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Trumpia > Case Studies > Douglas J Makes The Cut With Trumpia
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Douglas J Makes The Cut With Trumpia

Technology Category
  • Application Infrastructure & Middleware - API Integration & Management
Applicable Industries
  • Consumer Goods
Applicable Functions
  • Sales & Marketing
Services
  • Software Design & Engineering Services
The Challenge
Douglas J, an award-winning salon/spa franchise, was facing a challenge with their marketing strategy. They were sending texts to over 300 customers a day and needed a messaging software that could scale to that large number of recipients. Additionally, with multiple locations, it was critical for them to organize customers into groups so they weren't sent messages that didn't pertain to them. The challenge was to find a system that could handle the volume of messages and also sort customers based on their location for more relevant promotions.
About The Customer
Douglas J is an award-winning salon/spa franchise that offers premium services across the Midwest. They have six Aveda Institutes in addition to their four salons/spas. Their marketing strategy involves sending texts to over 300 customers a day. With multiple locations, they needed a way to organize customers into groups so they weren't sent messages that didn't pertain to them. They were in search of a messaging software that could scale to a large number of recipients and sort customers based on their location.
The Solution
Douglas J found a solution in Trumpia, a system that allowed them to text a large number of customers at once. They created and posted mobile keywords on their marketing collateral and notified customers as they checked out, which allowed them to efficiently collect phone numbers for their database. Then, based on their location, Douglas J sorted their customers into separate distribution groups. This allowed them to send more relevant promotions to their customers, enhancing their marketing strategy and improving customer satisfaction.
Operational Impact
  • Douglas J was able to efficiently collect phone numbers for their database.
  • They were able to sort their customers into separate distribution groups based on their location.
  • They were able to send more relevant promotions to their customers.

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