At Cloud on Tap, we often refer to the crawl, walk, run approach. And within this approach, we see a lot of variation as to what it can look like. For some, it’s starting on Sales Cloud, growing to Service Cloud, and then eventually a marketing product. For others, it stays on a single cloud but grows in capability and functionality. Regardless of your approach and the speed at which you get to running, you can only be as efficient as your data.
Enter: Data Cleaning. Naturally, over the course of time, data grows more inconsistent and you begin to realize ways it could be captured more efficiently. Whether that means changing a text field to a drop down or making a field required, everything that makes your data more streamlined, empowers your business to run smoother.
Before you make the leap to the next phase of your Salesforce project, our Salesforce experts recommend completing a Salesforce audit. Even if the next phase isn’t a significant change, an annual data audit is still considered best practice. This ensures that your Salesforce instance is running smoothly, efficiently, and accurately for your sales team. Here are the three most significant things to consider when doing your data audit:
What are the current pain-points in the data capturing process?
Oftentimes, our customers' primary goal of coming to Salesforce is to increase visibility and streamline processes. However, if the process for getting that visibility is tedious and messy, it can actually be counterproductive. Think about how you capture the data. When you enter a new lead or opportunity, how much time do you spend typing in information? How many boxes are you required to fill that have nothing to do with the end goal? How many error, help, and validation messages pop up?
When you are cleaning your data take all of this into consideration. Make the process as lean as possible by cutting down on text fields, required fields, and page layouts wherever possible. This will allow reps to have more time completing tasks that matter and will give you more consistent data in the end.
What tools and practices are being utilized to ensure that data is concise and consistent?
Do you have a tool that catches duplicates? Are there validation rules that exist to ensure that amounts or products entered are done so correctly? Or are you starting from scratch? Regardless of your status, it’s important to have some measures in place to ensure data integrity. If no fields are required and everything is text fields with no validation rules, you’re going to have duplicates, inconsistencies, and missing data.
There are lots of great tools available for free on the AppExchange that can stop duplicate data entry. On top of apps, having training for your team around how and why data should be entered can also be highly effective.
What is your primary use for the data?
Are you using the data for reports? Marketing materials? Both? Whatever your use case, make sure the data you are capturing is beneficial for that use. If you’re in a pattern of using notes or outside systems to track a set of data, it’s completely unusable. Make sure you have fields for all the critical information required by your business process.
You have Salesforce and you’re getting ready to adopt Marketing Cloud or Account Engagement. Or, maybe you just need to keep your data organized in Salesforce alone. Either way, data cleansing is crucial to your sales success. After all, Salesforce associates data cleaning with a 29% increase in sales opportunities!
What does bad and messy data look like? You may have duplicates that need to be merged, missing field data, and/or unverified (and potentially incorrect) data. Any of these issues can prove extremely damaging to your sales process, especially when you start syncing with marketing automations.
Our resident Salesforce experts recommend completing a Salesforce audit before integrating marketing automation as well as once a year as a maintenance best practice. This ensures that your Salesforce instance is running smoothly, efficiently, and accurately for your sales team.
When cleaning your data, here are qualities to strive for:
Accuracy - The data was recorded correctly
Completeness - All relevant data was recorded
Uniqueness - Entities are recorded once
Timeliness - The data is kept up to date
Consistency - The data agrees with itself
Some common data problems to look out for:
Changes in data layout/data types - Integer becomes string, fields swap positions, etc.
Changes in scale/format - Dollars vs. euros
Temporary reversion to defaults - Failure of a processing step
Missing and default values - Application programs do not handle null values well
Gaps in time series - Especially when records represent incremental changes
With all of the available services out there, choosing the appropriate one for your instance can be tricky, especially if you aren’t familiar with the services available. Contact us and let us help you decide on which service would be best for you!