The Power of Clean, Quality Data

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The Power of Clean, Quality Data

You invested in a Customer Relationship Management (CRM) system and have been diligent in getting the system implemented and adopted across the entire company. However, if your team is not consistently keeping the Lead, Account, Contact, Opportunity and Service Ticket data clean, you are likely missing out on the benefits of having a CRM system to begin with. How? Data quality is central to CRM effectiveness. More simply put…garbage in, garbage out.

Martin Doyle, CEO of DQ Global, found “42 percent of failed CRM projects came off the rails because of the state of the data.” When data is not kept current and clean, CRM efficiency collapses as activities collect around the wrong contact and the wrong marketing content, meaning the wrong messages go to potential buyers. Company confidence in CRM declines. 

What is the cost of poor quality data? A recent study from Sirius Decisions found that it will cost you $1 for each instance you prevent a bad record from entering your CRM system, and $10 to correct the data if it reaches the system. If the bad record goes unnoticed and works its way into the sales and marketing team’s efforts, it will cost $100 per incorrect entry. Where and how soon you address data quality has a direct impact on your bottom line.

And the effect is compounded as your company enters more records, migrates more records and integrates more applications into your system. Unless your team implements a quality system to ensure clean data, your CRM inefficiency will be followed by ineffectiveness and, ultimately, abandonment of the program altogether. 

But all is not lost. With the right tools, project management and process, you can quickly address and improve your data quality and CRM effectiveness, just follow these steps:

Step 1: Assess your data quality and its impact on your organization

Evaluate your duplicates in Leads, Accounts, Contacts, Opportunities, Support Tickets and custom objects/entities. Find the sources and impact of poor and duplicate data. Analyze the Activities and Interactions that are collecting on the wrong records that have an impact on system efficiency and effectiveness. Interview a variety of users to determine the impact of the data quality issues.

Step 2: In-depth record cleaning

Model the logic to determine the “golden record” in the Lead, Account, Contact, Opportunity and Support Ticket data sets, then model the logic to consolidate Activities and Interactions onto the golden record. Next, conduct a detailed test cleanse of your system on a sample data set. Improve the process until it perfects the records and merges the data correctly. Once the process is optimized, back up your data and merge any duplicates with the golden record. Make it a team effort to speed up the process and create an organized project process that has all users pitching in. 

Step 3: Keep data clean

Develop a discipline of data quality to keep all the hard work you put in to making the data clean in the first place. Invest in tools that keep your data clean. Run repetitive data improvement processes on specific tables on a regular schedule, because data degrades at a predictable rate. Says Doyle, “The rate of data decay is estimated at about two percent per month. That doesn’t mean a lot on paper. In real terms, industry experts suggest that almost a quarter of contacts in a regular CRM will be out of date in a year.” Otherwise, he says, your team will perform repeated data cleanses as CRM effectiveness predictively declines.

Step 4: Prevent data quality challenges at the point of entry, application integration and data migration

Consider how you input data. Are states written as AZ, Arizona or Ariz.? Are titles entered as Director of Sales, Sales Director or Director, Sales? Standardization of data format reduces the likelihood of record duplication. Employing duplicate prevention logic should trigger a warning and the record should be merged and updated immediately. 

Ensure data quality processes are implemented on all application integrations, including to ERP, and Marketing Data, and any purchased lead lists.

Step 5: Improve user involvement

Finally, create a culture where users proactively update database records if they come across changes in employment, titles or other data elements within the record. This will take training, communication and sharing the results of data quality analytics so users can see first-hand how important clean data is to maintaining information integrity. As your team members find methods to enhance your CRM database use, implement them; database and its effectiveness are only as beneficial as the time and motivation given to properly maintaining it.

The CRM data your company employs can mean a world of difference in your market credibility. User efficiency and effectiveness of your CRM system will bring bottom line results, creating longer-term and more profitable relationships with your customers. The cleaner your data, the greater potential it has to provide quality leads, critical contact information and important details about your clients. The more time and effort invested into ensuring the data is clean and focused, the greater the ROI on your CRM efforts. 

About the Author:

TopLine Strategies delivers the complete integration and development of sales, marketing and customer service technologies that enable corporate clientele to improve revenue streams and strengthen customer interactions. Our project management and consulting is designed to achieve timely delivery, 100 percent user adoption of the technologies we implement and deliver measurable returns on investments for our clients.

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