Jul 11, 20217:39 AM - edited Jul 11, 20217:40 AM
HubSpot Employee
How often do you clean your contacts database?
We’re in a data-driven era, where datasets are shared between marketing, sales, and customer service teams to increase organizational effectiveness and facilitate alignment. When you have high levels of inconsistent data, it’s not just one team taking the hit. It’s everyone. The entire company. The fallout from that bad data extends to every corner of your business that the data touches. With that in mind, how often do you currently audit and clean your contacts database? Once a month? Every quarter? Once a year? What does the process look like? Share your thoughts and current schedule.
I see the value of routinely checking and maintaining my contact database on an individual basis. Ideally, I carry out this procedure once a month. However, depending on how big my database is and how quickly I gather data, the frequency may change. Finding and fixing discrepancies, duplication, and out-of-date material is usually part of my approach. This guarantees the accuracy and dependability of my data.
I may clean their contacts database periodically, perhaps every few months or annually, to remove outdated or redundant information, update contact details, and ensure that the database remains accurate and useful.
Does anyone use any third party tools to bring in additional data about their contacts such as social media handles, locations or other? I am keen to understand what is the art of the possible to ensure I have as much information as I can about my customers. TIA
Regularly auditing and cleaning the contacts database, typically on a quarterly basis, helps ensure data accuracy, eliminates duplicates, validates information, and facilitates segmentation, aligning the data for effective use across teams and minimizing the impact of bad data on business operations.
We should be conducting a comprehensive database cleanup at least every 3 months or quarterly. This process involves removing duplicate or outdated entries, updating contact information, and ensuring compliance with data protection regulations. In short, keeping the contact information and database up to date. A clean and well-maintained contacts database enhances the efficiency of marketing campaigns, improves customer segmentation, and fosters better engagement with your target audience.
Inactivity: If the contact has not visited your website or opened your email for a long period of time, such as more than 180 days, they may be unengaged or irrelevant.
Email aliases: If the contact’s email address starts with an alias, such as info, support, hello, test, sales, office, postmaster, administrator, no-reply, and so on, they may not be a real person or a decision-maker.
Bounced emails: If the contact’s email address is invalid or no longer exists, and your emails are bouncing back, they should be removed from your database.
Unsubscribed contacts: If the contact has opted out of receiving your emails, they should be excluded from your database, as sending them emails may violate spam laws and damage your reputation.
Negative feedback: If the contact has expressed dissatisfaction, complaint, or request to stop contacting them, they should be removed from your database, as they may harm your brand image and word-of-mouth.
Quarterly seems sufficient as any more frequent may not give marketing efforts enough time to provide insight and annually is too long; could lead to unsubscribes if the contact isn't receiving the right info at the right time.
The frequency of auditing and cleaning your contacts database can depend on several factors, including the size of your database, the rate of data entry, and the importance of data accuracy to your business. Here are some common approaches:
1.Continuous Monitoring:
Implement continuous monitoring processes to catch and correct data inconsistencies in real-time. This can involve automated tools and systems that validate data upon entry.
Event-Driven Audits:
Trigger audits during specific events, such as a major marketing campaign, product launch, or system integration. These events can lead to an influx of data and are opportune times to ensure data quality.
Proactive Data Maintenance:
Encourage proactive data maintenance by different teams. For example, sales and customer service teams can be responsible for updating contact information during customer interactions.
The process of auditing and cleaning your contacts database typically involves:
Duplicate Removal: Identify and merge duplicate records to ensure a single, accurate representation of each contact.
Data Standardization: Standardize formats for fields like names, addresses, and phone numbers to maintain consistency.
Invalid Data Removal: Remove incomplete or invalid records that may hinder effective communication.
Verification of Data Accuracy: Cross-check contact information against reliable sources to verify its accuracy.
We make sure our contact list is accurate by checking it every three months/ Quarterly . We use both automated tools and human checks to catch any mistakes or outdated info. This helps us keep our data in good shape without making it a huge task for our teams. Everyone in their own department is responsible for keeping their contacts up to date, creating a culture where everyone plays a role in maintaining accurate information.
