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Prospect and customer data in the average organisation typically doubles every 12 to 18 months. However, it is estimated that between 10% and 25% of customer and prospect records include critical data errors. Add on top of that the view that data quality deteriorates at anything from 3% per month to 75% per year, according to industry experts and it is clear that clean and properly maintained data is essential for all businesses that rely on it.


The key dimensions of data quality are:

  • Completeness
  • Readiness
  • Consistency
  • De-duplication
  • Matching
  • Standardization (e.g. name, address)
  • Compliancy
  • Validation (e.g. correct email address)


Poorly organized, substandard or disparate data can severely impact the quality of sales leads and, consequently, the actual sales! The table below is a representative example of how poor data can cascade down through the sales chain and improving the quality can have a massive positive impact.


 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


So how can we help?


For each of the key dimensions mentioned earlier, we have a solution. For example, we can remove duplicate records from your database. It may be that you have separate records for:
- Alan Jones
- A Jones
- Mr A Jones
- Jones, Alan
- Jones, Mr A
- etc.

If these all have the same or similar address details, then they are clearly the same person. If these are not combined into one record, it may be that Mr Jones receives the same marketing correspondence five times or more. This is not going to impress him! Not to mention the cost to you in terms of wasted man hours and money.


We can analyse your database and remove all similar duplicate and merge them into just one record, standardized to your requirements.
For a more detailed list of the services we provide, please view our data services page.

 

Read the article that our Managing Director has had published in dataIQ magazine here
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