Leveraging Amazon Connections to Boost Performance

The notion that data is the lifeblood of the digital age is not novel. It is, however, increasingly paramount. With big data comes big responsibility for eCommerce businesses. For Amazon and Walmart sellers to succeed in such competitive markets, they must have access to the right data in order to extract valuable insights that work to enhance their selling performance. This article discusses how Amazon and Walmart brands and sellers can optimize their business performance using data connections to observe and monitor relevant trends and digital shelf analytics.  

Digital Shelf Analytics 

The digital shelf, commonly described as the online atmosphere a product resides, is the virtual equivalent of how consumers shop in traditional brick and mortar stores. It is a combination of various digital experiences consumers use to discover, learn about, and buy products online.

Amazon and Walmart brands and sellers are increasingly keen on finding new, innovative, and data-backed ways to optimize their product’s digital shelf. This process is often referred to as winning the digital shelf. 

The digital shelf offers brands and sellers an opportunity to successfully showcase their products and engage with consumers at optimum times during the customer journey. Winning the digital shelf on Amazon and Walmart translates to heightened product visibility and a significant increase in sales.

Digital shelf analytics include metrics such as listing content, share of search, ratings, reviews, number of sellers, stock status, sales, traffic, and conversion rate. However, the challenge with exploiting digital shelf analytics is that it is difficult to monitor and measure them regularly.

Therefore, to fully leverage digital shelf analytics to enhance selling performance and remain competitive, you must continuously monitor these metrics to gain insights and act on them. Amazon and Walmart sellers typically use eCommerce analytics platforms that routinely scrape millions of publicly available data points to monitor up-to-date digital shelf analytics.

How Are Digital Shelf Analytics Helpful?

Digital shelf analytics are practical in that they help eCommerce businesses make data-driven decisions by identifying problems and validating optimization efforts. For instance, Amazon and Walmart sellers can get valuable information from sales breakdown to assess which of their items generate the most sales, which ones are underperforming, and which demographic of consumers your products appeal to most. Such insights help you to redirect marketing efforts in more profitable ways.

Additionally, regularly monitoring competitors’ prices can help you craft a more dynamic pricing strategy. Analytics on ratings and reviews are also useful because they are an integral part of the purchasing decision process and should be closely monitored. According to a 2021 study by Oberlo, an eCommerce service, 89 percent of online shoppers worldwide read reviews before buying products.

Insights on customer sentiments can help efficiently address or avoid negative reviews by analyzing the positive and negative reviews from other sellers selling similar products. Doing so can help deter the possibility of negative reviews and enhance a brand’s reputation. Perhaps one of the most important metrics to win the digital shelf is the share search metric since it refers to how visible a product is on the search results page.

Share of search analytics, which is influenced by product data, product descriptions, and photos, helps measure brand visibility in terms of organic search compared to competing brands. By monitoring such data, brands and sellers increase their odds of improving their product’s rank and visibility on any given online platform, whether it be Amazon or Walmart.

What Are Data Connections?

Data connections allow you to analyze data from analytics platforms to external systems. According to Microsoft, a data connection is an active link between a form and a data source that gives data to that form. The form can have a single primary data connection, and it can also have multiple data connections; at DataHawk, this is referred to as advanced destinations. 

There are two main elements to data connections: the data connection and the connection to the data source. The first is the process of data connection itself, which stores information that you choose to include in a database and how that data should be formed in tables.

The second, the data source, is a tool that retrieves data from a database to accomplish numerous types of data-driven workflows. A lot is at stake when data goes wrong. This impending possibility surfaces the increasing need for reliable data analytics software.

How Do DataHawk Connections Work?

DataHawk Connections does not require you to learn new software; simply stick to the tools you are already comfortable with, and extract valuable insights to increase your chances of winning the digital shelf. What’s more, DataHawk Connections allow brands and sellers to link their Amazon and Walmart data to their own business intelligence tools. All Amazon and Walmart data is synched automatically and on an hourly basis to ensure accurate analysis and up-to-date insights. 

With connections, you can send data to Google Sheets and analyze your Amazon or Walmart data in pre-built spreadsheet dashboards or build your own template curated to accommodate each of your most pressing business needs. Pre-built spreadsheets include: operations dashboards, search dashboards, best sellers rank dashboards, and profit and loss dashboards. 

The layout and data of the dashboards allow you to do the following much easier: examine product search performance to evaluate organic and sponsored keyword rankings; assess historical financial, advertising, and search performance data to easily correlate sales data with other metrics; explore an overview of the best selling brands and products to track and analyze historical data about the top 100 best seller rank; understand the financial health of your business and analyze your product portfolio.

