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[Webinar] A Customer-Centric Strategy at Scale Using Machine Learning

Photo by Hazel Olayres on Unsplash

With over 5,000 stores worldwide and over 8,000 professional beauty products, Sally Beauty has a lot to share with its customers.

The opportunity? How to deliver the right content to the right customer and deliver on business goals.

In this webinar, hear how Sally Beauty’s CRM team leveraged their first-party customer data with Tinyclues to transform their CRM email marketing strategy.

Learn more about why machine learning is a must for CRM teams today and how the Sally Beauty team integrated it into their strategy to improve customer experience and achieve business goals.

Sally Beauty’s Gabriel Trujillo and Tinyclues’ Ashley Lively discuss strategy & results and answer the audiences’ questions!

The CRMC Webinar Series is hosted by The Wise Marketer. Fill out the form below to watch.

CRMC Webinar: Sally Beauty & Tinyclues

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Gabriel Trujillo is vice President of CRM customer analytics and research at Sally Beauty. He’s a senior leader in marketing, loyalty and CRM with over 20 years of consistently delivering high quality content throughout his career with several widely recognized retail brands, he has masterminded forward-thinking approaches to marketing as well, versed in tracking market trends and capitalizing on opportunities. Gabriel knows the importance of building relationships as evidenced by one of his favorite sayings that I noticed in his profile from Theodore Roosevelt, and it is “the most important single ingredient in the formula of success is knowing how to get along with people”. That’s a powerful one.

Ashley Lively is a senior customer success manager at Tinyclues. She has tremendous experience in building success for her clients. She’s worked with some great brands, including Tiffany’s, and we’ve learned that she’s an experienced cycling instructor, so she clearly knows how to make the wheels turn for her clients. All right? Can’t resist. I just can’t resist.

[Webinar] A Customer-Centric Strategy at Scale Using Machine Learning
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