# Data Entry and Cleansing Best Practices **URL:** \ **Category:** Tips, Tricks & Best Practices\ **Tags:** crm\ **Created:** [May 24, 2024, 12:34am UTC](https://community.hubspot.com/t/data-entry-and-cleansing-best-practices/107893 "2024-05-24T00:34:29Z")\ **Posts on this page:** 7\ **Page:** 1
**Author:** ![LMiller39](https://avatars.discourse-cdn.com/v4/letter/l/d9b06d/32.png) [@LMiller39](https://community.hubspot.com/u/LMiller39)\ **Post date:** [May 24, 2024, 12:34am UTC](https://community.hubspot.com/t/data-entry-and-cleansing-best-practices/107893/1 "2024-05-24T00:34:29Z")
Hi everyone, Thought I’d post on here to see if I can receive any advice for my team. We are currently working on a large scale data cleanse and have found that we do not have a standardized process for creating contacts and other objects. For instance, we have a bulk of contacts that are missing crucial information in their record and now we must find a way to fill in thousands of missing fields without losing data. Moving forward, we would like to prevent this kind of thing from happening. Can anyone share any tips or recomendations for best practices when it comes to keeping an organized database? What kinds of things should our team standardize, and what’s the most efficient way to train our employees on these processes? Any suggestions on how to clean up the existing data would also be greatly appreciated. Thanks for the help! ---
**Author:** ![karstenkoehler](https://d10pqhm3lwygmk.cloudfront.net/user_avatar/community.hubspot.com/karstenkoehler/32/68554_2.png) [@karstenkoehler](https://community.hubspot.com/u/karstenkoehler)\ **Post date:** [May 24, 2024, 4:07am UTC](https://community.hubspot.com/t/data-entry-and-cleansing-best-practices/107893/2 "2024-05-24T04:07:10Z")
Hi @LMiller39, Addressing a large-scale data cleanse and implementing standardized processes can be challenging but very rewarding in the long run. Here are a few things I’d consider especially in HubSpot. 1. Before you start, try to separate the good from the bad. For example, you could consider removing or reviewing the following. By doing this before you start working through records, you might be able to ‘skip’ a sizeable chunk. 1. Freemail / disposable email addresses: [GitHub - disposable-email-domains/disposable-email-domains: a list of disposable email domains · GitHub](https://github.com/disposable-email-domains/disposable-email-domains) 2. Contacts where “Unsubscribed from all email is true” 3. Contacts where “Email hard bounce reason is known” 4. … 2. Define early on what the must-have fields are for each record type and place them in the left sidebar of each object: [Customize records](https://knowledge.hubspot.com/object-settings/customize-record-sidebars) 3. To avoid further damage to data quality, try to use as many of HubSpot features that help with this directly, such as: 1. Required fields in record create forms: [Customize the create form for each object](https://knowledge.hubspot.com/object-settings/set-up-fields-seen-when-manually-creating-records) 2. Filtered views showing records, by owner, who are missing one of the required fields: [View and filter records](https://knowledge.hubspot.com/records/filter-records-and-save-views) 3. Workflow notifications for when critical required fields are missing: [Create workflows](https://knowledge.hubspot.com/workflows/create-workflows) 4. Create a dashboard with reports visualizing data quality: 1. Records where required fields are missing by record owner 2. Count of records where required fields are missing 3. Count of records with missing fields by original source Generative AI had a decent answer on the change management and practical side of this as well. > * * * > > ### Standardization and Data Quality Practices > > 1. **Define Standard Operating Procedures (SOPs):** > > 2. **Use Data Validation Rules:** > > 3. **Adopt a Single Source of Truth:** > > 4. **Regular Audits and Data Quality Checks:** > > ### Training and Process Implementation > > 1. **Comprehensive Training Programs:** > > 2. **User-Friendly Documentation:** > > 3. **Feedback Mechanism:** > > ### Data Clean-Up Strategies > > 1. **Automated Data Cleansing Tools:** > > 2. **Data Enrichment Services:** > > 3. **Manual Review and Correction:** > > 4. **Batch Processing:** > > 5. **Data Integration:** > > ### Prevention of Future Issues > > 1. **Data Governance Framework:** > > 2. **Regular Training Updates:** > > 3. **Monitor Data Entry:** > > * * * Hope this helps! ---
