Misleading, incomplete, or duplicate data is at the core of CRM product adoption, often prompted by the frustrations multiple departments face in the absence of good data. But a data quality ambassador can help.
The Challenge of Bad Data
For example, accurate information and reports are the lifeblood of an effective sales team. If accurate data is missing or not exact, how can companies create the appropriate pipeline necessary to drive business growth? How do organizations understand who their prospects and customers really are, and which contacts should receive which communications? And how can marketing teams effectively reach out to prospects in timely and efficient ways?
When poor data quality gets in the way of effective customer communications, marketing campaigns, and sales forecasting, the end result can mean lost revenue, frustrated customers, and stagnant growth.
Adopting CRM Systems and Solutions
To solve the challenge of bad data, companies investigate CRM systems and the third-party solutions that will help them maximize them. But implementing a CRM solution is only part of the equation. If the right tools aren’t leveraged properly to achieve and maintain high quality data, users, and even the company may abandon the CRM and revert to spreadsheets, or worse.
This is where being a data quality ambassador – a champion of CRM adoption and adherence to data quality processes – can be a key differentiator in a company’s ability to achieve and maintain CRM data integrity.
The Role of Data Quality Ambassador
So, what does a data quality ambassador do first? Start by putting your data first. Identify the CRM systems and solutions that are going to help you achieve your data quality goals and get buy-in from decisionmakers.
Support your cause with information. Invite potential users and stakeholders to demonstrations of products in your short-list of solutions. Download industry white papers or share statistics that show the value of implementing a data integrity platform.
Education Is Part of the Plan
Once you have buy-in for your solutions, and have brought them in-house, actively educate users. Train users on how to input data and standardize information. Create a company style guide for how data should be inputted, processes, reported, and shared. And then ensure sales, customer success, and marketing teams are adhering to processes and safeguarding best practices when working within the CRM.
Despite your best efforts to champion data quality, you can’t avoid the human factor. Some individuals may not always follow best practices and mistakes can be made. This is where proven software solutions come to the rescue. Take greater control over your data integrity processes by incorporating the right technology to support your objectives.
Best Practices for Data Quality
Here’s an overview of the methods you can enforce today to help stop dirty data in its tracks.
- Organize your data. Data profiling is all about understanding the various data elements in your database. Understand where your data comes from, how it enters your system, and who is manipulating this data on a daily, if not hourly, basis. Use this information to develop a data ecosystem that will keep data clean throughout its journey.
- Note any potential or frequent problems with data entry. Do you have automated quality checks before a new record can be saved? For example, are you implementing tools that identify a duplicate is about to be entered and either warn first or prevent the duplication entirely?
- Control your data. Data control ensures the right users have access to the right data. Do a search of how many of your CRM users also have admin access. If there are too many cooks in the kitchen, then you’re bound to break a few eggs. Limit admin access to only those who must absolutely have it.
- Establish validation rules. Add simple validation rules to keep data entry clean. Just be sure to strike a proper balance. You want to avoid implementing too many rules, which could hurt user adoption.
- Standardize your data. Are fields mapped correctly and sensibly? Are certain fields required fields? Do you want state names abbreviated to two letters rather than spelled out? Is it critical for your country field to be filled in? Do you want to standardize Incorporated as Inc. for entry, or do you have certain common abbreviations associated with your industry that you want to stick with, such as Mfg for manufacturing? Support standardization with picklists wherever possible.
- Automate data cleansing and processing. You don’t have to rely solely on “manpower” to continually clean data. Create scenarios in Validity DemandTools that you can automate with JobBuilder. Let third-party solutions like these take on the heavy lifting of CRM data cleansing and maintaining consistency among records.
- Monitor your data. Regularly check to see that the processes and plans you’ve put in place are working and don’t need to be modified. What are the numbers telling you? Create benchmark scores and processes to ensure that your data meets a specified and approved criterion.
Data Quality Is a Continual Process
Achieving high-quality data isn’t a one-and-done approach. It is an integral and ongoing program. It requires vigilance, the right team, the right technology, and the ability to make a commitment to data quality.
You are up for the challenge! Be a data quality ambassador for your organization. Put high quality systems and solutions in place and ensure your organization is on a successful path to achieving optimal data integrity.