Amazon and Walmart brands and sellers are likely in need of data connections if they experience at least one of the following issues:

1. Have trouble viewing and analyzing their data
2. Collecting data is tedious and messy  
3. Difficulty extracting valuable insights from the data 
4. Manually syncing data is too time-consuming 
5. Problems ensuring data is updated 

DataHawk generates and regularly updates Amazon and Walmart business data without any quality issues. Manually syncing your own data increases the potential for problems, not just with the assessment of the data but with the data itself. Synching your data automatically also allows you to increase the trust of your stakeholders by having something to show for. 

In sum, connections allow you to effortlessly sync and analyze your Amazon or Walmart product data, SEO data, finance data, ads data, and market data to more easily extract valuable insights and monitor changes or optimization efforts in product details, search, sales, and advertising performance.

Data Observability and Data Monitoring 

There is no doubt that connections facilitate the process of data observability and data monitoring. Data observability, which is used as a blanket term, refers to understanding the health or the state of one’s data system. But why would you need data observability when you already monitor your data? Well, data observability is what enables and facilitates data monitoring.

For instance, before you can monitor your business data and set up alerts, you must first obtain broad visibility of all your Walmart and Amazon data analytics. In other words, while data monitoring allows you to become aware of ongoing problems, data observability will enable you to observe and identify unknown problems.

Benefits of Analytics and Data Connections

Like many industries, analytics and data can significantly benefit Amazon and Walmart business owners. According to Forbes, a majority of business owners use only 0.5 percent of all the big data at their disposal. The other 9.5 percent of that data gets siloed in external tools or lost in proprietary software. 

However, with machine learning and the evolution of eCommerce analytics software becoming more and more adept at retrieving data, eCommerce businesses are increasingly leveraging them to transform data into actionable insights. The five key benefits of combining digital shelf analytics with data connections include: enhancing advertising initiatives, reducing financial losses, optimizing pricing strategies, increasing organic search performance, and maximizing productivity. 

1. Enhance Advertising Initiatives

A profitable advertising campaign relies on the examination of historical and contemporary data. There is PPC software out there that crunches millions of advertising-related data points on a regular basis reflective of your Amazon or Walmart ads performance so that you can better pilot future ad campaigns. 

2. Reduce Financial Losses

Analyzing digital shelf analytics can help Amazon and Walmart businesses diminish financial losses. For instance, predictive analytics, such as sales estimator tools that use historical sales data, can help eCommerce businesses accurately forecast how successful a product will be and mitigate the risk of a product flop. 

3. Optimized Pricing Strategy 

By analyzing up-to-date data on your competitors’ product prices, you can determine what products are being bought, at what price, and at what frequency. Such insights can help you optimize your own pricing strategy and price your product accordingly and timely to stay competitive. 

4. Increase Organic Search Performance

Data analytics tools for keywords allow brands and sellers to better pilot their SEO performance by providing them with their own and their competitors’ up-to-date ranking data to determine precisely at which point in time which keywords are driving the most traffic. 

5. Maximize Productivity 

Data connections and analytics can also help eCommerce businesses optimize operational efficiency by enabling them to extract their business data at scale with greater autonomy and eliminating the need to sync and update their data manually. 

How Data Can Go Wrong

Inaccurate data can have substantial consequences on business decisions, which is why Amazon and Walmart sellers seeking to optimize their businesses need to apply the latest analytics methods and practices to generate valuable insights.

However, in an effort to expedite the process of data analysis, many businesses tend to make the mistake of gleaning anecdotal correlations with little to no success in translating such insights into enhanced daily business operations. 

According to Information Age, a company that provides general intelligence for technologists, “There is rarely such a thing as ‘bad data’, but rather, a bad understanding of its intended purpose and the underlying processes used to collect it. What’s a lot more common in practice is a failure to connect data with its intended purpose or a failure to apply that data for secondary purposes to deliver value.” 

If businesses use outdated data to make real-time business decisions, it can backfire. Take, for example, search engine ranking data. Everyone knows that organic traffic is one if not the most important factor when it comes to a prosperous eCommerce business.

When your product’s ranking starts to decline on Amazon or Walmart, if you are not aware of the drop in rank when it happens, it can damage your SEO and hurt profits. Therefore, to respond to a drop in rank promptly, you must have access to up-to-date data so that you can remedy the situation by changing your choice of keywords.

Conclusion 

Data connections are comparable to a source of magic in that they help data-driven eCommerce businesses identify gaps and issues, notify them of which optimization efforts are successful, and empower them to make better and faster business decisions. 

In sum, relying on cutting-edge software to automate your digital shelf analytics allows you to enhance advertising initiatives, reduce financial losses, optimize pricing strategies, increase organic search performance, and maximize productivity.

If you are an Amazon or Walmart business that relies on data to make decisions, digital shelf analytics and data connections can bring significant competitive advantages to your daily business operations. However, to achieve the greatest long-term benefits of data connections and digital shelf analytics, your business should collect its data with the best programs built around the value they bring to both you and your customers.