Close icon
For agencies

Amazon and Walmart Connect resource guide for agencies

Consider this landing page your go-to guide for the latest updates from Amazon and Walmart Connect. Our expert team at Intentwise evaluates the latest news, helping you focus on what matters most for optimizing client accounts.

Agency resource guide preview for Amazon Marketing Cloud, data analytics, Walmart Connect, webinars, and training
Amazon Marketing Cloud

Your guide to Amazon Marketing Cloud

Amazon Marketing Cloud dramatically improves ad measurement and audience targeting, and helps answer virtually any business question your clients may have. Mastering AMC will impress your clients and give your agency a competitive edge.

Data strategy

The agency's cheatsheet to Amazon and Walmart

Success on Amazon requires understanding the interplay between ads data and retail data. We provide solutions for clean, automatic reporting, saving you time and simplifying the evaluation process.

Hot topics

Other hot topics in the industry

Our team stays on the cutting edge of e-commerce news, evaluating new features and highlighting the most important updates for our agency partners.

Ready to start training?

GET-STARTED with_our_free_self-serve = 'SQL 101 training'

Intentwise SQL training module

Knowing SQL can sharpen your understanding of what's possible in AMC. Wish there was an easier way to learn it? Our dedicated SQL training module gives you a running start — and it's entirely free.

Sign up now

Amazon AMC certification

Ready to test your AMC knowledge? If you've read all of our resources and you're ready to begin your AMC journey, you can get AMC certified through Amazon.

Complete the test here
The Amazon Marketing Cloud Strategy Guide cover
White paper

Download our Amazon Marketing Cloud strategy guide

Amazon Marketing Cloud (AMC), Amazon's analytics platform, connects together every interaction that shoppers have with your brand. It's the only way to build a holistic portrait of customer behavior.

Download our white paper and get a leg up on your competitors with a sophisticated Amazon Marketing Cloud strategy guide.

Download White Paper

Insights from our CEO

How to cut your data analysis time in half

Amazon agency teams spend a significant amount of time doing data analysis.

Read All

Why you need to watch for data errors

If you are an Amazon agency, data errors in reporting, esp. client-facing ones, are not w..

Read All

Why API connections cause so much trouble

If you are an Amazon agency trying to automate reporting, internally building ...

Read All
All three posts by Sreenath Reddy, CEO at Intentwise
Follow on LinkedIn

Sreenath Reddy · CEO, Intentwise

Amazon agency teams spend a significant amount of time doing data analysis. I bucket this time into two  😃:

🔹 The enjoyable, no-stress kind (Let's call this "Happy Time")
🔹 The stressful, anxiety-causing kind (Let's call this "Unhappy Time")

Here are some examples of each:

🔴 Happy Times

👉 You are auditing a prospect's ad account and finding clear opportunities to win them.

👉 You are on-boarding a client, doing competitive analysis, figuring out all the necessary targeting

🔴 Unhappy Times

👉 A client's ACOS has spiked. They are in your face and you are figuring out what happened and how to recover.

👉 Your client just forwarded an audit done by your competitor with a long list of findings.

My main point is this:

As an agency, proactively identifying the sources of "Unhappy Times" and reducing it via process and automation will dramatically reduce employee burnout,  increase client retention and help you scale.

As an example there should be automation and process in place to spot the key drivers in an account causing ACOS to spike (atleast the correlated factors), under 10 minutes, for all team members.

A while back, we were a Google Adwords agency before we pivoted to being a SAAS platform in the Amazon ecosystem. We experienced firsthand how much time goes into analysis as an agency. Hence, we continuously prioritize building capabilities to shrink this time for agencies via the Intentwise platform.

Read on LinkedIn

Sreenath Reddy · CEO, Intentwise

If you are an Amazon agency, data errors in reporting, esp. client-facing ones, are not what you want to see. Unfortunately, this is an occasional reality.

At Intentwise, we collect and harmonize data for a few thousand accounts. Gaps and errors in data can happen for many reasons. Here are a few examples:

👉 Your requests for data on certain reports could get throttled, which requires you to have a sound retry process in place.

👉 Sometimes, we have seen that the API calls look like they have succeeded, but no data has come through.

👉 There are reports that you can only request once every few hours (Example: FBA Fulfillment Report). So, when a request fails, your retry logic has to account for this constraint.

👉 You even run into situations where there may be no genuine issue, but your client thinks there is one. The best example of this is ad-attributed sales, where ad revenue over the past 14 days can change. People unaware of this often mistakingly think there are data issues.

🔹  What Can You Do About This?

🔸 Continuous investment into automatic detection, alerting, and automatic fixing, ideally before your client sees it, is a must. If you work with an external partner for data automation, ensure they prioritize this. This is a big area of focus at Intentwise.

🔸 Stay educated and keep educating the client on the nuances of the different reports and datasets, mainly because there is so much change.

This post is the second in a series of posts I am doing about Amazon agency reporting pain points. Below is the link to the prior post:

Pain Point 1 - Data Collection: https://lnkd.in/g3e-CdUb

Read on LinkedIn

Sreenath Reddy · CEO, Intentwise

If you are an Amazon agency trying to automate reporting, internally building and maintaining DATA COLLECTION capabilities is a mistake.

Last week, I wrote about all the friction points regarding Amazon agency reporting (https://lnkd.in/gv7XpagT) and promised to do a series of posts delving into each. Here is my first:

👉🏼 PAIN POINT #1: Data Collection in the context of ever-changing APIs, Metrics, Schemas

First, you have a number of data sources to collect data from: Sponsored Ads, DSP, seller central, vendor central, Amazon Marketing Stream, Rapid Retail Analytics, AMC, etc.

Secondly, the APIs for these data sources are constantly changing.
 
In this context, internally building infrastructure to automate data collection is a big investment—an investment in a direction that is not a core competence or differentiator for most agencies. I know several agencies that have gone down this path, stopped mid-flight and corrected their course.

Here are two pieces of advice based on our work at Intentwise with a number of agencies:

🔵 Please don't build and maintain data collection infrastructure internally. You are better off buying it. It will be a lot cheaper, faster, and more comprehensive. You can ignore this advice if you are an agency with development resources committed for a long stretch of time.

🔵 It's crucial to have a predefined set of questions (a roadmap) that you want answered through the reports or dashboards you're building. This will guide the data you need to collect, keeping your efforts focused and effective.

Need help with any of the above? Lets chat.

The next friction point I will write about is "Data Quality Headaches".

Read on LinkedIn