Ask the Expert: 5 Ways to Improve Your Salesforce Data Quality

Supermums is on a mission to inspire and educate mums (and dads) to accelerate their Salesforce Careers and we have launched our Ask The Expert series. Once a quarter we’ll focus on an Salesforce industry expert to share their tips and advice. Today’s focus is on Plauti and why data quality is so important. 

Why is data quality so important?

Since the pandemic, data quality is more important than ever before. But why?

Salesforce conducted an extensive survey across 3,600 business buyers and 12,000 consumers that gives us insight. Salesforce found that buyers are increasingly expecting a trusted, empathetic, and convenient experience. The key to answering these expectations is a connected engagement across all touch points. Many businesses fail to deliver on the following:

  • 68% of respondents expect an empathetic experience, but only 37% get one
  • 66% expects business to understand and act upon their unique needs (personalization)
  • 76% expect consistent interactions across departments, but 54% generally feels like sales, service, and marketing don’t share information

A true customer 360 view is needed to enable employees to act empathetically, personalise communication and have a smooth experience across all touch points.

A customer 360 is easier said than done. Siloed data, unformatted, unvalidated and duplicate data make it hard to trust your data. Never mind that existing data decays at an alarming rate at 70.3% per year, according to Gartner’s research.

To ensure your data quality efforts bear success, we have gathered five best practices from Plauti’s years of experience dealing with customers looking to improve their data.

When you receive an email addressed to someone else, how does it affect your perception of the organisation that sent it? If customers don’t trust the information held about them, overall confidence in the organisation can be quickly eroded.

Gartner Research 2021

5 Best practices for data quality initiatives

1 – Make someone responsible

Making data quality a specific responsibility for an existing role or creating a new role is the first step in ensuring there is continuous attention to data quality within your organisation.

The person responsible should perform an initial clean-up and focus on preventing bad data from entering the system from thereon.

2 – With a little help from friends

We advocate making someone responsible for data quality because shared responsibility is no responsibility. That does not mean this person has to do everything themselves.

Empower all employees to detect and fix bad data when they see it/are about to enter it. Some solutions alert employees when specific fields are invalid, empty, or when a record is a duplicate. These alerts are available both for viewing and updating existing records and when entering new records.

3 – Focus on prevention

As a data quality company, we see many organisations wanting to do a one-off clean-up of their data. Cleaning the floor when it is dirty is always a good idea, but when you don’t add a good doormat for visitors to wipe their shoes, you will soon have a filthy floor again.

And while we are in the visit analogy, refusing people with dirty shoes from entering is not a solution either. They might want to spend money with you.

Preventing bad data by deduplicating, validating, and formatting new records is perfectly possible without blocking or losing any valuable data.

4 – Keep it simple

Convenience trumps all rules for data quality you can come up with. If people must jump through hoops to save a record, check for duplicates, or change a field value, they will find a workaround (like entering bogus data), revert to other systems than Salesforce, or don’t bother at all.

All data quality measures should have almost zero impact on their daily routines. Make it a natural part of their existing workflows within Salesforce. Only this way will they perceive that the benefits of good data outweigh the extra effort it requires.

Convenience is another reason to go big on prevention: it does not place the burden of fixing or working with bad data on your employees.

5 – 1+1 = 3

Different types of data quality efforts reinforce each other. Take, for example, the formatting and validating of addresses and phone numbers. This not only leads to higher connected call and delivered mail rates but also makes identifying duplicates much more accurate: finding more actual duplicates and reducing the number of false positives.

If you want to know more about data quality best practices and who is responsible, and you are part of our Supermums Alumni, join the Plauti special webinar featuring Heather Black, founder of Supermums and 8x certified Salesforce consultant. Look out for an email with the link to join.

Get started!

You can get started with Plauti Data Management solutions by installing the apps from the Salesforce AppExchange:

Salesforce Business Analyst Training Programme

We are taking Expressions of Interest NOW for those of you who would like to begin your BA journey in February.  If you are interested take a look at our information pack.

Got questions? Come along to our Q&A session on Tuesday 11th January @ 12pm GMT to find out more. You will receive a confirmation email with details about how to join once you’ve registered.

Please note, this is currently only available for those that live and work in England due to funding restrictions from the UK Government.

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