Description
Welcome to another episode of The Ecommerce Braintrust podcast hosted by Acadia’s Director of Retail Operations, Jordan Ripley.
In this special edition, we dive into the results of this year's Prime Big Deal Days with some top-tier experts from the industry.
Joining us are Logan Nielsen, an Account Manager at Acadia and our resident Prime Day hype man, and Zach Christensen from Analytic Index, Acadia's trusted category and search analytics data partner.
Just 36 hours after the event, they share their initial impressions, key trends, and data-driven insights, helping you understand what worked, what didn't, and what it all means for the future of e-commerce.
Make sure you tune in to find out more!
KEY TAKEAWAYS
In this episode, Jordan, Logan, and Zach discuss:
The different names for Prime Day and the event's brand identity.
Personal takes on prime big deal days: personal experiences and purchasing stories.
Analysis of consumer engagement and awareness compared to the summer Prime Day event.
The general sentiment and energy surrounding Prime Big Deal Days.
Emotional involvement and purchase decisions.
Preliminary key trends and data insights
The importance of leveraging external traffic and influencers.
Analysis of the increased competitive landscape and its impact on ad spending and ROI.
Notable Glitches and Technical Challenges: Issues encountered with Amazon's ad consuls and badging for sponsored brands.
Logan's strategies for mitigating these challenges in future events.
Logan highlights the success of premium brands with compelling discounts.
The important role of prime exclusive discounts despite the new deal fee.
Zach's insights into the surge of novelty items and Amazon's private label strategies.
Predictions and strategies for the future: Leveraging brand-tailored promotions and new audience types.
Importance of analyzing competitive promotions and preparing for upcoming Q4 events.
Zach discusses the potential long-term impact on search visibility and shopping patterns.
Summary of initial findings and anticipated future analysis.
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