July 17, 2015

Case Study: Stage Store's Valentine's Day Shopping


Screen_Shot_2015-07-28_at_11.36.47_AMWhat was the objective? 

Valentine’s Day shopping is challenging! Stage Stores understands this and wanted to make the experience easier for their customers by offering perfect gift ideas for any recipient. The goal was to learn more about customer shopping objectives so they could accurately personalize gift recommendations.

What did we do? 

Stage Stores leveraged the Iris Platform to engage customers in a two-way dialogue. Using their existing subscriber list, they asked the following question:

Roses are red, violets are blue, still got Valentine's shopping to do? No problem! Reply & tell us who you're shopping for.

 - HIM
 - HER
 - KIDS

Screen_Shot_2015-07-28_at_11.36.53_AMThe platform incorporates natural language processing technology, which can interpret the responses and reply with timely and personalized content. Based on who the individual was shopping for, Stage sent content that showcased products and offers customized for that special someone or little someone. They provided additional utility with a link to a mobile optimized Valentine’s catalog for convenient shopping on the go.

What were the results?

Campaign analytics revealed a 16% response rate and elevated redemption rates for the featured products, illustrating the effectiveness of personalized content recommendations. This campaign illustrated a simple, innovative and effective way for brands to accurately personalize content and add value to shoppers. Our technology helped enable two-way mobile conversations and provided personalized content recommendations.

Ready to make it happen for your company?

 

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