Advertising on Amazon can be complex, especially when it comes to figuring out how to get the most out of your budget. Recently, Xnurta teamed up with the Amazon Ads team to dive into this challenge, focusing on how brands and sellers can use Amazon Marketing Cloud (AMC) models to distribute their budgets more efficiently and drive better conversion rates.

In the latest session, we covered practical ways to tap into AMC’s rich and granular event-level signals and make your ad strategy work harder for you. Here’s a recap of the main highlights and success stories.

How different ad types affect conversion rates

Amazon offers a variety of ad formats—Sponsored Product (SP), Sponsored Brand (SB), Sponsored Display (SD), Amazon Demand-Side Platform (DSP), and Sponsored TV (STV)—each influencing consumers at different points in their buying journey. To get the most out of these formats, advertisers need to know how to use them in combination to boost conversion rates.

Xnurta data shows that when SP and SD ads run together, audiences exposed to both see a significant lift in conversion rates. However, many sellers find it difficult to distribute their budgets effectively across these formats. This challenge typically shows up in three areas:

• Choosing the right ad formats:
  With different ad types having unique bidding structures and cost models, selecting the most suitable ones for your product and audience is vital. Properly distributing the budget across them makes all the difference.

• Managing budget strategies:
  Sellers often need to adjust their budgets based on the performance of each channel, finding a balance between ad spend and ROI.

• Data analysis and optimization:
  Monitoring key metrics such as click-through rates, conversion rates, and ACoS helps sellers make informed decisions on budget adjustments that can improve ad performance.

Understanding how each ad type contributes to conversions is the foundation for making these adjustments. Ad attribution helps track all consumer touchpoints, revealing how each interaction affects the final purchase. This is where AMC’s data insights provide clarity.

How AMC provides consumer insights

AMC is an advanced analytics tool that lets brands measure how effective their ads are across different channels, including search, display, video, and TV. Unlike the standard data seen in the Amazon Ads dashboard, AMC delivers highly granular user-level insights, capturing every impression and interaction.

AMC’s foundation on Amazon Web Services (AWS) gives brands a transparent, flexible way to analyze cross-channel data. The advanced analytics allow for deeper insights into how campaigns are performing across multiple channels.

Some of the main advantages of AMC include:

• In-depth consumer insights:
  By connecting the dots between audience behaviors, search patterns, and browsing habits, AMC gives a clearer view of consumer behavior.

• Custom audience creation:
  AMC’s customization options allow sellers to create targeted audience segments, tailoring their ad strategies to specific groups.

• Lookalike audience expansion:
  With machine learning, AMC helps identify potential customers similar to existing ones, broadening the reach of campaigns.

Xnurta AMC Hub simplifies this process with an intuitive drag-and-drop interface, allowing brands to easily build custom marketing models and audiences to refine their strategies across the entire funnel.

How AMC models optimize budget allocation

Xnurta AMC Hub’s Multi-Touch Attribution (MTA) model helps sellers reassess how different ads drive conversions and adjust their budgets based on those insights. This approach allows for smarter spending decisions and ensures every ad dollar is working effectively.

• Rule-based attribution models:
  Models like first-touch, last-touch, time decay, position-based, and linear attribution allocate conversion credit based on preset rules. While easy to understand, these models may not fully capture the value of each touchpoint in more complex ad strategies.

• Mathematical modeling attribution models:
  Advanced models like the Markov Chain and Shapley value use algorithms to evaluate each touchpoint’s role in the customer journey. These models are especially helpful in complex campaigns but require more data processing.

• Xnurta AMC Hub custom models:
  Xnurta AMC Hub offers brands the flexibility to customize their MTA models, allowing them to fine-tune how they analyze their campaigns. Features like ad account filtering, custom ad groupings, and focused ASIN monitoring help tailor ad strategies for maximum impact.

Success stories and case studies

One of our clients in the fashion category, ranked within the top 100 Best Sellers Rank (BSR), had difficulty balancing their budget across different ad formats. They relied heavily on Sponsored Products (SP) and Sponsored Display (SD) ads, with some use of Sponsored TV (STV) ads. To solve this, Xnurta used the Markov Chain MTA model to forecast conversion rates during off-peak periods. This helped our client identify which ad formats were driving the most value, leading to an increased focus on Sponsored Brands Video (SBV) ads. As a result, they saw an 8% increase in sales after reallocating their budget based on these insights.

Another client, a top player in the bedding products category, had reached a growth plateau despite being a market leader. While their ad formats performed well individually, they struggled to optimize the overall synergy between them. Xnurta stepped in with the MTA model, analyzing how their ads worked together. By adjusting their budget to create a more cohesive ad strategy, the brand saw a 5.1% increase in orders, showing the potential of an integrated approach to ad budgeting.

During Prime Day, the bedding brand saw a 16.7% boost in conversions by combining Amazon DSP with Sponsored Products ads, and by optimizing their budget further, they achieved an additional 15.9% increase.

These success stories highlight the power of Xnurta’s MTA models in understanding how each ad touchpoint influences conversions. By reallocating ad budgets and refining strategies, our clients have seen significant improvements in both conversion rates and overall sales. For example, during Prime Day, one client saw a 16.7% boost in conversions by combining Amazon DSP with Sponsored Products ads, and by optimizing their budget further, they achieved an additional 15.9% increase.

In the case of an appliances client with multiple brands and stores, managing ad spend efficiently was a challenge. Each brand had its own budget allocation structure, making it difficult to optimize ad spend across the board. Xnurta used the MTA model to analyze conversion rates for each brand, identifying areas where budget adjustments could drive better results. By tailoring the budget for each brand, the client saw sales growth ranging from 4% to 30% across their stores.

Using tools like Xnurta AMC Hub, sellers can get a clearer picture of how different ad formats contribute to the buyer’s journey. This helps them make smarter, data-driven decisions that optimize budget allocation and drive better results. Whether it’s balancing multiple ad formats or using detailed insights to refine strategies, brands are seeing measurable improvements in performance.

If you’re looking to make the most of your ad spend, request a demo of Xnurta AMC Hub to generate data-driven insights and unlock new growth opportunities.