27/11/2019

We’ve all been told to clean up our rooms at one point in our lives, either by our parents or by the little voices we have in our heads that keep us awake at 3 am in the morning. However, some of us work with CRM data, cleaning a CRM system can often be a nightmare that will plague your days let alone your nights.

Having a clean CRM system decreases admin time spent by your marketing and sales team, as well as improving the effectiveness of account mapping, sales enablement, account-based marketing and increasing marketing/sales alignment. This article will present some methodologies for CRM data cleanup and how to implement them into your organisation.

1. Standardization

Creating rules for the definitions of how data will be inputted into the CRM and with what terms, nomenclature, vocabulary and standards, will make it easier to search for relevant information and make reports within the CRM. If concrete and strict rules aren´t implemented, employees will be unsymmetrically inputting data that will be difficult to align. As databases become larger, this becomes more and more relevant as data standards can quickly be lost.

2. Data enrichment

Completing the profiles of your customers by filling in missing information such as empty zip codes, industry data or company information can make it much easier for your sales reps to meet the needs of your customers. Furthermore, removing less used fields can also make this information clearer to access.

3. Lead-to-Account (L2A) Matching

Lead to account matching is the automated connecting of a lead to the account it stems from. This enables a vast amount of time-saving every week and marketing initiatives extremely focused on individual accounts. This leads to massive cleanup due to bulk matching as well as data maintenance through on-demand individual matching.

4. Duplicate Removal

Eliminating copies and ensuring that these copies don’t happen again is a necessity to ensure an effective CRM system. Many CRM systems contain automation features to create conditions and rules for updates that will detect possible duplicates. However, deduplication features in CRM systems are limited in their capabilities so to be most accurate it is recommended to work with a professional service provider.

5. Formatting

Something as simple as formatting issues can really hurt the quality of a CRM database. Ensuring that the correct capitalisation, sentence order or abbreviation is kept consistent can seem trivial, but they can make all the difference in an easy to navigate CRM system. Something as simple as “Head of Marketing” versus “Marketing Head”, can make filtering through the data extremely difficult.

6. Deleting Old Data

Database professionals may face this as a hoarder on a reality show that’s asked to start emptying out rooms. However, deleting contacts that no longer work at a relevant company or maybe entire companies that no longer exist, can go a long way in improving the quality of a database.

7. Consolidating Fields

Sometimes there may be multiple fields for entries that contain the same information. Reducing the amount of these types of redundancies will make it easier to look through the database and keep it concise.

8. Automation tools

It seems that even with CRM data cleanup, more and more tools are starting to appear to automatically improve database quality by, for example, detecting duplicate leads or filling in empty fields.

9. Defining a Database Maintenance Schedule

Keeping a calendar for when to undertake data cleanup may seem simple, but it can be an effective way to ensure a certain level of quality is maintained within the database. Having a concrete plan on how to clean up the database is also key, defining the responsibilities of who will undertake which part of the cleanup.

Notably, a significant degree of these activities can be automated with intelligent systems and artificial intelligence, however, manual refinement is needed. For more information on CRM data, quality management check out our page which expands on the subject.