Data quality is a critical topic in any organization where data is used. Data quality refers to the level of accuracy, reliability and validity of a specific data set such as marketing or sales data. Data quality is a gauge for measuring the extent to which your organisation can rely on set of data for decision making, marketing and sales.
Why it is Important:
Data is the heart of any organisation. In this age of big data, data quality is simply critical. Data quality is very important for Marketing, Sales, Operations and Analytical departments and can affect all levels of your organization. Therefore having bad quality data can have an impact on:
Sales rely on data as a way of determining buyer persona and choosing which channels to pursue for high ROI. In a case where data relied on by the sales department is bad, a lot can go wrong. Resources end up wasted without results. Moreover, instead of selling, the sales team becomes more focused on fixing bad data.
Data is at the center of all marketing activities. After all, an organization must know their market before selling to them. Bad data can greatly hamper the success of marketing activities. Issues like undeliverable email campaigns, marketing resource wastage, and lack of segmentation are a few problems caused by bad marketing data. Good quality data on the other hand, results in more efficient marketing processes and higher conversion rates.
Several organisations have suffered irreparable damage as a result of decisions that were based on bad data. Without accurate data, decisions will be made on wrong information. For instance, a marketing manager might double count the number of leads in CRM as a result of duplicates in a data set. The same issue of duplicate can cause management to take hasty decisions based on inflated numbers.
Data quality is like oil to sales mechanism. Good quality data results in an almost effortless sales process. On the other hand, use bad data and your sales operations drags to a halt. Without data completeness, activities like assigning leads to your sales team will impossible. Moreover it will take even more resources like time and money for your sales team to double check data for errors.
Bad data from marketing and sales usually ends up in the hands of operations team to fix prior to finalizing sale or when performing customer service. However, even your internal operations team can miss huge gaps in data quality resulting in wastage and bad decisions.
Some Steps to Ensure the Best Data Quality
Establish Data governance – The best way to ensure data quality is to safeguard it by restricting unauthorized access. You have to be aware of who has access to what, establish high data quality control and enable reporting.
Set in Place Systems and Processes – Another vital step is establishing a system. You have to establish a process which allow automatic data noramalizating, dedupeand automatic data appending when needed. This will make it easier for your organisation to authenticate and validate data before it is used.
Clean Data on an on-going basis – Data cleaning must be adopted on a regular basis if you want to keep your data quality high. Data cleaning helps in eliminating common data issues like duplicates.
Data management is everything in a business and you should entrust such a vital activity to the experts. At StrategicDB, we offer full service data cleaning to increase data quality and save you lots of resources. Get in touch with us today to get started on your data.