Lead Generation: A Beginner's Guide
March 1, 2021
As a B2B Marketer, you rely on software, tools, and data for your campaigns. But what happens when the data stored in your systems become unreliable?
The end of the year 2020 is close and planning to boost your lead generation will be on the top of your list. If data cleansing and enrichment is not a priority for you yet, we believe it should be.
Dirty data is a major concern for all B2B marketers. Industry sources say nearly 67% of businesses use CRM data to target customers and 94% of businesses believe their customer database is inaccurate. It is tempting to put off dirty data prevention until something goes wrong. But studies suggest it takes $1 to prevent bad data from entering your systems, $10 to cleanse and dedupe it, and $100 if you do not take action.
Bad data can lead to poor decisions. Things can't get any worse than that!
When contact and company databases are wrong or redundant, not only do you end up paying a lot of money for data storage, but your sales and marketing campaigns also suffer. Duplicate data is just one problem. Outdated data is a bigger hurdle
Business today is dynamic in nature. Company revenues rise and fall, employees switch jobs and there are mergers and acquisitions. In such a scenario, contact and company databases are highly likely to fail to keep up with the ever-changing market. Campaigns suffer, Sales Development Representatives waste time on wrong or outdated data, sales operations spend crazy amounts of time on data prep leading to enormous overheads!
Data cleaning, or cleansing, is the process of correcting and deleting inaccurate records from a database or table. Broadly speaking data cleaning or cleansing consists of identifying and replacing incomplete, inaccurate, irrelevant, or otherwise problematic ('dirty') data and records.
With effective cleansing, all data sets should be consistent and free of any errors that could be problematic during later use or analysis.
Better quality data impacts every activity that includes data. Almost all modern business processes involve data. Subsequently, when data cleaning is seen as an important organizational effort, it can lead to a wide range of benefits for all. Some of the biggest advantages include: