising businesses struggle to stay on top of it…
Our study shows 25 per cent of businesses utilise Excel and paper to manage customer data, even though it is estimated 88 per cent of those contain errors, affecting data accuracy. As a result, your communications may be misinformed or not reach the intended recipients, which can damage your customer relationships.
21 per cent of businesses use separate systems for different functions business. Although fit-for-purpose, entering data into disparate systems can lead to inaccuracies and duplicates. When one hand can not see what the other is doing, it jeopardises the customer experience and ultimately revenue generation.
11 per cent of SME’s use email software to store data which poses a risk of cyber-attacks and security breaches, putting your customer’s data at risk. A damaged reputation could cause customers to leave, not to mention the hefty fines!
TOP TIP: To address your data quality issues it is important to review your current systems and identify the right solution for effective data management. Explore other benefits of using the right technology for your business.
66 per cent of businesses admit finding duplicate data ‘by accident’. With customer interactions recorded against different records, it can be challenging for sales and customer service teams to have full visibility of a customer account and impacts ability to deliver consistent levels of service. Consequently, high levels of duplicate data can be a source of frustration to customers, leading to complaints and ultimately low retention levels.
TOP TIP: Regular deduping exercises will catch any duplicate records helping you keep overcome poor data quality. More here.
Our research found a staggering 79 per cent of businesses are unable to verify their customer records are up to date, let alone data held from other sources. Furthermore, due to inaccurate email address data, 66 per cent of companies experience deliverability issues. As a result, important messages are not getting through and customers miss out on significant notifications and offers, affecting you ROI.
TOP TIP: Implement data quality processes to make it easier to record data, in the right place and format. More here.
According to our study 59 per cent of businesses don’t have data cleansing processes in place. Without a clear strategy, data issues mount up becoming hard to manage. With an increased number of errors and inaccuracies, customer satisfaction levels will drop. Think about it from the customers perspective – do you getting frustrated when a customer service advisor takes a long time to find your records? What about when they haven’t got any information from prior interactions and you have to repeat yourself?
It is important to realise the consequences of poor data quality as it’s really the accuracy of data that separates the best businesses from their competition and increases customer retention. According to Data Management Survey by SAS, 93 per cent of leaders agree that their data strategy allows them to innovate existing business processes through improved analytics.
If you are at the beginning of your data management journey, check out our post on how to achieve data quality nirvana.