salesforce data quality

5 Top Salesforce Data Quality Hacks to Clean Your Org

If you want to get scared, take a minute to learn about the amount of revenues that your business could lose due to poor data. IBM estimates that dirty data costs the U.S. economy more than $3 trillion every year. Meanwhile Experian’s best guess is a 12% annual revenue loss thanks to bad data alone.

Naturally, that’s not money you want to lose. It seems so simple to keep your data clean, and yet the opposite tends to be the case. Did you know that according to Salesforce’s best guess, 71% of your data will become outdated or obsolete within the next 12 months?

The potential consequences are devastating:

  • You’ll lose significant revenue, as outlined above.
  • Your salespeople will have less accurate information as they communicate with customers.
  • Your automated communication flows might be segmenting or sending out messages to the wrong audiences.
  • Your customers will become confused or even alienated because of bad personalization.

That’s a massive problem. Businesses who don’t get their data under control can suffer massive losses in both trust and revenue, not to mention effectiveness. To remain competitive and continue growing, you need to get a handle on your data quality.

Some of that requires comprehensive organizational strategy. The qualities of good data have to be preached from the mountaintop and integrated into daily business processes. That type of strategy requires time and effort, along with leadership buy-in. Fortunately, you don’t have to wait for that to happen.

In fact, companies using Salesforce can leverage the integrity of their data over time through a number of easy tips. They’re simple, approachable, and easy to implement. These are our top 5 Salesforce data quality hacks.

1) Standardize Your Data Entry

The first hack may also seem to be the most obvious. Still, it’s importance can’t be overstated. Put simply, data quality is impossible if you don’t have standardized data entry practices.

The classic example in this tends to be the title of an HR director that might be a prospect in your Salesforce database. Consider the possibilities:

  • HR Director
  • Director of HR
  • Human Resource Director
  • Human Resources Director
  • Director of Human Resources

There might even be a few more. When you try to segment your data by job title, these five might well be considered five different occupations. A simple naming convention for job titles, capitalization, required and optional fields, and so on can go a long way towards avoiding confusion and reporting errors.

Of course, a data entry standard still has to be followed reliably by all with entry access. That might require training or the support of technology to minimize errors and maximize data quality.

2) Integrate Data Quality into Customer Communications

Data quality issues don’t just happen at the entry point. They can occur at any point in time during the customer journey. Even the best data, as seen in the 71% stat above, can become bad over time when not treated correctly.

A good way to avoid both initial quality issues and outdated data is to integrate a quality emphasis into your customer conversations. Depending on your sign up process, that might mean email verification after filling out a lead form to ensure the contact info is just right. Of course, it also goes beyond that setup.

Every person communicating with customers should be trained to verify current information. It might be as simple as confirming that the current job title is still valid, or ensuring that the spelling of the last name is right. Regardless, the key here is that every touchpoint should be an opportunity for data quality improvement.

That’s not always easy. In fact, it may feel counterintuitive. Still, it helps you build a database that isn’t just right on the onset, but remains that way over time. You can’t entirely avoid data churn. You can, however, do your best to stay on top of that churn and minimize inaccuracies that inevitably occur over time.

3) Build Specific Data Quality Responsibilities

You know the old saying? If you don’t know how to solve a problem, appoint someone else to take care of it. There’s actually a surprising amount of validity to that. Someone with ownership over data quality will take the process more seriously, building more credibility and expertise over time. It can only help the accuracy of your Salesforce contacts.

In the best case scenario, if you have a Salesforce quality assurance manager whose job this specific process will become. Most companies, of course, don’t have that luxury or business. Fortunately, you don’t have to. Simply making the data quality responsibility part of the job description of a technology manager could accomplish the trick.

Still worried about workload? It can also be split up among multiple members within the admin center. That might mean housing dedupe processes in the IT department, and the customer data communication mentioned above in sales management. That way, each job gets done right without overloading a single professional with an existing full-time job.

Related: when data quality begins to lack, look for the reasons behind it. It’s not necessarily the most motivating task, and someone may simply be de-prioritizing it as a result. Individual data quality recognition and awards can go a long way towards restoring that motivation. Between responsibilities and recognition, you can build a culture of data quality.

4) Set Up Dedupe Processes

Besides human errors during data entry and outdated information, duplicates tend to be a significant problem for organizations of every size and industry. It’s easy for two salespeople to enter the same prospect into Salesforce simply because they learned about them from a different source. When the same prospect fills out the same lead gen form twice from different devices, the same problem tends to occur.

Fortunately, Salesforce makes it easy to check for these duplicates. You just have to know how to set it up right. The software provider suggests four processes for deduping your database:

  • Manage duplicates one at a time. Salesforce allows you to set up dashboards where you can easily view potential duplicates and either merge them or simply delete one of the two.
  • Manage duplicates globally. Advanced users can set up automatic dedupe jobs that run every time a new record enters the database. You can either set up reports to monitor them, or take automatic action (such as deletion) as needed.
  • Duplicate detection and handling processes. These processes allow you to not just detect duplicates but also find matches that are ripe for merging. You can define how broad a match can be before it is considered a duplicate.
  • Custom duplicate management. When it comes to database management, no two organizations are the same. Custom duplicate management helps you set up the individualized rules you need to avoid accidentally flagging or deleting valid records.

Each of these processes requires a different level of setup and management. Some are simpler, while others are more complicated. Still, setting them up will help you begin to remove duplicates without significant manual error. Now there’s a hack that we can all buy into.

5) Implement Some Data Tools

Finally, Salesforce has distinguished itself from its competition through integration with a number of third-party tools that help you keep a cleaner database. Identify what your biggest dirty data issues are, then find the tools you need to take care of them specifically. Just a few of the many options include:

  • DupeCatcher, as its name suggests, catches duplicate records at the time of data entry. Helpful and saves some time in the process.
  • DupeBlocker is the equivalent to DupeCatcher, just with web forms. Prevent someone filling out the form multiple times from becoming multiple records.
  • DemandTools can both build comprehensive de-duping processes and cleanse your inaccurate data over time. It’s a comprehensive solution designed for data quality.
  • Case Merge Premium allows you to merge cases that are duplicates of each other or have converged. 
  • Data Loader for Salesforce allows you to mass import new records, preventing the danger of human error in the process.
  • AddressFree automatically validates addresses to make sure your mailing efforts get matched to the USPS database.

Hundreds of tools like these allow you to improve your data quality. Browse through the Salesforce appexchange to find those that solve the greatest current needs for your organization. Who needs a headache over dirty data when automated tools can help you clean it instead?

Build a Better Salesforce Org

Salesforce’s greatest strength is its comprehensive nature. Organizations in all industries and all sizes can leverage it to grow their revenue and customer base. Of course, that comprehensive nature also introduces data quality issues that are impossible to ignore or overlook.

To maximize your benefits from Salesforce, you have to get it right. Data quality is hugely important in that process, Ebsta eradicates the reliance on your sales reps to enter data with our next generation email integration solution, request a demo here.