How Can I Trust My CRM?


85% of a luxury brand's sales come from customers already registered in their database.
69% of organizations believe that inaccurate data undermines their ability to provide an excellent customer experience.
Does Bad Data Matter?
Your customers are excited. The new arrivals for this season are soon arriving. You are their brand and they feel an emotional connection. It may have taken years to build these relationships and they are ready to be delighted.
This moment depends upon what you do next and how well you know your client. And, how well you know your customer depends on the accuracy of the data in your CRM (Customer Relationship Management) or Customer Data Platform (CDP) system.
85% of luxury brands sales comes from customers registered in their database. (Luxe Digital)
Misspell or mispronounce customers’ names … forget their preferences … ask them again to enter their address, even though they gave it to a different representative last week … and they will think you don’t care about them or that your attention to quality details are lower than they thought. When the information is wrong, you’ll also miss key customer insights, and won’t be able to identify your best customers or project customer trends.
More than two-thirds (69%) of organizations believe that inaccurate data undermines their ability to provide an excellent customer experience (Experian Data Systems).
You cannot underestimate the impact of bad customer data on your customer experience.
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69% believe inaccurate data undermines their ability to provide an excellent customer experience.
69% believe inaccurate data undermines their ability to provide an excellent customer experience.
Why does my CRM have bad data?
Customer data constantly changes. Individuals get married, change their names, get divorced, and die. People and companies also move. The quality of stored U.S. address data declines at a rate of 17 percent each year (USPS). People may also use different phone numbers at different times, such as a mobile number and a work number. Both are valid, but they usually do not match.
It is important to update your records at every opportunity. Each time a customer interacts with you online, in-store, or by phone is a chance to verify her information. Change of address databases from postal authorities and others enable the data to be improved between interactions.
Another common source of problems is bad data entry at a customer touchpoint. A customer named “Christiane” might have her name misspelled as “Christine” or “Chris” by an eager sales advisor. A common result is that the same person will be listed multiple times. The result could be that you will send an offer using the wrong name, multiple offers with different names, and that she not even appear on your VIP list when all of her purchases would qualify her. (How do I merge and match records?)
Frequently, bad data is the result of the improper integration of systems that were never designed to work together. For example, country data silos may be formatted differently (e.g., address and phone number). Some may use a different character set that is appropriate to the local market.
Related articles:
How Do Personal Names Differ Around The World?


A recent study showed that nearly half of all the customer records (45%) at a major luxury brand contained bad data.
69% of organizations believe that inaccurate data undermines their ability to provide an excellent customer experience.
How big is the customer data problem for luxury retailers?
A well-known, global, luxury retailer asked us this question. We looked at more than 11-million of their customer records and discovered that nearly half of all the customer records (45%) contained bad data.
- 43% did not have data in the country field.
- 38% had unusable terms or phrases, such as “Needs New Address,” in the data
- 12% had duplicate information in different fields, such as the same entry in the ADDRESS 2 and CITY fields.
- 5.5% had identical values in the given name field and the surname field.
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Reduce the amount of bad data right at the source by tackling the three primary causes.
69% of organizations believe that inaccurate data undermines their ability to provide an excellent customer experience.
How can I reduce the amount of bad customer data?
You can reduce the amount of bad data right at the source by tackling the three primary causes of bad data in CRM and CDP systems:
- The customer data wasn’t entered consistently or accurately.
- The customer data has changed and wasn’t updated.
- The customer data was improperly integrated from different systems that were not designed for the same purpose.
Focus on the following areas to minimize these three causes of bad data:
Customer Form Design
Make sure that your customer and sales representatives know what to do. Many form designers think that their instructions and layout are clear. But, we are dealing in a world with cultural and physical differences that need to be handled.
One pervasive and easily fixed problem has to do with instructions for name entry. It is common in Western Europe and the Americas to ask for a person’s “First Name” and “Last Name.” However, in Japan, Korea, and Hungary the family name is used first. Solve the problem by using terms like “Given Name” and “Family Name.” (Personal Names Around The World.)
The other common problem is that form designers tend to create forms based on the structure of the database rather than the way people want to enter data. How many address lines does your customer need to ensure delivery? How do customers enter a post office box, tower number, or a home’s name? It may be best to have large open fields that can be parsed by software into their proper components. If a form structure is required, it is essential to have clear instructions. (More about addresses in forms may be found in an interesting article entitled Falsehoods Programmers Believe About Addresses.)
Data Entry Mistakes
Reduce typos by looking up the customer in real-time and through the use of autocomplete software. You might be able to retrieve customer information by asking a customer for his or her phone number first. The entire form might be completed automatically, which reduces the chance of a typo. The customer can review and corrections can be made on the spot.
In the absence of real-time customer information, real-time autocomplete works well by suggesting addresses as the person types. After typing a few letters, entire addresses can be displayed on a list from which the customer may select, saving time and reducing errors. It saves time and reduces errors. If real-time autocomplete is not feasible, specialized software can also check a customer’s entry after it is completed and suggest corrections based on a database of address information.
Proper Data Silo Integration
Luxury retailers have many data silos: online and brick-and-mortar, country by country, and product lines. Each was created for a different purpose and likely has different data in a differing format. When data from these silos is merged, new errors are produced.
Related articles:
Best Practices for Address Hygiene


Improve the accuracy of data that you already have in your customer database.
69% of organizations believe that inaccurate data undermines their ability to provide an excellent customer experience.
How do I fix bad customer data already in my CRM or CDP?
For the data that already exists in a database, data accuracy can be improved significantly with address cleansing, name matching, merge/purge, and suppression.
Consistency is a critical first step. Address cleansing and standardization is a record-by-record process that involves removing common errors, adjusting address formats where appropriate, and then verifying each address. Automatic fuzzy error correction corrects switched letters, missing words and letters, standardizes abbreviations, and handles missing or extra spaces. Phrases like “Needs New Address” or “Unknown” can be flagged. It is essential to make sure that country, language, and regional issues are top of mind when cleansing and standardizing as the patterns can be different in significant ways.
A similar process can be used to verify email addresses and phone numbers.
Once all of your data is cleansed and standardized, you can start the process of matching across customer records to increase accuracy and completeness further. Standardized records for the same person may not match exactly. Personal data is always changing. People move. Individuals may provide a work phone number during one interaction and a mobile number during another interaction. Many people also have multiple addresses (e.g., primary and vacation homes), multiple phone numbers (e.g., fixed landline and mobile), and numerous email addresses (e.g., personal and work).
Matching records with these subtle issues can be challenging. A technique known as “cascading” assembles data from different cleansed records for the same customer. It looks for differences between the records and uses advanced logic to resolve conflicts and fill in incomplete information.
The ideal solution is not to change the source document, but to create a system of reference that can be synchronized with the various data silos.


You will be able to trust your data.
69% of organizations believe that inaccurate data undermines their ability to provide an excellent customer experience.
Conclusion
You can trust your CRM.
Global-Z can apply decades of international customer data expertise to work with your existing CRM or CDP vendor to achieve the highest possible level of confidence in your customer information. With that, you will be able to provide an outstanding customer experience at every touch point.
Learn how we can start a project together.
Learn About
Trust Your CRM
Be confident that your customer’s information is entered correctly and validated, so that you can trust what is in your CRM or CDP.
Integrate Data Silos
Integrate online and brick-and-mortar, multiple geographies, and your lines of business with a common system of reference.
Implement Customer 360
Identify, aggregate and link customer data across all of on-line and in-store data with accessible Single Customer Views.
Delight Across Borders
Create customer experiences that recognize and delight your cross-border luxury shoppers at every touchpoint and in every location.
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