Dirty CRM Data Is Like Dirty Fuel – 7 Tips to Avoid It

BY Maximizer
February 26, 2015

Dirty fuel causes the fuel injectors in your car to develop issues: failed emissions, surging and bucking various throttle loads, smoke from the tail pipe, lower RPM and pollution. In the worse case scenario, it leads to engine detonation, which causes catastrophic engine failure. Simply put, dirty fuel is nasty and best avoided. Whereas, if there is some quality fuel in the tank, the engine not only purrs like a pussy-cat, but also functions efficiently and affordably.

A parallel between a clean CRM system and a clean driving experience can be easily made, because ultimately, each demands a ‘tank’ to be filled with a quality catalyst.

In the case of CRM, it’s the purity of the data loaded into the database which powers effective and efficient CRM. ‘Bad’ or dirty data means the database has been clogged with ineffectual or redundant contact information, resulting in poorly segmented customer profiles and unresponsive campaigns across multiple channels.

When a business make a substantial investment in a CRM system, both financially and from a resources perspective, it’s vital that CRM offers a positive return on investment; follow our steps to clean and import data into your CRM for high performance results.


1. User training
Best practice CRM training will go a long way with designated staff, by ensuring that only clean data is imported from the outset. The sooner staff users respect the importance of intelligently analysing the vast volumes of data from different channels, the quicker the CRM database can be properly populated and campaigns segmented. The easy way to do this is to run regular training sessions with all users on what signifies clean data from the organisational perspective, how to sift and key in data easily, as well as on the functions of the CRM system.


2. Lock down your sources
With the wealth of channels available, data can come in from many sources at a dizzying speed. It’s critical to have a clear understanding of exactly where the data comes from and that no avenues are left unaccounted for. Sources may include: email inbox and contact lists, mobile phones, project books, invoice sheets, lead generation activity lists, web enquiry and registration forms, social media contact form responses and internal data listings. Find, track and monitor them closely.


3. Clean and de-dupe
De-duping is an essential activity, which will quickly locate old, part entered, obsolete or inaccurate data. This activity can also be used when new data from old databases is being imported into a new system, so that only high grade contacts and background information make it through to the final list. Duplicate data can often be merged, so that the records are unique and clear. The process means the right, clean data is kept up-to-date for whomever uses it.

4. Be choosy and vigilant
Not all data generated is valuable data. Sales and marketing staff upload and collate complex data into dashboards, which arise from a variety of integrated marketing campaigns. Firstly, it’s wise to implement a policy as to which types of information merit attention and meet the strict standardised user conventions deployed on the system. Secondly, it’s also a very good idea to repeatedly test record uploads in small batches, so there is evidence that the right data is being imported into the right area of the CRM system in order for planned campaigns to run smoothly and correctly.


5. Label all campaigns
Unfortunately a CRM system isn’t a mind-reading robot. Unless a user tells it precisely which data it needs to pull and match to go out with a certain campaign at a certain dateline then the chances are that it won’t happen or else there will be mistakes. Data segmentation will minimise any hassles in this area. It will also ensure key CRM actions related to certain important data will complete as anticipated.

6.  Run regular audits
There’s always the 1% chance that dirty data will worm its way into a CRM system, either through human or technical error. The data needs to be kept fresh and you’ll need to know how old certain data is; for example, if you’re running a telemarketing campaign externally that data needs to flow back in and overwrite (e.g. Job roles changing) and any old data needs to be removed. Just like good user training, it’s equally important to schedule in regular audits to check, for example, for: any new data sources, new CRM system edition requirements, user training needs, data validity or to identify strategies which will evolve the process and in doing so, reduce bottlenecks in clean data flow.


7. Finally, choosing a CRM with tools built in to support your clean data strategy is key. A fully-featured CRM should allow you to sync contacts from different sources, as well as provide duplication search catalogs. Rule defined user defined fields will ensure all data required to support an action or task is provided.

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