Les Mills

Summary

Les Mills rely on member addresses for mail and analysis on best locations to open new gyms.

They implemented Addressfinder for address verification which led to:

• Significant drop in undelivered mail.
• Better decision making for gym locations.
• Streamlined website user experience.

Background

In 1968 four-time Olympian Les Mills opened his first gym in Auckland, New Zealand. Les Mills has since expanded immensely and is the hub of a global fitness revolution - where a global team of thousands are fusing science, music, movement and ground-breaking technology and taking it to the world.

The Challenge

Les Mills rely on collecting their member’s address information to send out mail and for an in-depth analysis on the best locations to open new gyms. At first Les Mills’ address fields in their CRM and on their website were free formatted with no validation. They then moved to using the NZ Post PAF file to verify addresses.

They found that the addresses they were collecting were not very accurate, causing mail to often go undelivered and making their gym location analysis difficult.

The Solution

Before

• Manual entry address fields

• Reliance on NZ Post PAF data

• Inaccurate address information

• Issue with unsuccessfully delivered mail

After

• Improved user experience on the website and within the CRM

• Reliable and accurate address information

• Significant drop in undelivered mail

• Ability to make better judgment calls on the placement of new gyms

The Result

In 2017 Les Mills took on a major project to modernise and transform their systems. As a part of this, they implemented Addressfinder’s address validation service into their CRM and website. Since then, Les Mills have been capturing accurate and correctly formatted address information for their members which has contributed to improved business solutions and outcomes.

Not only has Les Mills cut back the number of unsuccessful mail deliveries, but they can now also accurately identify the impact a new gym will have on existing gym memberships and determine the likelihood of success for the new location. Using data to identify the best gym locations has been a breeze.