Say Goodbye to Dirty Data With These Salesforce Data Cleansing Best Practices

Clean Data

Congratulations! You’ve made the (in our opinion) wise decision to invest in Salesforce. You’re probably eager to get your implementation underway and to take full advantage of all of Salesforce’s innovative features and functionalities but, before you do, we need to have a conversation about dirty data.

If you’ve worked with any type of software system in the past, you’re likely already familiar with dirty data and its associated challenges, particularly how it negatively impacts productivity, reporting, and revenue.

What you might not know is that poor data hygiene can also affect user adoption because it immediately calls into question the credibility of your data, which can, in turn, lead to a crisis of confidence in your end users. It’s a reasonable apprehension — after all, why should your end users invest time and energy into embracing a new system when they know that dirty data will actively counteract the quality of their work?

Clean Data

Whether you’re starting fresh with Salesforce or doing some data-related spring cleaning in your existing system, you don’t want to put dirty data into a nice, clean system — after all, you’ve spent a lot of money on this investment, so you wouldn’t want to gum up the works right out of the starting gate. Consider this your opportunity to clean out the proverbial data closet and start your implementation on the right foot.

A Two-Pronged Approach to Salesforce Data Cleansing

A strong Salesforce data cleansing strategy should consist of two key components: reactive cleansing and proactive cleansing.

Reactive cleansing, so-called because it refers to the cleaning of preexisting data, should be your first priority. Many new Salesforce users are coming from legacy solutions and already sit on a mountain of customer and product data pulled from various sources. Before it can be entered into Salesforce, this data must be sorted and cleaned, which can be a challenge if it’s spread out across multiple systems. Therefore, the first step to cleaning your data is to consolidate it.

Say, for example, you have customer data spread out across a dozen different spreadsheets. Rather than review each individual spreadsheet for misspellings and outdated information, condensing them into one master spreadsheet makes it easier to discover duplicates and sniff out any inaccuracies or discrepancies.

Once you’ve consolidated your data and set to work cleaning it up, the next step is to standardize data formatting within your central repository. One way to standardize your existing database is to create data filters that refine data on the basis of how it is used. Creating standards not only helps ensure that all data entries are complete, consistent, and accurate — it also gives your end users a formal process for how data is to be entered into the system in the future.

With your data house now in order, you’re ready for part two of your Salesforce data cleaning strategy: proactive cleansing. Proactive cleansing refers to the process of ensuring good data hygiene for any new data entering your Salesforce implementation.

A key element of proactive cleansing is to identify the input sources of your data, such as:

  • End users who create data
  • Administrators who import data or manage integrations from other systems that create data
  • Web forms that contain publicly generated data, which is then entered into your system
  • Partner portals where vendors and partners can create data
  • And so on

The more cooks there are in the data kitchen, the more opportunity there is for dirty data to be generated, which has a net negative effect on overall Salesforce data management. You can take vetting input sources a step further by creating different rules for each individual path — for example, if you’re a B2B business, you could create a rule that prevents web forms with Gmail usernames from creating data. Or, if it’s a partner portal generating leads, you could implement a rule that prevents the creation of duplicate leads in the system.

Another way to simplify the process of isolating and eliminating duplicate data is to invest in a third-party application built for that exact purpose; for Salesforce data management, we recommend Validity DemandTools, which is available through AppExchange, or creating duplicate rules, which is a Salesforce-native functionality.

Dirty data is sometimes the result of malicious behavior but, more often than not, it’s the product of human error. In fact, human error is the leading cause of data inaccuracies, coming in at 49% according to Experian’s 2018 Global Data Management Benchmark Report — and minor mistakes, such as spelling errors, have the potential to cost your business thousands of dollars. Therefore, it’s in your best interest to automate the data cleansing process. Salesforce offers native functionality to merge and clean Accounts, Contacts, and Leads, and recommends a number of free and paid data cleansing applications such as Cloudingo and Duplicate Check for Salesforce for larger merges.

Finally, if you suspect that the root cause of data inaccuracies within your organization is, indeed, malicious behavior, you can implement validation rules. Per official Salesforce documentation, “Validation rules verify that the data a user enters in a record meets the standards you specify before the user can save the record.” Validation rules give you greater control over what data enters your system and can be a powerful tool to weed out data from malicious sources.

You can also validate users on an individual basis to ensure that they’re actually a person and not a bot with user verification tools such as CAPTCHA and reCAPTCHA or by setting user permissions within Salesforce.

In-House vs. Outsourced Data Cleansing: Not an Either/Or Proposition

We’ve talked in previous posts about the importance of working with a partner to handle any type of Salesforce project; we even wrote an entire eBook on how to find the perfect partner. 

But, when it comes to data cleansing and Salesforce data management, we advise that you hold off on outsourcing your work — at least, initially. You see, consulting firms provide a lot more value in terms of introducing proactive to ensure Salesforce data quality rather than reactive measures to clean existing data.

Reactive cleansing is best handled in-house for a couple reasons: First and foremost, there’s the cost. Working with a consulting firm, whether it’s on an implementation or for custom application development, requires a significant financial investment. Most organizations are capable of handling reactive cleansing on their own, which means your money is best saved for other, more challenging projects. In fact, the only time you really should approach a consultancy for reactive cleansing is if you lack the bandwidth to tackle it yourself.

Second, there’s always a subjective element to data cleansing. A consultant can apply rules, logic, and matching techniques to identify data which is definitively clean, but they often lack the nuance that comes with having an intimate knowledge of the business and its customers to pinpoint minor issues. For example, a customer service representative would be better equipped to detect duplicate data in the form of a customer whose information has been entered into the system twice — once under her maiden name and once under her married name — due to their preexisting relationship with that customer. When it comes to reactive cleansing, insider perspective is exceptionally valuable — after all, it’s your data, and you know it best.

Once you’ve managed the reactive cleansing side of Salesforce data management, it’s time to call in the experts. Salesforce consultants are best suited to assist with proactive cleansing because they have the experience and expertise to help you to implement and enforce effective data cleansing policies; at VennScience, we offer ongoing data hygiene strategy consulting as part of our managed services engagement. We tailor our approach to data cleansing and our level of involvement on a client-by-client basis, guaranteeing a hand-crafted, custom-made strategy that meets the specific needs of your organization.

Let VennScience be the copilot on your Salesforce data cleansing journey; talk to one of our representatives today.

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