One of the Top Amazon Ranking Experts You Haven't Heard Of

In an in-depth episode of Seller Sessions, host Danny McMillan sits down with Garfield, a pioneer in understanding and applying the concept of Geo Rank and is way ahead of the curve than most when it comes to ranking on Amazon. This podcast sheds light on how Geo Rank affects sellers and offers a critical look at common misconceptions in the industry.

It has taken four years to get him on Seller Sessions and well worth the wait…

• Understanding Geo Rank: Geo Rank does not rely on inventory levels but is driven by local shopping activities following a search. This is a significant shift from the common misconception that inventory levels directly influence rankings.
• The Impact of Inventory: Garfield explains that while inventory levels don't drive rankings, they can penalise them if the inventory is too low for the demand in a specific area, thus preventing potential stock-outs and customer dissatisfaction.
• Debunking Myths: Many sellers believe that Geo Rank normalises rankings across different regions, but Garfield clarifies that each of the 400-500 geographic zones has unique shopping activities which affect rankings individually.
• Localized Advertising: By understanding regional ranking differences, sellers can tailor their marketing strategies to boost visibility and sales in areas where their products are not performing well.
• Cost-Effective Campaigns: With detailed insights provided by Geo Rank analytics, sellers can allocate their budgets more efficiently, ensuring that they are not spending on ads in regions where they already dominate the market.
• Inventory as a Modifier: If a seller's inventory drops below what is needed to meet the demand for a specific keyword in a locale, Amazon may lower the product's ranking to prevent customer dissatisfaction from unavailability.
• Strategic Inventory Management: Effective inventory management becomes crucial to maintaining high rankings in key markets, making it a strategic area of focus for sellers to avoid penalties.

• Single Sample Issue: Most keyword tracking tools used by sellers capture data from a single location or a very limited number of locations. Garfield emphasises that these tools might be reporting ranking data from just one of the approximately 500 geographic zones that Amazon uses. This approach gives a very narrow view of a product's overall performance across the market.
• Misleading Data Representation: Because these tools often pull data from random, singular points, they do not accurately reflect the broader performance of a product. For sellers, this can lead to misguided strategies, as they might believe a product performs well universally based on its rank in one zone or poorly based on another. The lack of comprehensive geographic data can lead sellers to allocate their marketing and inventory efforts inefficiently.
• Randomised IP Sampling: Tools that do attempt to gather broader data often use randomised IP addresses to scrape Amazon, which might access different geographic data points at each scrape. However, they typically do not control for or even identify from which geographic zone the data comes, leading to a patchwork of information that does not accurately represent any cohesive market performance.

• Adversarial Nature of Amazon Advertising: Garfield describes the relationship between sellers and Amazon advertising as adversarial, where Amazon aims to maximise its revenue from each click, while sellers strive to minimise cost per click. He warns that tools and metrics provided by Amazon often serve Amazon's interests more than the sellers’.
• Brand Share and Impressions: Garfield criticises the use and effectiveness of brand share metrics provided by Amazon. He argues that these metrics are often promoted by Amazon to encourage increased spending without delivering meaningful benefits to sellers. He describes these metrics as "financial traps," suggesting that they are designed to benefit Amazon's revenue goals rather than genuinely helping sellers improve their business performance.
• Inaccuracy and Manipulation in Amazon's Data: Garfield criticises Amazon's use of data, noting that it often comes with financial traps and is incomplete or incorrect. He is particularly critical of how Amazon handles impressions in PPC campaigns, explaining that impressions are counted whenever a page is served, regardless of whether the ad is actually seen by consumers. This can mislead sellers into making ineffective optimisations based on skewed data .
• Questionable Validity of Search Query Performance: Garfield plans to demonstrate that the data provided under Amazon's search query performance metrics might be misleading. He suggests that Amazon may be withholding information or providing erroneous calculations, affecting sellers' strategies and financial decisions.

Reach Garfield Moore either via Facebook or direct via his website : https://rankdiagnostics.com/