Dirty Data: 5 Crucial Points to Avoid in Business Running with CRM
The dirty fuel causes some issues in your car starting from failed emissions or smoke from the tailpipe to engine denotation. However, if your tank is full with high-quality petrol, the vehicle either functions efficiently and saves you a buck. A parallel between CRM system with well-executed data management and clean driving experience can be easily made. Ultimately, both the solution and car demands a ‘tank’ to be filled with good-value catalyst.
In the case of CRM, the purity of the records loaded in your database that powers the efficiency of the platform, as well as overall business processes. Yet, even CRM platforms with comprehensive algorithms may fail without the single data quality strategy rules that can lead to:
- ineffectual or redundant contact information
- mistakes and delays in service providing
- offering inappropriate product due to inefficient customer segmentation
- extra expenses on imprecise invoicing and overpayment
- cracks in security that may lead to sending personal data to wrong addresses
- unresponsive campaigns across multiple channels
Consequently, among the main reasons of dirty data, you can discover too creative records entry, different transpositions, and typos, as well as mistakes in formatting or naming. Hence, to improve the quality of your records, you pay attention to the types of information that have the influence on your database:
Incorrect records are the false information that doesn’t adhere any requirements, e.g. the age of the prospect can’t be 140 years.
Inconsistent information is the redundant records, usually duplicated client information. It appears due to the lack of the single data entry rules, besides various departments create the same customer under different names.
Incomplete items are the missing fields of address, zip code, or a phone number. It can occur when the records are misinterpreted, or data entry is violated.
Inaccurate data is a real info, yet there are some incorrections. For instance, the mistakes in the zip codes.
As it was mentioned above, the dirty data can deliver you a fair number of nasty issues, and extra expenses won't delay in reaching you. Furthermore, your business make a considerable investment in a CRM, so it is critical to receive a desired returns. EBiz article indicates that corporate information grows at 40% per year, while nearly 20% of the average database suffers from irrelevance and inaccuracy. By setting back the actions to solve these dirty data troubles, you may spend almost $100 per dirty record due to Sirius Decisions.
More details you can figure out with this infographic provided by RingLead for better understanding the astronomical cost of ‘bad’ data.
Now, when you all fired up with the useful information about the reasons and costs of redundant, unnecessary, and messy information in your CRM platform, let’s focus on the steps to clean and import data into the system for achieving high-performance results:
#1 Lock down the sources
Due to a number of channels available, organizations have to deal with a variety of records that come into database with a lightning speed. At this point, it is significant to understand where exactly the data appear from to ensure there are no avenues left unaccounted. So, the main sources may contain: invoice sheets, social media contact from responses, lead generation activity lists, registration forms. It is recommended to find them, track, and monitor closely.
#2 Clean and dedupe the records
Deduplication is a critical activity to eliminate unnecessary, obsolete or inaccurate information. You can also use this option during migration from existing CRM to the future one, so just grade records make them through the final list. Dupes can usually be merged or replaced to remain the items clear and unique.
#3 Stay picky and vigilant
Not everything generated is worthy information. Sales reps and marketing managers upload the complex data gathered from different campaigns into dashboards. First of all, it is critical to set the rules and policies for all the users to know what types of records deserve the attention. Secondly, it is a wise idea to try out the items’ uploads in the small parts. Here, you have an opportunity to explore whether the proper data were imported to the right sector of CRM, so the planned campaigns can run smoothly.
#4 Train the users
The practice of CRM training stays closely with the educated and skilled team members that are aware how to enter data to keep it clean from the outset. So, the sooner your users understand the value of clean data for the accurate analysis, the quicker CRM database can be populated in the right way as well as you receive the opportunity to segment all your data. The simple way to teach this is to run constant trainings with all the colleagues to show the significance of clean data for company performance.
Furthermore, you can assign the data steward to oversee records administration and collection according to the practices you have established in your cleansing exercises.
#5 Run constant audits
It is well-known that dirty data may worm its way into the CRM platform, no matter through technical or user error. In this case, you should schedule the regular audits to explore:
- new data sources,
- staff training needs,
- data validity, as well as
- Identify strategic approach to reducing upcoming pitfalls.
The End Slice
Dirty data bites, and the structured one helps to manage the project and campaign planning, as well as improves the accuracy of reports or productive activities. Take advantage of the hints above to accomplish total data quality as the clean and valid database will guide you to the right path of generating revenue.
P.S. If you want to learn more on the most common challenges and solutions on data quality issue, check out our white paper on “CRM Data Management Strategy” for useful insights.