Sarah Stalnecker of New Balance: How to deliver on consumer expectations using data

(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

Session AI’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

Featured resources

Intro to Profitable Promotions

The stakes are high and the margins are tight. Listen to the conversation with Anh Vu-Lieberman, VP of Conversion Rate and Site Optimization at Nogin, to explore how to run more profitable promotions and the role AI plays in the process.

Read More
AI playbook for ecommerce conversation

AI: The playbook for ecommerce

AI is in the air this year. Hear how Mike Dupuis of SPARC Group, Colleen Waters of Steve Madden and Jenna Flateman Posner of Solo Brands are leveraging AI to drive results and improve the customer experience.

Read More
Shirley Gao-PacSun

Why PacSun uses in-session marketing

The future is in-session. Hear from Shirley Gao, the visionary CIO of PacSun, on what makes in-session marketing the perfect solution to lift revenue and drive conversions in a privacy-first world.

Read More

Apply now