Pacvue optimizes e-commerce data insights using AMC on AWS Clean Rooms | Amazon Web Services

Amazon Web Services · Advanced ·☁️ DevOps & Cloud ·8mo ago

Key Takeaways

Pacvue utilizes Amazon Marketing Cloud (AMC) on AWS Clean Rooms to optimize e-commerce data insights, providing a solution for brands and agencies to understand customer journeys and make data-driven decisions. The platform offers customizable machine learning models to analyze Amazon advertising data, organic data sets, proprietary data sets, and oneP data.

Full Transcript

Hi everyone, my name is Anne Herald. I'm the head of product enablement at PACView. Pacview is an e-commerce [music] acceleration platform that services over 90 different retailers and we support brands and agencies in their journey across retail operations and media. As consumers, we have more choices than ever. It's not just what to buy, when to buy, but also where you shop. [music] And that makes it quite challenging to understand that customer's full journey. Pacview firmly believes that data clean rooms are the way to answer this 360 address question. And that's why we partnered with Amazon marketing cloud on AWS clean rooms in order to build out a solution that makes it easy for people to get started by templatizing the queries so that you don't need to have a [music] data science team include anything from multi-touch attribution to path to purchase modeling to overlap audiences to demographic and geographic [music] data. So it's pretty robust. So it's ultimately super crucial that we make sure that the the privacy of the customer and their [music] data is secure and that's why data clean rooms are so impactful in that way. The next evolution is how do you scale? [music] So, Pacio has built a solution called build your own model using AMC custom models built on AWS clean rooms that allows customers to [music] customize a machine learning model that pulls in Amazon advertising data, organic data sets, [music] proprietary data sets, and oneP data all into one place to find highv value segments to [music] target and for analytics. It basically knits together the narrative of what's actually happening [music] in your complex Amazon ecosystem. And so what we've designed is actually a solution that allows customers to deep dive into that narrative and pick out the most uh insightful pieces [music] of it. This means that if you have a streaming TV ad, a DSP ad, and a search ad, and each of them are in a customer journey, you're actually able to assign credit to each of those touch points based on the value that they're actually [music] driving. Our a AMC solution enables faster decision-m uh allows folks to be more nimble and flexible [music] um and is AI powered. It's easy to use. It's easy to scale and ultimately it drives value for the brands and agencies that we work with. Regardless of your strategy, your market, the category that you're operating in, there's always going to be some data set in AMC that's going to drive value for [music] your strategy on Amazon ads.

Original Description

Pacvue is an e-commerce acceleration platform that serves over 90 different retailers, empowering brands and agencies to optimize their retail operations and media strategies across multiple channels. Today, consumers have more choices than ever, including what, where, and when to buy making it increasingly challenging to understand the full customer journey. Discover how Pacvue leverages Amazon Marketing Cloud (AMC) on AWS Clean Rooms (ACR) to create a privacy-enhanced solution that combines multi-touch attribution, path-to-purchase modeling, and audience segmentation. Learn how Pacvue built a solution called "Bring Your Own Model" to enable customers to customize a machine learning model using Amazon Ads signals, organic datasets, and proprietary data for AI-powered insights, resulting in faster decision-making and scalable privacy-enhanced analytics that drive value across all marketing strategies. AMC and AWS Clean Rooms, enabling advertisers to more seamlessly collaborate with Amazon Ads exclusive signals, generate enhanced insights, and discover new audiences – all without having to move their underlying data outside of their Amazon Web Services (AWS) environment. AWS Clean Rooms ML helps you and your partners apply privacy-enhancing controls to safeguard your proprietary data and ML models while generating predictive insights—all without sharing or copying one another’s raw data or models. Learn more about AMC on AWS Clean Rooms: http://go.aws/4qJZyqj Learn more about AWS Clean Rooms: http://go.aws/47sSdE2 Subscribe to AWS: https://go.aws/subscribe Create a free AWS account: https://go.aws/signup Try AWS for free: https://go.aws/free Connect with an expert: https://go.aws/contact Explore more: https://go.aws/more Next steps: Explore on AWS in Analyst Research: https://go.aws/reports Discover, deploy, and manage software that runs on AWS: https://go.aws/marketplace Join the AWS Partner Network: https://go.aws/partners Learn more on how Amazon build
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Pacvue's solution utilizes Amazon Marketing Cloud on AWS Clean Rooms to provide e-commerce data insights and customizable machine learning models. This enables brands and agencies to understand customer journeys and make data-driven decisions. With Pacvue's solution, users can assign credit to each touch point in a customer journey and drive value for their strategies on Amazon ads.

Key Takeaways
  1. Partner with Amazon Marketing Cloud on AWS Clean Rooms
  2. Build a solution using customizable machine learning models
  3. Analyze Amazon advertising data, organic data sets, proprietary data sets, and oneP data
  4. Assign credit to each touch point in a customer journey
  5. Make data-driven decisions using data insights
💡 Data clean rooms are crucial for ensuring customer data privacy and security, and customizable machine learning models can help drive value for brands and agencies on Amazon ads.

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