Information and data are the most strategic assets of an organization. The Data Warehousing Institute reports, “Intellectual capital and know-how are more important assets than physical infrastructure and equipment.” It is critical to harness business data for effectual decision-making, and this blog series will walk you through the savvies of Big Data, and its impact on your Demand-gen and Revenues. So ready to have some Fuel for Marketing?
What is Bad Data?
Developing a data stratagem is no more new. However, many organizations struggle with the accuracy of data underpinning day-to-day decisions. The reason being – the Bad Data. Bad or Dirty Data refers to information that can be erroneous, misleading, and without general formatting. Unfortunately, no industry, organization, or department is immune to it. If not acknowledged and fixed early on, bad data can cause serious coercions.
How does the Bad Data occur – The Sources?
Initially, data quality was limited to just the CRM systems. This complexity now lengthens beyond structured customer data. To start fixing the data quality, you need to get inside the niche and know what exactly cause bad data:
- Missing Data: Empty fields that should contain data.
- Wrong or inaccurate data: Information that has not been entered correctly or maintained.
- Inappropriate data: Data that’s been entered in the wrong field.
- Non-conforming data: Data that hasn’t been normalized as per the system of records.
- Duplicate data: A single Account, Contact, Lead, etc. that occupies more than one record in the database.
- Poor data entry: Misspells, typos, transpositions, and variations in spelling, naming or formatting.
How does the Bad Data affect your Data warehouse?
Dirty data wreaks havoc on the entire revenue cycle of an organization, and in a need to fill the funnel, bad data is creeping into our marketing automation and CRM systems. The impacts can range from a transaction level loss to catastrophic effect for an enterprise. Let’s have a look at the impacts of bad data:
- Higher consumption of resources
- Higher maintenance costs
- Errors in product/mail deliveries
- Lower customer satisfaction and retention
- Increased churn rate
- Distorting campaign success metrics
- Failure of your marketing automation initiatives
- Dissatisfied sales and distribution channels
- Higher spam counts and un-subscriptions
- Negative publicity on social media
- Misinformed OR under-informed decisions
- Invalid reports
- Lower productivity
- Loss in Revenue
David Raab, Demand Gen Expert
How to rescue your data from getting bad/decayed
If you have a data warehouse, you will certainly have some form of bad data corroding it. Though avoiding bad data completely from a source is virtually impossible, Data Management is the key to keep your data clean. The next blog of this series (Fuel for Marketing) will help you have a deeper insight on Data Management and Best Practices. By the time, you can have a look at these Quick Steps, which can help you have a cleaner and a more accurate data silo.
This post was originally posted at grazitti