Small companies face numerous challenges as they strive to grow and scale effectively. One aspect that often gets overlooked, yet holds paramount importance, is maintaining clean CRM data. While larger organizations may have more resources to allocate to CRM management, the fact that small companies have limited resources is precisely the reason that they must ensure their data is accurate and up to date.
Bad data costs US companies up to $3 trillion every year. But only 3% of companies meet basic quality standards.
Clean CRM data allows smaller companies to optimize their resources more effectively. With accurate data, they can identify their most impactful leads and accounts and focus their marketing and sales efforts on the right targets. For example, a small e-commerce company can use clean CRM data to create targeted email campaigns for their most engaged customers, leading to higher conversion rates and increased sales. Keeping CRM data clean also helps small businesses avoid record-based pricing pitfalls by ensuring they are only paying for the data they need and use.
Another benefit of clean CRM data is that it makes your data easier to use. When employees can easily access and understand the data, they are more likely to use it to its full potential. A cluttered and confusing CRM system will lead to wasted time and resources and frustration among staff.
Lastly, maintaining clean CRM data enables smaller companies to gain a comprehensive top-down view of their customer experience. With accurate data in place, small businesses can better understand customer behavior, preferences, and pain points, allowing them to make data-driven decisions and tailor their offerings to meet customers' needs. For small companies entering a period of potentially rapid growth, a clean and reliable CRM database positions them to capitalize on opportunities and grow as quickly as possible. On the other hand, when data isn’t clean, small companies in particular can suffer many negative effects.
A dirty CRM database can have significant negative consequences for smaller companies, hampering their growth and competitiveness in the market. The implications of inaccurate, outdated, or incomplete data can range from lost revenue opportunities to increased operational costs and decreased employee productivity.
One of the most direct consequences of an unclean or disorganized CRM database is its impact on sales and marketing efforts. With inaccurate information, smaller companies will struggle to identify and engage their target accounts effectively.
This could lead to misdirected marketing campaigns and resources being wasted on low-quality leads.
Example: A small B2B services company with outdated and unreliable CRM data might invest valuable time and money targeting clients who are not a good fit. As a result, the team will miss out on potential deals with the high-value prospects they could have focused on instead. Had they had reliable CRM data and activity logs, they would have been able to disqualify the bad leads early in the process and avoid wasting resources pursuing them.
Another negative impact of a dirty CRM database is the inefficiency it brings to daily operations. Cluttered or low-quality CRM data makes it harder for employees to locate and process essential information, leading to frustration and decreased productivity.
Further, inaccurate data can cause communication breakdowns between departments, resulting in missed deadlines, duplicated efforts, and even tarnished customer relationships.
Example: Duplicate CRM data could cause miscommunication between sales and development teams at a small software development company. This would result in misaligned expectations, and, ultimately, customer dissatisfaction when the deliverables don’t meet those expectations.
On the sales side, at a company that does not do a good job of limiting duplicates in its CRM, two sales reps may find themselves stepping on each other’s toes when they are both assigned to separate duplicate records in the database.
While these issues would certainly be headaches in a bigger company, in smaller companies they have a more noticeable impact on the company’s ability to grow. Data issues cause hangups in automations that drive operations within your business. These issues cause employees to constantly pause what they are doing to address data issues in the CRM.
In addition to operational inefficiencies, a disorganized CRM database can lead to increased costs in a variety of areas for smaller companies.
First, there are the operational inefficiencies we just discussed. When your employees are wasting their time undertaking data cleaning and maintenance tasks, double-working accounts, or generally spending time sifting through unreliable CRM data, more of your payroll is going towards inefficient use of time.
Additionally, as many CRM systems operate on a record-based pricing model, businesses may end up paying for data that they don't need or use. This can be particularly detrimental for smaller companies with limited budgets, as these unnecessary costs can divert resources away from more crucial growth initiatives.
In short, wasted time means missing out on everything else your teams could have spent their time doing instead of wrestling with CRM data.
