Amazon and Walmart are sharing more data than ever. Now, suddenly, you can build a deeper understanding of shopper behavior. The problem? It can be overwhelming to find where to start.
The reality is, the most sophisticated brands and agencies have already figured out how to utilize this firehose of new data.
Building a data strategy is therefore essential for retaining your competitive advantage.
Below, we’ve compiled all of our tips and tricks about crafting a smart data strategy.
Say goodbye to those messy, error-prone Excel reports. With our suite of customizable templates in Intentwise Analytics Cloud, see your organic and ads data in one automatically refreshing view.
By default, your ads and retail reports live in separate sections of Seller Central, Vendor Central, and the Ads Console.
You can combine them by hand, by downloading all of your reports day by day or week by week. Then, map them together in spreadsheets. That approach becomes tedious quickly.
If you use Amazon’s APIs, by contrast, you can ensure the data is automatic. Feed both retail and ads data into the same platform, and you can see how they work in tandem.
ACOS (Advertising Cost of Sales) is the default KPI for many brands. It’s a decent start for measuring your ad campaigns—but it’s incomplete. ACOS only tracks ad-attributed sales.
But what if you wanted a metric that calculates the downstream benefits of advertising, such as the benefits from increased exposure or organic ranking?
TACOS (Total Advertising Cost of Sales) measures both organic and ad-attributed sales.
It gives you a more holistic understanding of whether your ad campaigns are working. The catch: The only way to calculate TACOS is to tie together your ads and retail data.
Calculating this one time, or on a monthly basis, is pretty straightforward. But getting TACOS at the ASIN level takes many steps, unless you’re using a platform like Intentwise Analytics Cloud.
Once you connect your retail and ads data, you can start to bring metrics like profitability into clearer view.
As discussed above, building a profitability calculator requires you to join tables from 6+ Amazon reports. It’s difficult to do on your own.
Instead, use APIs to download those reports automatically, and mix in the COGS for each of your products. Finally, feed all of that data into a visualization tool like Power BI or Tableau, so you can see a graph of your profitability per item that updates in real time.
Much like profitability per ASIN, Customer Life-Time Value (CLTV) is vital to understanding the health and long-term effectiveness of your customer acquisition strategy.
Vendors will have trouble calculating CLTV unless they use Amazon Marketing Cloud. But if you’re a 3P seller, there is one way to do it:
Step 1: Calculate the average purchase frequency of your products (average purchase frequency = total number of unique orders / total number of unique customers).
Step 2: Calculate the average purchase value of all of your products over the chosen time period (average purchase value = total revenue / number of orders).
Step 3: Multiply the average value of your products by the average purchase frequency, and you have your average customer value.
Step 4: To make this number a customer lifetime value, just multiply that average customer value number by the average number of years that a shopper buys from you. You might have luck finding the lifetime stat based on your DTC channel. In e-commerce, a customer lifetime is typically 2-3 years.
From there, you can calculate the CLTV.
The problem is, it’s a lot of work to repeat that process again and again. That’s why Intentwise Analytics Cloud built a customizable CLTV template that does all of this for you.
We’ve discussed above the importance of API access for automating the data collection process. If you’re a large brand or agency, you might be thinking: Well, should I build my own API connections with Amazon?
Some brands have created API pipelines successfully. But it is much harder than it looks.
First: Just building an API pipeline alone will take a dedicated employee several months.
Second: Forging that API connection is actually the easy part. Once you have the API, you have to make your data usable. Enrich it with currency conversions, complicated groupings and segmentations, and additional data points, like inventory levels.
That’s not to mention all of the API updates and errors you have to prepare for.
It’s rarely worth all of the work. Instead, you should consider partnering with a software platform like Intentwise that can handle the messy realities of API management for you.
One of the trickiest parts of managing your Amazon data is segmentation.
Let’s say you’re a cookware brand, and you have separate product lines of oven mitts and saucepans managed under the same account.
At Intentwise, we call these product lines “sub-brands.” Sub-brands often have very different price points and audiences, so you’ll want to analyze your performance for each separately.
You could segment your sub-brands by creating a complicated series of mapping tables. Or, go the easy route, and let Intentwise make sub-brand segmentation automatic. Just upload a key, and we’ll split up your ad performance by sub-brand for you.
Segmenting out your brand vs. non-brand keywords is critical for evaluating the success of your ad campaigns. If you accidentally mix brand terms with your non-brand keywords, you might artificially inflate your ROAS. After all, brand terms reach customers who are far closer to a sale.
To segment out your campaigns, just create and upload a key to your brand vs. non-brand terms, and a platform like Intentwise can do these segmentations automatically.
If you do choose to segment these campaigns yourself, be aware of some pitfalls. Oftentimes, when you run broad-match campaigns, your branded keywords might accidentally get counted in your non-branded campaigns. For example, a broad-match keyword—like “headphones”—might accidentally match to your brand terms, like “Bose headphones.”
Within Seller Central, your reports are separated by geography. That means, if you want to calculate total spend across all countries for which you run ads, you have to download an individual report for each country and connect them together yourself.
After you’ve connected all of those reports, layer on up-to-date currency conversions, so you can ensure your numbers are up to date.
Or, if that’s a hassle, you can let a software like platform connect and enrich your data with currency conversions for you.
The most tedious part of client reporting is organizing your data. Without a clear process, you’ll be sinking hours into downloading and preparing reports.
You want to create automatic processes for each of these steps:
Step 1: Download your clients’ data on a regular schedule, such as through an API.
Step 2: Set up an auditing mechanism to ensure the data is accurate and on time.
Step 3: Layer on additional metadata, such as COGS, so that your clients can see the full picture of their performance.
Step 4: Create a consistent procedure to graph the results for your clients, such as through customizable templates.
Step 5: Send and share the report to clients.
Agency owners often want to customize their dashboards to the specific needs of their clients. You can do this easily in tools like Looker, QuickSight, PowerBI, and Tableau.
Similarly, when it comes to storing your data, we recommend choosing a state-of-the-art data warehouse like Snowflake, Redshift, and BigQuery. Choosing which warehouse is best depends on your specific needs. But if you already have your other business data in one warehouse, we usually recommend sticking with it.
Wish you didn’t have to think so hard about moving your data back and forth? The good news is, Intentwise Analytics Cloud pipelines your data into warehouses for you, and makes it easy to create customizable dashboards in the tool of your choice.
Managing the Amazon channel is complex, and ad formats are constantly changing. Various non-advertising factors—such as inventory, pricing, and placement in search results—influence advertising performance. This white paper outlines the ecommerce data strategy required for advertisers to scale.
Understanding SQL is one of the most vital skills for data analysis and management.
SQL is the only way to unify disparate data sets or to leverage Amazon Marketing Cloud.
Luckily, we built a free learning module for e-commerce professionals looking to brush up on their SQL knowledge. Sign up for an account here, and get started right away.