How Duplicate Corrode Your Salesforce Data and What You Can Do About It

4 Tips How Duplicate Corrode Your Salesforce Data What You Can Do

While Salesforce is a very powerful sales and marketing tool, its effectiveness depends on the data you put into it. If you have a lot of data quality issues, such as duplicates, you are missing out on all of the powerful features Salesforce has to offer. Since duplicates have a negative impact on the data in your Salesforce environment, we will take a look at some of the most common issues attributed to duplicates and what you can do about these problems. 

Issues With Data Quality

Without the necessary Salesforce duplicate management processes in place, you will experience inconsistent data issues, which brings on an entirely new set of issues on its own. For example, you might think that you have reached your lead generation goals for the quarter, but the actual number of leads might be a lot less than what Salesforce is telling you because of all the duplicates. There are many other issues caused by duplicates such as: 

  • Inconsistent data – One of the biggest ways this problem manifests itself is that the same exact data exists in different formats and across various tables. 
  • Management time – If your Salesforce duplicate management process is rule-based, somebody will need to spend time updating those rules every time a new duplicate is detected. 
  • Lingering impact – If your sales team has already been burned by duplicate data at least once, they will need to spend additional time double-checking all of the information in Salesforce. 

Lack of a Single Customer View

When your sales team reaches out to prospects and leads, they are relying on the information in Salesforce to increase the conversion rate. However, if customer data is scattered all over the place, this could be a big problem because they will need to go from one record to another and collect all of the necessary pieces of information to get a single customer view. Not only does this make your sales team’s job a lot harder, but it also makes them less productive, especially since providing a single customer view is one of the main features offered by Salesforce. 

A lot of companies are dealing with these sorts of issues. In fact, 

 42% of sales reps feel they don’t have enough information before making a call, and working with patchy, inaccurate data further compounds their ability to do their job well. By improving your duplicate Salesforce management, you enable your sales reps to be more efficient and use their time wisely when connecting with prospects. 

Duplicates Hinder Your Work With Data

In the previous section, we talked about how duplicates make your teams less productive, but they also cost you money. One interesting example of this is the Children’s Medical Center Dallas, which engaged an outside firm to help clean up their duplicate data. The initial duplicate rate was 22%, and the firm managed to reduce it all the way down to 0.2%.

The data revealed that, on average, a duplicate medical record costs the organization more than $96. While the exact costs of duplicates will vary from one company to another, keep the following general rule in mind: it costs $1 to identify a duplicate record, $10 to remove it, and $100 per record if you do nothing about them. 

What we have seen so far is that duplicates can cost your business to lose value in more ways than you think. Try getting a handle on your duplicate issues before the costs start to get out of control.

How to Improve Your Data Quality 

The first thing you need to do is get an understanding of just how to bug your duplicate issues really are. There are some Salesforce deduplication apps out there that give you an instant data health overview which will give you a sense of where you stand. If you notice that your problems are really big, it may be a good idea to do a data quality assessment. Try treating data quality as a process.

Creating value from data is more than just delivering “one-off” insights. While an established data management system helps, businesses need to cleanse and maintain their data and build rigor around these practices. True success requires operationalizing your data and continually reevaluating how your data can work for you and what data and data analytics processes serve your business. Everything from data storage to analysis to application needs to be streamlined, managed, and automated. 

Next, you should start cleansing your data. Inaccuracies or inconsistencies in your data will harm your data quality and prevent you from using it for effective decision-making. Over time, data sets become riddled with out-of-date or incorrect information as customer data changes or information is improperly added to your database.

Data cleansing is the process of correcting incomplete or inaccurate information, fixing formatting issues, and more. Issues in your data set that require data cleansing include:

  • Typos in data entries
  • Incomplete data fields
  • Inconsistent formatting of addresses or contact information
  • Out-of-date contact information
  • Duplicate data entries

Addressing incorrect information in your database provides you with more confidence that your data provides an accurate picture of your customers and allows you to make appropriate business decisions as a result. There are a variety of tools available to help you cleanse your data. These tools include email address list cleansing, real-time address verification, and more to help you cleanse your database of errors and also prevent incorrect information from entering at all.

Data Quality is a Journey

All organizations today confront data quality problems, both systemic and structural. Neither ad hoc approaches nor fixes at the systems level—installing the latest software or developing an expensive data warehouse—solve the basic problem of bad data quality practices. Your company needs a roadmap that can be used by all parties involved to implement a viable data and information quality management program. Create a practical guide that is based on rigorous research and informed by real-world examples that will include the challenges of your particular data management and provide the principles, strategies, tools, and techniques necessary to meet them.

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