Amazon is continuing to make more and more data available to its Sellers as demand for greater visibility grows.¹ While these developments offer the potential for more valuable insights, it also raises the question of how Sellers can improve their process of drawing these insights — specifically through the use of analytics tools.
So how can you choose the best Amazon analytics tool for you out of the many options on offer?
Today we’re going to run through the seven steps you need to follow to find the right Amazon analytics tool for your business. Let’s dive right in…
Suggested reading: The value of analytics comes down to how they help you better understand your customers — check out our latest eBook You Don't Understand Your Amazon Customers and It's Costing You to get up to speed.
Step 1: Establish your business objectives
Before investing in any tool or solution, define your desired outcomes. This process is crucial whether you’re new to Seller Central or already have a solid sales record and a well-established Amazon business. Boosting your Amazon analytics capabilities is great but not an end goal in itself. It should be a step towards delivering specific business objectives, like:
- Having a successful product roll-out.
- Increasing market share by a specific percentage.
- Seeing an uplift in profitability.
High-level goals like the above can help you hone in on the analytics software features that are most critical to your business. For example, you’ll need a tool with solid competitor analysis capabilities to increase market share. Meanwhile, increasing profitability requires a tool that helps you drive down marketing costs, upsell to your customers, and better understand your Customer Lifetime Value (CLV).
Once you’ve got a better idea of what you are aiming for, you can start to consider which tools for Amazon Sellers can help you realize these goals.
Step 2: Investigate what Amazon offers for free
The most logical place to start is the free tools that Amazon offers to Sellers. Seller Central and Vendor Central offer large troves of data. Amazon Advertising reports are the baseline.
The most effective free analytics option is Amazon Brand Analytics (ABA), free for qualifying users who enroll with the Amazon Brand Registry program.
While it’s worth taking some time to explore these free options before moving on to third-party tools, these reports pose two critical challenges, namely:
- A lack of hard numbers.
- And a lack of contextual information.
Though certain upgrades like the ABA Search Term Report now reporting on actual search volume as opposed to just the most popular search phrases prove that Amazon is moving in the right direction, the fact remains that Sellers still have to trawl through a number of reports to then get insights worth actioning.
These free Amazon reports might suit small businesses just fine. But if you have a lot of product listings, it can be harder to bridge the gap from data to action. In these cases, you should consider more sophisticated solutions.
Suggested reading: ABA is an especially crucial tool to understand. To learn more about ABA best practices, check our free eBook: Mastering Amazon Brand Analytics.
Step 3: Match the size of your operation to your data needs
To reiterate what we said above, larger Amazon businesses will only really profit from more sophisticated analytics tools. The more products you sell (both in terms of product lines and volumes), the more variables and data sources you are dealing with, and the more value you can derive from good data analysis.
So if you are just starting out or have a small operation, you can go a long way using Amazon’s own tools and augmenting that information into spreadsheets. Amazon makes all of its information available in CSV files, with handy features such as regular email delivery if you need it. Remember, ABA doesn’t keep data available indefinitely, so exporting and saving the information is critical to building up long-term analytics.
Augmenting basic Amazon data manually will allow you to track fundamental long-term trends and craft personas beyond aggregated demographic data. Eventually, the volume of data flowing through Amazon will make manual analysis difficult to scale.
Fortunately, several tools can help you automate Excel. One such software is Supermetrics. PowerBI and Tableau are also good choices, although they do require users to refresh data manually. They all provide good dashboards with exploratory analysis. Of course, these three are third-party tools that need investment. Whether or not you already have access to them (for another business purpose) should weigh on your calculation here.
Not everyone is comfortable storing and classifying Amazon data, manually augmenting CSV files, and deriving insights from the results. If this kind of work fills you with dread, then you should consider third-party analytics tools that can:
- Centralize and simplify your data review.
- Provide long and short-term views.
- Augment the detail of your analysis beyond what you could achieve manually
Step 4: Look for integration across Amazon data channels
At this point, it’s worth taking a brief step back to take a holistic view of integration. Amazon data can provide deep insights into customer behaviors and their buying habits. Yet the data is siloed across different locations, and it can be hard to put together. The most cutting-edge solutions adapt to data trends and find the most useful data reports for you.
