Why Salesforce Data Validation Capabilities are Not Enough

Marketing professionals go to great lengths to get anonymous website visitors to somehow engage with their brand, performing actions like voluntarily submitting contact information, opting into a program, and many other possible actions. These types of leads are known as marketing qualified leads (MQL) which are then handed over to the sales department who will try and contact these MQLs.

However, research shows that the average website sees 97% to 98% of anonymous visitors, i.e. people who have never given you their email address. We also need to keep in mind that only a fraction of these MQLs will convert.  

Now, think about the quality of the customer-submitted data. How confident are you that the email or phone number they put in is valid? Let’s take a look at some data that underscores the importance of validating customer data.  

Why is it so Important to Validate Customer Contact Data? 

Customer data is a cornerstone to a successful business strategy. Data-driven organizations realize the importance of this and take action to ensure that they collect the necessary customer data points that would enable them to improve customer experience and fine-tune business strategy over time. However, recent studies show a very sad state of affairs of data quality:  

All of this invalid data not only wastes time and money but also makes it almost impossible to measure the effectiveness of your marketing and lead generation campaigns. It also has a particularly negative effect on your sales team, which relies on accurate data to contact prospective customers. If they’re constantly calling disconnected numbers, writing to an invalid email, or a host of other time-wasters, it will be impossible for them to fill the sales pipeline and meet their quotas. All of this costs your business money in more ways than you may think. We explore this in the next section. 

How Much is All of this Invalid Data Costing Your Business? 

In order to try and calculate the costs of invalid data, we need to understand all of the impacts it is having on your sales teams. First of all, let’s think about all of the time it drains away from your sales team not only by using the wrong information when trying to contact a lead, but also by fixing the mistakes manually. All of this wasted time will cause them to miss out on a lot of opportunities. Also, research shows that 50% of buyers choose the vendor that reaches out or responds to them first. Therefore, if you have the wrong contact information, you are putting your sales team at a big disadvantage as they try to close more deals. 

However, calculating lost opportunities that you don’t even know about is like guessing how many angels can fit on the head of a pin, but here is what we do know: 

How is Salesforce Helping You Validate Your Data? 

The only way Salesforce helps you validate customer contact data is by creating contact validation rules. However, these rules can only verify that the data a user enters in a record meets the standards you specify before the user can save the record. So, for example, let’s say you want to verify something simple, like the zip code. If the zip code needs to be in the 99999 or 99999-9999 format, you would need to create a rule like the one below:

You would need to create a separate rule for any data you would like to validate. So to input an email address Salesforce would consider valid, you would need to create a formula like the following:

REGEX ( UPPER ( EmailField__c ) ,”^[A-Z0-9._%+-/!#$%&’*=?^_`{|}~]+@[A-Z0-9.-]+\\.[A-Z]{2,4}$”)

However, these rules only help you to make sure that all of the data is in the right format. Salesforce will not go a step further and make sure that the phone number, email address and other information is actually correct. Let’s take a closer look at data validation tools and what they can do for you.

What are Data Validation Tools and How Can They Benefit Your Business?

Data validation tools allow you to automate the identification and removal of inaccurate or anomalous information, leaving behind a clean data set for consideration by the end user. There are number of ways data validation tools can improve the quality of your data:

  • Cross-reference validation – This is where the tool will compare incoming data with a trusted database. If newly ingested data doesn’t match what’s on file, it can either be rejected or set aside for review. Cross-reference validation is especially useful when assembling leads lists or trying to confirm other business details.
  • Data Type validation – This is something we talked about earlier where data validation rules enforces the consistency of data types. For example, if someone were to accidentally insert an exclamation point or some other special charater into the address field, the system would recognize the inconsistency and ask the person to review what they’ve submitted.
  • Range Checking – This is where you constraints on the numeric values that are accepted in a given field. We talked about this earlier with all of the rule creation in Salesforce that checks to make sure that the phone number has ten digits or zip code has five digits etc.

Which Data Validation Tools Should You Consider Buying?

There are not all that many tools that do a comprehensive data validation job, meaning that they can validate all kinds of customer data such as emails, phone numbers, street addresses and other information. A great tool to use is DataGroomr. It validates contacts’ email and phone number either when you are importing data or merging records. They also have plans of providing physical address verification in the near future. If you only want to validate one aspect of your data you can look at an app like AddressTools,

Data validation is a necessity for both small businesses and multinational corporations. If there aren’t data checks in place, inaccuracies can cause a cascading effect that ends in missed opportunities and lost revenue. Businesses must have confidence in the data underpinning their marketing and sales strategies. With so many sources of information available to management, data quality is essential to reaching conclusions based on sound facts and figures. After all, your business analytics reports are only as good as the data that goes into them.

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