The specific process for auditing and cleaning the database will depend on your organization's needs and the tools you have in place. However, regular maintenance of your contacts database is crucial for maintaining the integrity of your data and ensuring that it continues to be a valuable asset for your organization
Cleaning and maintaining a contacts database is crucial for ensuring the accuracy, relevance, and effectiveness of marketing efforts. However, the frequency of cleaning a contacts database can vary based on several factors, including the size of the database, the rate of data acquisition, and the quality of data sources.
There isn't a one-size-fits-all answer to how often a company should audit and clean its contacts database. Instead, here are some considerations to determine the appropriate cleaning frequency:
Regular scheduled cleanings: Establishing regular intervals for database cleaning can be beneficial. For instance, some companies opt to conduct a database audit quarterly, semi-annually, or annually to ensure consistent data hygiene.
Data acquisition rate: If your company acquires data at a high frequency, whether through lead generation campaigns, events, or other sources, it might necessitate more frequent cleaning to manage and update the influx of new information.
Monitoring data quality: Monitoring the quality of data continuously is crucial. Implementing automated tools and processes to identify and correct data inconsistencies, duplicates, outdated information, and inaccuracies can help maintain data quality on an ongoing basis.
Changes in business operations: If your company undergoes significant changes such as rebranding, shifting target demographics, or altering products/services, it might necessitate more frequent database cleaning to ensure alignment with these changes.
Performance and analytics: Assessing the impact of bad data on performance metrics can guide cleaning frequency. If you notice a decline in marketing campaign effectiveness or other key metrics due to data issues, it might signal the need for more frequent cleanings.
In summary, while there's no set rule, a proactive approach involving regular monitoring, scheduled cleanings, and continuous data quality checks can help maintain a healthy contacts database. Adjusting the cleaning frequency based on the specific needs and dynamics of your company's data management practices is key to maximizing the value derived from stored contact and customer information.
Actually it spend upon the business needs and bandwidth of the team handling the data. In our business, we aim to audit our database every 6 Months but cleaning is the regular ongoing process. This is crticial process in our organisation as this involves teams from all functions - Marketing, Sales, CR Teams. Regular cleaning exercise maintain data accuracy and fostering organisational effectiveness.
Companies are supposed to evaluate their data once a month (ie., 2 days from the end of every month). This would enable them to make corrections on time. Especially in a sales-driven firm where every critical decision that aids budgeted revenue is driven by insights from field market data, this strategy is rigorous but neccessary.
We closely monitor engagement and deliverability with each campaign. Based on engagement at 3, 6, 9 and and 12 months, we take different actions to try and re-engage them before rolling them off our active list after 12 months.
Customer-centric organisations understand that well organised customer data drives meaningful, value-add conversations and customer experiences. With this in mind, data should be continuosuly reviewed and monitored, and audited at minimum quartely.
I Think that the criteria for database cleaning should be the average purchasing period osf the customers x2. Meaning that if we take into account that we want the purchasing behaviour to be cyclical process and we strive to have returning customers, not every customer or prospect that doesn/t make the first purchase in the first cycle should be excluced from the DB. instead they should enter an additional revival or nurture cycle. if nothing works after that, we should consider them to be excluded. The other criteria should be scoring and customer idleness, meaning that the scoring criteria should define the realistic expectation for purcasing behaviour and if it indicates that the customer is reasonably turning the other way they should be excused from the DB. Also works with the idleness criteria, especially if we have an incentive based campaign that attracts more people than we expected and we can reasonably believe that they came for the prize but not for the product.
General cleaning and database refreshment such as contact data update or taking consideration of career movements (B2B) should be set up as an automated process on a 6mths or 1yr basis depending on the volatility of the segment.
I believe the contact database should be reviewed and cleaned every six months but, the specific frequency may depend on the size of the database, the rate of data accumulation, and the criticality of accurate information for effective operations. It's crucial to establish a cleaning schedule that aligns with your organization's needs and data quality objectives.
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