With integration in mind, the idea automation software will be able to pull data from across the Amazon ecosystem: advertising, retail, etc. If you want a transaction-level view of different products’ performance rather than a simple high-level picture, utilizing Amazon Selling Partners API (SP-API) — an upgrade on Amazon Marketplace Web Services — is especially important. Of course, you also want a tool that can integrate data from other sales channels that you use.
Step 5: Prioritize transparency and data access
Finding patterns and trends is a key benefit behind insightful analytics. When you can identify and understand trends, you can repeat success and mitigate failures. With enough data and strong analysis capabilities, you can take action to keep ahead of the curve. If you can cut down on the time you (or your team) spend crunching numbers, you can free up capacity to spend on using your data-driven insights to create better business outcomes.
So why are transparency and data access important? Well, if you are confident in what sources are driving your decisions, you can keep a close eye on the relationship between your marketing and sales outcomes.
You need a tool that tells you why it makes (or recommends) certain decisions and allows you access to the underlying data if needed. This helps with integrations across your entire operation.
A full-spectrum system that provides daily updates, lasting trends, and access to the granular data behind them can provide you with this confidence. Then you can make those critical cross-department decisions and internal adjustments based on the most profitable days, products, and campaigns.
Step 6: Stay focused on outcomes
At this point, you should have a good sense of what the right analytics tool will help you with, including:
- Providing shortcuts to making better-informed decisions
- Providing useful insights
- Contextualizing those insights for you
- Explaining why something is happening
- Giving you suggestions on how it can be improved
That’s all well and good, but what outcomes are you really looking for here? You probably already have some idea, but here are some of the most important outcomes your analytics should be able to deliver…
Detailed customer personas
One goal of pulling data from across the Amazon ecosystem is to understand your customers, from which products they’re buying to who they are. The difficult part is using the relevant information to create a real-time, detailed picture of your customer personas. Your analytics tool should do this for you.
‘Buying trajectories’ derived from purchasing patterns
Amazon provides data on purchase volumes, and Amazon SP-API provides granular information on the different products that specific individuals buy, as well the order in which they are purchased. When you cross-reference this information with your customer persona categories, you can establish ‘buying trajectories.’ Your analytics tool should deliver clear projections, which in turn enables you to target ads and create bundles.
Insights on how much each customer is worth to you
In the longer-term, analytics tools can crunch the numbers on repeat purchases, and combine that information with persona and PPC (pay-per-click) data. Eventually, you can develop detailed estimates of how many products different buyer personas are likely to purchase. Predictions can be made with startling accuracy — delivering robust information on CLV and insights for your inventory management.
Improved search terms and keywords
If you’ve been using standard keyword research tools, you’ll know the main issue with them is in the details. Sifting through your current Amazon PPC campaigns’ product performance information and scoping out new search terms is only half the battle. Analytics tools powered by machine learning can do the heavy lifting required to spot opportunities. This analysis goes well beyond simple keyword ranks.
The primary way to do this is by comparing product categories to how different search terms perform. You get a powerfully nuanced picture by combining persona categories, geo-location analysis, product research, basket comparisons, and purchase patterns. A good analytics tool will present this information to you in an easy-to-digest dashboard.
Step 7: Create a plan for the future
Adopting a tool or platform requires energy, time, and money. So you don’t want to invest in software that’s only going to work for your business today. You really need a tool that will help you grow, and help you scale your analytics as you grow.
The Amazon ecosystem is constantly shifting and changing. So your solution of choice needs to be both aware of that and capable of adapting to those changes effectively — especially when it comes to leveraging new data types as and when they become available.
Consulting services can also be useful. Data specialists who design and build software tools often have insight into how their product can be best deployed. Although nearly all SaaS products have a self-service option, these consulting services can help you ensure that your future path is correct. What’s more, analytics can reveal very specific business issues that these complimentary professional services can help you resolve.
What the right tool for the job looks like
The core question when choosing an analytics set up is to ask how it will help you succeed against your competitors in an increasingly overwhelming marketplace.
The true measure of any analytics tool’s efficiency is in how it boosts and informs your ability to act. After all, your aim is to really thrive in the Amazon market. Even the cleverest insights won’t help your sales and profits if they just sit on the shelf.
Faster and more actionable results are ultimately what you are looking for from an analytics tool. It’s worth keeping this in mind as you explore your options. If you want advice tailored to your specific needs, get in touch — we’d be happy to help.