Chief Global Supply Chain Officer, Wayfair
Search every verified Sascha Hower interview, podcast appearance, and on-the-record quote — each transcript cross-checked by AI and human review to confirm speaker identity. In a September 2022 keynote at the Email Insider Summit, Sascha Hower, Chief Global Supply Chain Officer at Wayfair, discussed the company's approach to email personalization and its limitations. Hower described Wayfair as a platform serving the home goods market with over 33 million products and 23,000 suppliers, and noted that the company sends billions of messages to 27 million customers who made a purchase in the previous year. He stated that Wayfair builds and develops most of its technology and data science in-house, including algorithms for personalization and recommendations. Hower said the company uses machine learning models to predict customer behavior, such as clicks and unsubscribes, to determine optimal email frequency. Hower highlighted challenges with stale personalization, explaining that signals can become irrelevant if not decayed based on product consideration cycles and price points. He noted that during supply chain disruptions, Wayfair pauses notifications for customers experiencing poor post-order experiences until resolution and an apology. Hower also said the company is intentionally shifting from aggressive subject lines to more conversational tones for long-term brand accretion, and is building models to improve omni-channel messaging by centering the customer rather than the channel. He acknowledged that this omni-channel integration was still in early stages.
“Wayfair is a platform that serves the home goods market with over 33 million different products and 23,000 suppliers, which presents challenges in narrowing down the catalog and maintaining a cohesive experience across diverse supplier content.”
“We send billions of messages to 27 million customers who placed a purchase last year, so it is mission critical that everything from our tech stack to personalization solutions is scalable.”
“During massive supply chain disruptions, we snooze notifications for customers experiencing bad post-order experiences, waiting until resolution and an empathetic apology before re-engaging them.”
“We use machine learning models to predict whether a customer will click and make a purchase or unsubscribe, which helps us determine the optimal email frequency to maximize revenue and minimize costs.”
“Personalization can do more harm than good if signals become stale; for example, sending emails about a product a customer just purchased is irrelevant and can damage engagement.”
“We decay personalization signals based on product consideration cycles and price points, recognizing that customers make quicker decisions on lower-priced items and slower decisions on higher-priced purchases.”
“We are starting to focus more on getting the exact right product for customers, not just a top-rated or popular product type, but this is a difficult problem given the size of our catalog.”
“Wayfair builds and develops most of its technology and data science in-house, including the algorithms used for personalization and recommendations.”
“We are intentionally toning down our historically loud and in-your-face subject lines to be more conversational and less aggressive, aiming for a longer-term brand accretion rather than just short-term performance.”
“We are building models to improve omni-channel messaging by putting the customer at the center rather than the channel, ensuring messages are coordinated and sent through the right channel for each individual.”
Personalizing transactional email has become table stakes for e-commerce retailers of Wayfair's scope and experience. But as it ...
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