Smaller companies have limited resources. That means that they need to choose their projects and strategies wisely to make the most of the resources that they do have. When decisions are based on bad data, they will delegate employees and prioritize projects incorrectly. On the other hand, a larger company has more wiggle room with its resources, and time spent chasing a bad project or task doesn’t impact it so noticeably.
A dirty or disorganized CRM is sure to lead to errant reporting, and in turn, bad decision-making based on those reports.
Example: If a small business has unstandardized job titles, a CEO at a company could show up in the database under dozens of different titles including: CEO, C.E.O., chief executive officer, founder/CEO, founder & CEO, co-founder & CEO, etc. If the marketing team decides to launch an outreach campaign to CEOs for potential partnerships and it does not segment for every single variation, it will underestimate the number of contacts for the campaign. Worse, it will omit many potential contacts in its outreach.
Not only that, but the team might be barking up the wrong tree altogether. It might be that chief marketing officers or chief technology officers were a better target for the campaign based on the contacts present in the database. But because the database wasn’t accurate, the team did not even realize this.
Without accurate data insights, it becomes challenging to make informed decisions, identify trends, or anticipate customer needs.
A dirty database also makes it difficult to implement automation processes that can streamline operations and support growth.
Example: A small healthcare startup with bad data might struggle to analyze patient records to predict future demand, develop targeted marketing campaigns, or implement automated appointment reminders. Combined, these issues will ultimately hinder its growth potential.
With unclean data, your team is hamstrung, handling many tasks manually that would be better handled by automated systems.
Improving CRM data quality is crucial for small to mid-sized companies looking to optimize their operations and grow their businesses. By maintaining accurate, up-to-date CRM records, these companies can make informed decisions, streamline processes, and better serve their customers. In this section, we will discuss various strategies small to mid-sized companies can employ to enhance their data quality, including:
Firstly, small to mid-sized companies should focus on identifying and removing duplicate records from their CRM databases. Duplicates can cause confusion, waste resources, and hinder effective communication. By implementing tools or manual processes to find and merge duplicate records, companies can avoid these issues and enhance data accuracy.
Example: A small marketing agency can use a CRM system's built-in deduplication tool to identify and merge duplicate client records, ensuring that each client has only one unique entry in the database. This keeps sales, support, and customer success reps from stepping on each other's toes, or missing context that had been split up between multiple accounts. In the end, this means better experiences for customers.
Businesses should identify and remove useless records and inactive contacts from their CRM databases. By regularly reviewing and purging unnecessary or outdated records, companies can reduce costs associated with record-based CRM pricing and improve overall data quality.
Example: A small e-commerce business can remove records for customers who haven't made a purchase in several years, ensuring that its database only contains relevant and active customer information.
Standardizing data in critical fields is also an important aspect of maintaining CRM data quality. By implementing consistent data entry practices and formats, businesses can ensure that their data is easily searchable, sortable, and usable.
Example: A small manufacturing company can create standardized formats for fields like addresses, phone numbers, and product names, making it easier for its sales team to search for and access relevant information.
Segmenting and categorizing CRM data can further improve its quality and usability. Organizing data into relevant categories and groups allows companies to analyze, track, and target specific customer segments more easily.
Example: When a small software company segments its data based on customer industry, size, or product usage, it can create targeted marketing campaigns for each segment.
Updating and enriching quality records is another essential step to improving CRM data quality. Companies should regularly review their data to identify gaps or inaccuracies and take steps to fill in missing information or correct errors. This may involve using third-party data enrichment tools or conducting manual research to gather current information on contacts and accounts.
Example: A small B2B company can use a data enrichment service to append missing contact information, such as email addresses or job titles, to its existing CRM records.
Training team members on data standards and best practices is critical to maintaining CRM data quality. Companies can ensure that their CRM data remains clean and reliable by educating employees on the importance of data accuracy and providing clear data entry and management guidelines.
Example: A small financial services firm can hold regular training sessions for its staff, reinforcing the importance of consistent data entry and emphasizing the consequences of poor data quality.
Finally, automating data cleaning processes can help small to mid-sized companies maintain CRM data quality more efficiently. By implementing automated tools or workflows, businesses can reduce manual effort, minimize human error, and ensure that their data remains accurate and updated.
