The evolution of retail media networks has made the customer journey more complex, making it difficult for advertisers to engage customers throughout the buying process. Brands trying to reach their customers on Amazon and Walmart have struggled to manage upper-funnel and off-site marketing because retailers do not share their customer data with ad channels.
Ampd addresses this challenge and revolutionizes off-site campaign management by providing closed-loop attribution. It combines conversion data from retailers with engagement data from ad channels and leverages artificial intelligence to drive performance.
This document explores the Ampd's features, benefits, and implications for brands and agencies looking to drive sales on Amazon.
Key Features of Ampd’s Predictive Bid Management:
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Closed-loop Attribution
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This feature seamlessly integrates Google Ads with Amazon conversion data, providing transparent campaign and keyword-level attribution.
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Proprietary Data:
- Ampd uses its exclusive Google Ads to Amazon sales data to enhance predictive accuracy.
- Machine Learning:
- Ampd utilizes its own proprietary Bayesian probabilistic algorithms for predictive modeling, making the system highly efficient..
- Probability Distributions:
- Automatically models probability distributions for metrics such as impressions, clicks, average order values, revenue, and conversion rates for every keyword.
- Automated Smart Bidding:
- Because Amazon doesn't share conversion data with Google, brands cannot use Google’s Smart Bidding for conversions. Ampd's Predictive Bidding offers a solution—the industry's first automated bidding for conversions specifically designed for Amazon. Ampd is revolutionizing marketing channels for retailer advertising.
- Goal-Based Campaigns:
- Advertisers can set campaign budgets to achieve specific targets for cost, clicks, revenue, and ROAS. Optimization can focus on revenue maximization or cost efficiency.
- Keyword-level Bidding
- Ampd Predictive Bidding manages bids at the keyword level, allowing advertisers to precisely manage budgets
The image below demonstrates how to set up Ampd’s Predictive Bidding and enter your goals. After this, you can relax and observe as Ampd automatically modifies bids to achieve your objectives. Move the slider to the left to focus on efficiency, or slide it to the right to be more assertive and prioritize reach and revenue. Alternatively, position it somewhere in between to align with your targets.
Essentially, Ampd’s Predictive Bid Manager allows advertisers to forecast results with campaign budgets optimized for cost or revenue, helping brands determine the best balance between awareness and revenue in advance.
Benefits of Ampd’s Predictive Bid Management Technology
The integration of AI and machine learning in this platform brings several benefits:
- Accurate Cost and Revenue Forecasting
- Advanced predictive modeling lets advertisers know how many impressions, clicks, and conversions they can expect their budgets to produce.
- Optimized Campaigns
- Avoid human error and human hours, and let Ampd constantly adjust bids to keep campaigns efficiently tracking toward your goals.
- Advanced Strategies
- Probabilistic modeling can help optimize ad spend and campaign performance, resulting in more effective budget utilization.
- Enhanced Omnichannel Strategy
- Ampd assists advertisers in developing effective omnichannel strategies to reach billions of daily shoppers.
Read a few of Ampd’s Predictive Manager case studies.
- Flywheel used the Ampd platform with Predictive Bid Manager to drive 94% New-to-brand customers and a $3.55 ROAS.
- Essence Media (part of GroupM) reported that Ampd’s Predictive Bid Manager improved their performance by 30%.
Conclusion
Brands engaging their customers on Amazon face challenges in managing upper-funnel and off-site marketing due to the lack of data sharing by retailers with ad channels.
Ampd solves this problem by transforming off-site campaign management. It integrates conversion data from retailers with engagement data from ad channels, using artificial intelligence to optimize performance.
