Kevin Ascher explains how to deal with bad data from Salesforce and what causes it.
At the end of the day, Salesforce is a database.
Yes, that database is the lifeblood of revenue and customer relationships, but a database nevertheless.
So if the data in said database ain’t all that great, bad stuff happens. Execs can’t manage the business effectively, users lose trust and abandon, customer experiences suffer, etc. etc.
Ay caramba!
The good news? Well-established methods exist to measure and fix data quality issues.
The bad news? It takes resources and commitment.
Of course no one ever says they’re okay with bad Salesforce data, but not everyone is willing to invest in a solution. But first, let’s understand what we mean by bad data by defining good data.
Uniqueness: each real-world entity is represented by one record. In other words, the absence of duplicates. One Contact for one person, one Account for one company, one Lead for one prospective customer human.
Accuracy: information is correct for each record, such as emails, phone numbers, and addresses.
Completeness: first, a given record – such as an Account – has all the necessary information, such as Industry and Annual Revenue. Second, all the records exist in Salesforce – such as having an Account record for all current and past customers.
Validity: is the data in the correct and usable format. For example, without having State and County Picklists enabled the chances that any 10 given Accounts from California all being listed as “California” vs “CA” vs “Cal.” vs. “Cali”, is virtually non-existent. Are Contacts listed in ALL CAPS? If so, good luck with your merge fields.
Age: data decay is real. The older your data is, the more likely it is to be inaccurate. Job changes are more frequent than ever and is a leading cause of inaccurate contact data, for example.
Usage: this one gets frequently overlooked but is just as important. Data that’s collected but not used in reports, models, prompts, automations, etc. is wasting resources. Wasting time if entered manually, wasting storage space (Salesforce storage limits are a real thing once your business takes off), wasting space on an input form. It’s not a good habit to collect data “just in case”.
Still with me? Cool. Now that we understand good vs bad data, let’s talk about the most common causes of bad data.
Key points include:
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Data decay
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Lack of Data Governance and Ownership
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Poor User Experience (UX)
Read the full article, Help! My Salesforce Data is Driving me Nuts!, on AcousticSelling.com.