Mapping the Consumer Genome: Ep 9

Conversation with Sarah Stalnecker of New Balance on:

  • How to deliver on consumer expectations using data
  • The impact of social proof on consumers
  • How to use rich data points to power digital personalization

Sarah Stalnecker, Head of Consumer Analytics at New Balance

(0:12) Sarah’s role at New Balance Athletics, Inc. 

  • Sarah leads Consumer analytics team for North America
  • She and her team are responsible for understanding the consumer journey
  • Her team transforms data into actionable insights to build relevant consumer experiences

(01:02) Harnessing data through a consumer data hub

  • Sarah started out by recognizing that all consumer data the company has is in disparate and siloed systems 
  • Then work on breaking down the silos to create comprehensive insights about every consumer to deliver experiences that resonate with them

(03:00) Driving relevant digital experiences for consumers

  • Sarah and her team use the rich data to support traditional digital experiences such as product recommendations 
  • More importantly, they use data to help mirror great in-store experiences in the digital environment

(04:48) The impact of social proof and events in influencing demand 

  • Having the community weigh in about a product of interest through their likes, views and reviews gives the singular online shopping experience a more community feel 
  • Such compelling experiences instill confidence in the product for the consumer, which in term helps to not only drive conversion but also helps in customer retention

(07:49) Using location and weather for personalization

  • Leveraging rich data is important to make consumers’ digital experience relevant and their shopping more convenient 
  • Using weather and location intelligence is critical for lifestyle products because what is useful for a consumer living in one region is not of the same value to another residing elsewhere with different weather conditions
  • For Sarah and for New Balance Athletics, it’s all about leveraging consumer data to provide seamless experiences that make shopping convenient for them
  • They do this by ensuring they understand the consumers’ constantly changing needs and lead them to the products that they want or might be interested in

(12:38) The role of machine learning (ML) to better understand consumers

  • She has used ML for demand forecasting and planning
  • Additionally, ML models work well with intelligent product recommendations, applying weather and location intelligence
  • Furthermore, using ML to predict consumers’ time to next visit and understanding what kind of experience to deliver to motivate them to come back sooner
Sarah Stalnecker, Head of Consumer Analytics at New Balance

“I believe that delivering convenience in an omnichannel way has a lot of complexity. And it’s incumbent on all of us is to deliver against that and with a subtlety that is not overt, heavy handed. I’m [not] collecting data for data’s sake. But rather I’m trying to create an experience that’s better for you, more convenient for you, more efficient for you”

-Sarah Stalnecker, Head of Consumer Analytics at New Balance

ZineOne’s patent-pending ML models run on AWS’s highly resilient architecture using EC2, S3, WAF, CloudFront, Config,  and CloudTrail to deliver a significant increase in conversion rates for eCommerce sites.

Last Updated: June 1, 2022

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