Business

What is the Cost of Low Quality Data?

Low Quality Data

Many businesses feel that the quality of their data isn’t good enough, even though they understand the importance of great data. Some organisations believe an average of 30% of their data is not accurate, often because the right processes aren’t in place when information is initially entered.

Poor Data Affects your CRM – Customer Relationship Management

Your CRM – Customer Relationship Management is used to manage interactions with your customers and potential customers. It will build customer relationships to increase sales, build relationships with your customers and increase your ROI – Return on Investment. So it makes sense that your data has to be of the best quality for your CRM to work effectively.

High-quality data increases good business decisions and enhances confidence, but how detrimental is it to let your data become out of date or not relevant?

CRMs that contain out-of-date, duplicated or incorrectly data have obvious costs, such as paying extra for storage. Additionally, there’s also many hidden risks that initially, you may not even see.

  • Directing Campaigns Using Obsolete Data

The accuracy of customer data is fundamental to ensure that their work is optimised for best results. When campaigns are created, it can be incredibly discouraging to see emails bounce back and mail unopened. Irrelevant of how good a campaign is, if you’re using outdated data, your information will be inaccurate and your ROI will suffer.

  • Time is Money – Waste of Time with Inaccurate Leads

Your sales and marketing teams depend on accurate customer data to ensure that they’re well informed on possible prospects and can deliver their best sales pitch. If they’re using inaccurate data, they will miss valuable opportunities. A team that’s calling an obsolete phone number when they could have been emailing the ideal potential customer is a waste of time and time is money. Dead leads will slow down your sales pipeline and in turn demotivate your sales team.

  • Poor Data affects Brand Reputation
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Brand reputation means higher sales and profits for many reasons: trust and customer loyalty. However, if you’re sending duplicate catalogues or spelling people’s names incorrectly, it can damage your brand reputation irrevocably. Once your brand’s reputation is damaged by poor data, your customer retention is also damaged. If they lose trust in your business or fear their personal information is exposed, even your most loyal customers will stop patronising your business.

  • Loss of Repeat Business

With many customers, all it takes is one bad experience to stop doing business with a brand they have previously loved. Maintaining good-quality data can be the difference between compliance and being fined. Incorrect data means time, money and reputations can be lost, reflecting badly on your business and lowering customer confidence and reducing repeat business.

  • Lost Revenue

Businesses waste revenue on bad data quality. Failure for businesses to contend with poor quality data could mean ever-increasing costs and communications may fail to convert to sales because the customer data is incorrect. Poor quality data means you have inaccurate targeting and communications.

The Importance of High-Quality Data

Having the confidence in high-quality data will save you time and money. Knowing your data is fit for purpose means more time spent using the data to drive insight.

Effective data quality management should be rooted into your organisation. Ensuring it and identifying data problems as they occur is more beneficial and cost effective than trying to fix poor quality data.

The digital and regulatory rules are becoming increasingly complex: more data, more channels, more regulation. This adds pressure on the processes that organisations have to maintain the integrity of their data.

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What is a Data Management Strategy?

A successful data management strategy involves collecting, organising, protecting, storing and using valuable information and data. A data management strategy creates and implements a well-planned approach in managing an organisation’s data assets meaning there is less chance of poor quality data.

Choose Data Acquisition Services

Choosing data acquisition services is a cost-effective solution to poor data quality. You can be guaranteed that data has been run against the Mailing Preference Service (MPS,) and has agreed to receive 3rd party communications and is verified in line with the Direct Marketing Association’s (DMA) guidelines.

Poor Quality Data Sees Poor Results

So, if you get poor quality data you will see poor quality results. Customer service, marketing and your bottom line will suffer. Many businesses fail to achieve their objectives due to missing, incomplete or inaccurate data.

The cost of poor quality is high. It’s a widespread problem and business leaders have a responsibility to their stakeholders and employees to put top quality data at the top of their to-do list.

 

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