ave at their disposal.
Duplicate contacts, invalid emails, incomplete leads, and delayed/cold leads throw off database measurement which then has a detrimental effect on decisions made about program optimization. This, in turn, decreases the ROI of the marketing program while generating more bad quality leads for sales and a lesser budget for marketing teams.
B2B marketers continue to pump poor quality leads into their marketing automation and CRM systems which add to the current challenge of maintaining the accuracy and reliability of customer data by creating data in silos.
Bad Quality Data
The effectiveness of B2B marketing is based solely on the quality of the underlying data and B2B marketers continue to struggle with this. The reasons for which are:
According to research conducted, only 70-75% of CRM data is accurate. This is due to the wrong contact information provided by prospects, conflicting information from 3rd party data providers, high employee turnovers and the unprecedented pace at which business’ grow and consolidate.
Many key attributes are missed when CRM systems are filled which is needed to successfully engage with prospects. Marketers end up chasing the wrong prospects with the wrong content when they aren’t equipped with the complete picture.
Even if a company devotes a significant amount of resources to data management, the data goes stale quickly. According to research, in just one year, 22.5% of your email list will most probably decay. There are plenty of reasons for data decay. People stop using old email addresses and change jobs all the time.
Due to technology evolving there is a rise of new risks and pitfalls appearing so it’s no surprise that security is usually at the top of a company’s priority list. But security is only one part of the equation. To harness the full power of data, it is imperative to place a similar priority on data integrity.
The accuracy and consistency of the data that is stored in a database, data warehouse is called data integrity. Data is considered to have ‘integrity’ if it contains all the correct characteristics and the complete structure that define the data.
Information has become digitalized which has resulted in an increasing amount of that data that arrives from all directions; through mobiles, loyalty cards, CRM systems, social media sites, and complex market research tools. This information will also be arriving in your database in a variety of formats; numbers, formulas, or individual pieces of text.
Apart from this confusing variety of information sources, some employees rely on their own spreadsheets and word documents while others use advanced data visualization tools. This disparity causes its own set of unique problems and can result in useless data.
This is where data integrity comes into play. It ensures recoverability, search-ability, traceability, and connectivity of data. The stability and the performance of your systems increase only when the validity and accuracy of your data are protected.
Implementing Data Integrity
The solution to bad data quality is extensive as you would need to put your demand generation efforts on hold for a long period of time in order to thoroughly clean your database and create new processes. But you need to think of this cleaning process before it gets into your CRM system as prevention of bad database quality is cheaper and more effective than the treatment of a bad database system.
So how do you secure the integrity of your data?
The most important objective for 62% of B2B marketers is to improve the quality of the marketing data but only 40% of surveyed executives believe they have highly accurate data. So implementing a comprehensive data strategy is required in order to stay competitive and to serve customers better.
Bad B2B data can have a profound impact on closing opportunities and can result in low or lost responses, redundant marketing, frustrated sales reps, higher marketing costs, and lower sales revenues. In order to avoid these pitfalls from happening in your company, the focus must go on lead quality from start to finish. The cost of better lead data management is well worth it.
Duplicate contacts, invalid emails, incomplete leads, and delayed/cold leads throw off database measurement which then has a detrimental effect on decisions made about program optimization.