Bad data hygiene is one of the leading causes of CRM failure. No matter how good your marketing campaigns are, if the customer data in your CRM system is outdated or incorrect, you won’t get the results you should.
At WiseGuys, we start by diagnosing the problem. The first step is to browse your customer data, looking for patterns:
- Faulty data hygiene patterns – Blank fields, inaccuracies, duplicate records, incomplete data entry, outdated information. For example, one common problem is that often zip codes in New England have lost the leading zeroes. Another is that data entry operators who take phone orders may routinely key the same source code for all orders.
- Database conversion patterns – When new software is implemented, a quality control process for the data conversion is often overlooked. Old codes may not be mapped properly to new fields, or old dates are converted badly. Contact names can get mixed in with company names.
- Missing data – Gaps in customer numbering might mean you are missing an entire set of records for a period of time.
- Inconsistencies between reporting systems – Experienced marketers know that you can’t expect marketing reports to tie out exactly with accounting reports. There are always differences in order cutoff dates vs. paid dates. We look for large differences in customer or transaction counts, which may indicate serious problems with data handoffs.
- ETL (Export, Transfer, Load) issues – We check results from your ETL utilities to make sure data is being transferred correctly.
Once we have the issues identified, we can use a variety of tools and services to clean and update your data.
Some issues – those caused by human error, such as entering incorrect source codes – may not be fixable in historical records, but we fix whatever we can. We also recommend steps you can take to monitor data hygiene and implement best practices so you improve data quality for the future.
With clean customer data, you are ready to take the next step – analyzing your customer base and doing predictive modeling of customer behavior, so you can segment your customers and target your campaigns for greater results.