Example: A small retail business can use automation tools to automatically update customer contact information, verify email addresses, or flag duplicate records for review.
For more guidance on improving your data quality, check out our CRM Data Quality Checklist.
Insycle is an extremely helpful tool for smaller companies that are looking to improve the quality of their data, make the most of their understanding of customers, and put themselves in a position for rapid growth.
Let’s examine some of the ways Insycle can help.
Insycle offers deep and flexible duplicate identification and merging features.
The Merge Duplicates module allows you to identify duplicates using any field in your database as a matching field. You can use exact match or similar match to catch more duplicates. You can also ignore aspects of any field, including symbols, numbers, white space, or common terms like “Inc.” or “LLC.”
Identifying duplicate contacts by first name, last name, and company name in Insycle
When merging, you have complete control over the resulting master record. You can choose the master record based on rules. In the example below, the resulting master record will have the highest number of marketing emails clicked. If one cannot be identified, Insycle will move down to the next rule on the list until a master record is set.
Setting rules for determining the master record in Insycle
For more advanced use cases, you can choose how data is retained when duplicates are merged on a field-by-field basis. You have options like appending values from all records, choosing which record’s data to retain based on rules, or simply pulling the data directly from the resulting master record.
Choosing data to retain after merging on a field-by-field basis with Insycle
With Insycle, you have complete control over how your duplicate records are identified and merged. As a result, you can catch more duplicates and enjoy a cleaner, more usable CRM database.
Smaller companies need to focus on purging clutter so that they don’t spend time marketing or selling to prospects that they never would have prioritized, had the database been accurate.
Insycle’s Customer Data Health Assessment tracks data issues automatically, and includes numerous categories that can help you identify low-quality records that may be good candidates for purging.
One of these categories is Incomplete Data, where you can track records that are missing critical fields. These records might be low-value clutter and thus good candidates for purging.
Tracking data issues on an ongoing basis with Insycle's Customer Data Health Assessment
Additionally, you can build custom templates to track data traits that are important to your organization.
Insycle makes it easy to evaluate data in specific fields, view the variations in that field, then update and standardize where necessary.
In the example below, we are selecting all U.S. state field variations that represent New York state. Once you’ve made your selections, you can bulk-update all of them to one standardized version.
Choosing US state variations to standardize in Insycle
By standardizing data, you can improve segmentation and reporting. Then you can make smart decisions and prioritize the right activities for your small or mid-sized company.
With Insycle, you can bundle individual templates into Recipes. These recipes can then be automatically executed in the order listed, or even automated to run on a set schedule.
Managing data maintenance templates in Insycle
Recipes allow companies to define a series of steps to perform specific actions—such as cleaning up contact records, associating records, or analyzing your data. By creating Recipes, you provide your teams with definitive processes they can follow for data maintenance.
Insycle allows you to automate individual templates and Recipes to run on a set schedule.
Automation data maintenance templates in Insycle
You can automate Insycle templates to run hourly, daily, weekly, or monthly. You can also add Insycle Recipes directly to HubSpot Workflows so that your data is cleaned immediately after it is collected and before your first communications go out to customers.
Clean CRM data is crucial for the success and growth of small to mid-sized companies. Insycle is the perfect tool to help these businesses effectively clean and maintain their CRM data. With its comprehensive suite of features, Insycle enables smaller companies to identify duplicates, remove useless records, update and enrich data, standardize critical fields, segment and categorize data, and automate data cleaning processes. By utilizing Insycle, smaller companies can efficiently tackle the challenges of maintaining clean CRM data, allowing them to focus on growth and delivering exceptional customer experiences.
Beyond its CRM data cleaning tool capabilities, Insycle is a complete solution for data operations and collaboration. It offers an intuitive platform for managing, analyzing, and sharing data across teams and departments, fostering better organizational communication and decision-making. With Insycle, small to mid-sized companies can improve their CRM data quality, streamline their data operations, and build a data-driven culture that empowers employees to make informed decisions and drive success.
Don't let dirty CRM data hinder your success. Discover the benefits of Insycle and start making data-driven decisions that propel your business forward.