**Author:** ![Lucila-Andimol](https://d10pqhm3lwygmk.cloudfront.net/user_avatar/community.hubspot.com/lucila-andimol/32/69276_2.png) [@Lucila-Andimol](https://community.hubspot.com/u/Lucila-Andimol)\ **Post date:** [May 24, 2024, 1:54pm UTC](https://community.hubspot.com/t/data-entry-and-cleansing-best-practices/107893/3 "2024-05-24T13:54:54Z")
Hey @LMiller39 so the best recommendations that I can give you are : - identify crucial información for the company - identifiy how this information is being created (assign responsibilities in the team) - Review or define a process for registering information (stablish mandatory information for each step) ----upto here this will prevent generating new incomplete information - Build a reports dashboard: for example, contacts without company (if you are B2B), deal without contacts, deals closed without amount…etc - Monitor the dashboard weekly - audit the processes and the CRM periodically \> this last part will hepl you identify red flags as soon as they start to arise in order to correct them in time hope this helps ---
**Author:** ![Alexa2358](https://avatars.discourse-cdn.com/v4/letter/a/919ad9/32.png) [@Alexa2358](https://community.hubspot.com/u/Alexa2358)\ **Post date:** [August 23, 2024, 12:29pm UTC](https://community.hubspot.com/t/data-entry-and-cleansing-best-practices/107893/4 "2024-08-23T12:29:19Z")
Hello everyone, thank you for opening up this topic! I was also wondering the same thing and also, does anybody have any templates for these clean-ups? Would be super helpful on getting started. ---
**Author:** ![NAdler](https://avatars.discourse-cdn.com/v4/letter/n/85f322/32.png) [@NAdler](https://community.hubspot.com/u/NAdler)\ **Post date:** [December 29, 2024, 4:08pm UTC](https://community.hubspot.com/t/data-entry-and-cleansing-best-practices/107893/5 "2024-12-29T16:08:59Z")
Hi @karstenkoehler - Could you give an example of a dashboard for point #4? We’re trying very hard to make sure that all of our data is clean after our migration over to HubSpot and we need to make sure that we have a really good visualization of our data quality. Thanks for being such a great contributor!! ---
**Author:** ![taylorsusanne76](https://d10pqhm3lwygmk.cloudfront.net/user_avatar/community.hubspot.com/taylorsusanne76/32/51717_2.png) [@taylorsusanne76](https://community.hubspot.com/u/taylorsusanne76)\ **Post date:** [October 14, 2025, 7:05pm UTC](https://community.hubspot.com/t/data-entry-and-cleansing-best-practices/107893/6 "2025-10-14T19:05:52Z")
Hi @LMiller39, Honestly, this happens to almost every team once the data pile gets big. The best fix is to set some basic standardslike required fields (email, title, company, country), consistent formats, and using picklists instead of free typing. You can also put validation rules in the CRM so incomplete records can’t be saved. For the mess that already exists, do a bulk cleanup with enrichment tools instead of trying to fill in fields manually. Additionally, I’m familiar with tool named LeadAngel can actually help a lot here, it can auto-fill missing data, catch duplicates, and make sure no incomplete lead goes into the system again. Once the cleanup is done, automation + simple rules will stop this from repeating. ---
**Author:** ![MellisaPet](https://avatars.discourse-cdn.com/v4/letter/m/edb3f5/32.png) [@MellisaPet](https://community.hubspot.com/u/MellisaPet)\ **Post date:** [February 15, 2026, 5:30pm UTC](https://community.hubspot.com/t/data-entry-and-cleansing-best-practices/107893/7 "2026-02-15T17:30:57Z")
This issue is pretty common once a team’s data starts piling up. A good approach is to establish basic standards, like making certain fields mandatory (email, [ , ]([Best Window Cleaners in Gilbert, AZ | Window Cleaning Services](https://watermelonwindowwashing.com/best-window-cleaners-in-gilbert-az/)) title, company, country), keeping formats consistent, and using picklists instead of free text entries. You can also set up validation rules in your CRM so incomplete records can’t be saved. For the existing messy data, it’s more efficient to do a bulk cleanup using enrichment tools rather than filling in fields manually. Tools like LeadAngel can be really helpful they can auto-fill missing information [,](https://watermelonwindowwashing.com/best-window-cleaners-in-gilbert-az/) identify duplicates, and ensure no incomplete leads enter the system. After the cleanup, combining automation with simple rules can prevent this problem from happening again.