The customer shopping journey is more complex than ever - requiring eCommerce advertisers to serve and measure ads to their target audiences at more and more touch points. Thankfully, Amazon Marketing Cloud helps brands get a clearer picture of the customer journey and provides meaningful insights into ad performance.
The most important concepts when it comes to understanding the success of Amazon ad campaigns are attribution and measurement. AMC brings together hundreds of data points across ad types, sales, and other first-party data. This allows advertisers to look at their advertising efforts on Amazon holistically across channels to see what is actually driving growth.
Pacvue integrates with AMC so advertisers can access their AMC data through their Pacvue login instead of logging in to the AMC Native Console. Users have access to a dashboard full of premade visualizations of queries, some from Amazon’s Instructional Query Library and some Pacvue specialized queries.
In our recent Friday Snack Break video, Pacvue’s Senior Manager of Retail Media, Anne Harrell, and Product Manager, Jack Lindberg, discussed how to more accurately measure holistic ad performance using Amazon Marketing Cloud. Here are the most important takeaways from that great discussion.
Measuring return on ad spend (ROAS) is an important metric for judging the performance of an ad campaign. However, it can lead to some inaccurate measurements if it is the only metric used - especially for top-of-funnel placements.
An advertiser can see significantly fewer impressions, clicks, and sales, but still, see an increase in ROAS. This doesn’t mean that your program is growing. It just means that the dollars that you are spending are getting a slightly higher return.
Additionally, last-touch ROAS – although it’s the standard for the industry – doesn’t have any sort of weighted attribution. This means that any advertising efforts falling before the final click or view in a customer’s journey get 0% of the credit for encouraging the outcome of that journey. This makes it really difficult to accurately measure tactics like upper funnel display or video because these rarely see any return when measured this way. These tactics introduce your brand or product to the consumer and, arguably, that is the more valuable moment in the journey to a conversion.
Getting a more accurate measurement of the success of these kinds of tactics requires a more holistic measurement approach.
AMC provides some excellent data and queries for measuring the full marketing funnel. Along with this data, Pacvue has layered on a proprietary machine-learning algorithm to provide budget recommendations to maximize total advertising sales. Add these tools and queries to your Amazon advertising strategy:
This AMC data set allows advertisers to see how users engage with ads across different ad types. Which ads do they click on? And in which order? How frequent is this unique path to purchase, and how successful is it in driving sales?
Advertisers are often surprised that their customers engage with so many touch points before making a purchase. This further proves the need to look at this type of data to make informed advertising decisions.
Combining AMC’s data on each customer journey with Pacvue’s Assisted Conversion Analysis allows you to attribute partial value to touchpoints earlier in the customer journey. So, when you’re looking at the Path to Purchase query, the upper funnel views like video and display will be credited for part of the final conversion value.
This analysis assigns a more accurate value to each advertising touchpoint and therefore enables advertisers to make more informed budget decisions. Ultimately, if assisted conversions go up, so will last touch conversions meaning measuring this way can encourage sustainable long-term growth. And in many cases, we see that tactics previously viewed as inefficient are actually more efficient than their lower funnel counterparts when using multi-touch attribution. Since we know all the paths to purchase and the propensity of a user interacting with each type of ad, we can build a robust model of which paths and ad types to support with an additional budget.
Pacvue recently had a client splitting their budgets between search and DSP at an 80:20 ratio- a common distribution across the industry. When Pacvue ran our budget suggestion algorithm, we discovered that our client was packing too much money into the bottom of the funnel in search ads. After a month of using a 60:40 search to DSP split, our client increased their ad sales by 64% month over month without increasing their total expenditure.
As retail media and Amazon advertising continue to expand at an exponential rate, advertising programs are becoming more complex and mature. Measurement and attribution need to follow suit. Otherwise, true growth will be just out of reach.
You can learn more about Amazon Marketing Cloud and Pacvue’s integration by booking a demo today.
Timely trends and need-to-knows delivered straight to your inbox.