Maintaining Clean Data in Your Salesforce Org
For many companies, maintaining clean data in your Salesforce org is akin to working out for many humans. Many companies resist getting the habit off the ground, even though they recognize the benefits. People don’t feel like taking the time to ensure clean data gets into the system, but those same people are quick to moan and groan when they feel their reporting in Salesforce is inaccurate because of the data they don’t want to clean.
When you get into the discipline of not putting garbage into your Salesforce org, you’ll be surprised when you don’t get garbage out. Just like changing behavior when you need to get healthier, getting disciplined about data takes time, and it’s an ongoing habit to follow.
Usually, resistance to creating a data-cleaning strategy is due to a lack of skillset, budget, or both. Even without the budget to hire a dedicated data czar, you should at least identify someone in your organization who is detail- and process-oriented, and adept at organizing and classifying information. Make sure the group that takes on this responsibility is working directly with the sales or marketing teams and is in a position to enforce adoption. Usually this responsibility falls on a sales or marketing operations group, or on the IT business applications team.
If management doesn’t understand how to kick off this initiative, perhaps a cost-of-inactivity analysis can help. Identify your company’s current costs in not enforcing clean data at the top of the funnel. Maybe additional humans are needed to manually clean data because the sales reps won’t. Maybe pipeline and territory analysis must be done in other systems (that take additional humans and products to build). Identify how many humans along the deal cycle are involved in either cleaning up data later or handling customer service issues that result from having incorrect customer data.
When someone has been assigned the responsibility of fixing the dirty data problem in your company, you’ll need a data strategy. Relying on outside data vendors alone to come up with your strategy is dangerous, because each company has its own unique needs and challenges when it comes to dealing with customers.
To come up with your data strategy, follow this outline:
Define how you want to standardize your data.
Company names, street addresses, and postal standards all have official and unofficial abbreviations. This is the hardest step because it’s the first, and there’s no silver bullet. You and your company need to define what quality data means in your organization.
Clean your data.
After you’ve created standards, get your current data into shape. Determine naming conventions, do mass updates of certain fields on records, use tools to manipulate and transform sets of data. Make decisions on when some old information should just be archived.
Now that the data is cleansed, you can start re-duplicating it.
Determine what attributes you want to match on, and whether the match has to be exact or not. Determine how many dupes you may have using various third-party vendor options. If there are duplicate records, when does one record’s data trump the data in another record? When these have been determined, merge the data. Reparent child data where needed.
Enrich, integrate, and automate.
Plan to enrich records that may have missing information. Determine a company hierarchy plan and reflect that in your linking within Salesforce.
Now that you’ve become a cleaner data organization, there’s no time to rest on your laurels. Regularly validate data, clean and modify duplicate or inaccurate data that somehow gets back in there, and repeat.