# Eric Coats

Eric Coats shares practical advice for Amazon sellers, including how to analyze returns, repeat purchases, and inventory to improve business decisions.

- Profile: https://b2binfluencer.marketing/creators/eric-coats/
- LinkedIn: https://www.linkedin.com/in/eric-coats
- Topics: sales, customer-retention, inventory-management
- Based on 13 dated posts, latest 2026-10-05

## Summary

Eric Coats is most useful for practical Amazon seller advice on returns, repeat purchases, and inventory decisions.

- Best for: Amazon seller growth agencies or home-goods brands needing diagnostic help with returns and inventory.
- Not for: Consumer brands or creator-platform companies seeking paid LinkedIn creator campaigns to reach marketing leaders.
- Check first: Ask for client references, engagement terms, and measured business outcomes beyond illustrative figures.

### Takeaways

- January returns can include purchases from earlier months, masking January order return rate.
- Match return order IDs to purchase months and compare cohort rates with reported rates.
- Use return reasons and reviews to find root causes, then change pages, packaging, manufacturing, or service.

## Main ideas

- **Platform-reported numbers can hide what is actually happening**: Coats distrusts headline metrics until they have been rebuilt from order-level data. Amazon reports a monthly return rate as units returned divided by units sold that month, but January returns include holiday purchases from earlier months. Sellers who accept the reported figure can mistake a healthy product for a problem, or miss a real one until later in the quarter. Coats recommends matching each return to its purchase month, then calculating the rate for each purchase cohort separately.
- **Reduce returns by finding root causes, not by watching the average**: Coats frames returns mitigation as both a profitability and customer-experience project: fewer returns mean better margins, happier customers, better reviews, and more sales. They recommend a four-step loop: check rates, identify products with excessive returns, determine root causes from return reasons and reviews, then address them. Coats also tells sellers to read neutral and positive reviews for complaints, even when overall sentiment looks fine.
- **Repeat-purchase data should set how much you spend to acquire customers**: Coats argues that lifetime value, not intuition, should govern front-end marketing spend. Amazon's Brand Analytics reports repeat-purchase behavior weekly, monthly, quarterly, and yearly. Whether a brand retains 4% or 40% of customers should dramatically change what it is willing to pay to win a new one. Coats also treats the trend as a diagnostic: a falling repeat rate may point to competition, quality, or negative reviews, while a rising one may reflect promotions, tentpole events, or a strong product.
- **Aging inventory is a capital problem, not just a stock count**: Coats points to Amazon's Inventory Analytics dashboard to see aging, aged, and total inventory against fulfillment and sell-through. They focus on the costs: what stagnant stock is costing the business, what the platform recommends, and how the data breaks down by SKU. This framing turns inventory from a warehousing question into a cash-flow and pricing question.
- **Once you can identify a business buyer, support the relationship directly**: Coats describes a platform change that matters mainly for business-to-business sellers: Amazon historically did not report the business name on B2B orders, making it hard to give business customers the support they need. A buyer-company-name column now appears in the All Orders report, allowing sellers to identify the purchasing business and handle post-purchase and technical support more directly. Coats sees this as a route to retaining high-value accounts, while drawing a clear line at Amazon's rules: customer support is allowed; soliciting Amazon customers off the platform is not.

## Work to read

- [Using Cohort Returns Analysis to Reveal True Performance](https://www.linkedin.com/posts/eric-coats_boring-amazon-hack-23-this-is-a-fun-one-activity-7293052692585754624-RYYy)
- [A 4-Step Strategy for Amazon Returns Mitigation](https://www.linkedin.com/posts/eric-coats_boring-amazon-hack-31-inventory-analytics-activity-7314049275007549440-K--k)
- [Leveraging Brand Analytics to Measure Customer Lifetime Value (LTV)](https://www.linkedin.com/posts/eric-coats_boring-amazon-hack-26-repeat-purchase-behavior-7300294690636013568-G0_D)
- [New Amazon Feature: Identifying B2B Buyer Names](https://www.linkedin.com/posts/eric-coats_boring-amazon-hack-43-see-business-names-activity-7358568909052002304-k1vw)
- [Inventory Analytics: Managing Stagnant Stock and Capital Flow](https://www.linkedin.com/posts/eric-coats_boring-amazon-hack-31-inventory-analytics-activity-7314049275007549440-K--k)

## Brand relationships

- **Amazon** (mention)
- **Kapoq** (mention)

## Partnerships

Eric Coats specializes in practical strategic advice for Amazon sellers, covering business operations, inventory analytics, true return rates, and repeat purchase behavior. Brands interested in creator partnerships or corporate sponsorships should ask about available formats and how to inquire.

## Alternatives

- Suharsh Mahajan: Choose Mahajan when the agency's brief shifts from Amazon report mechanics to why customers do or do not come back. The two posts work through cohort retention at a handmade jewelry store and a pricing experiment at a cafe: group customers by the month of first purchase, find that first purchases were strong and second purchases almost absent, then act through email, thank-you notes, and price changes. Mahajan's pattern is to ask a different question of the numbers, find the leak, and change the customer experience. For a brand that is not primarily a marketplace seller, or a brief about repeat-purchase demand and pricing rather than returns root cause, that maps directly onto the diagnosis the agency has to present.
- Adam Kitchen: Choose Kitchen when the engagement is about lifetime value and repeat purchase across a portfolio rather than a single returns problem. One post breaks customer value into four levers—acquisition, first-order spend, repurchase frequency, and repeat spend—and shows a US outdoor brand where 12-month value rose each year while the month-one repeat rate fell from 10.2% to 8.9%, with growth coming from higher first orders. The second reports two brands above $80 million in revenue where bundling on the first purchase hurt 180- and 365-day LTV. This is the right evidence when a client wants repurchase economics tested before spending more on acquisition.
- Brandon Fishman: Choose Fishman when the campaign needs forward-looking Amazon channel strategy or SKU-level profit work. The two posts cover Accelerate announcements—Prime Air drone delivery, Amazon Quick pulling Seller Central data into AI, Seller Flex, Profit Analytics, Scenario Modeling, better inventory visibility, and AI supply-chain planning—and Fishman's stated approach of starting Amazon audits at the SKU-level profit and loss, so a brand can see which products are losing money to ad spend, fees, fulfillment, or returns. For a client weighing which Amazon features to adopt or where margin leaks by product, this frames the decision.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/