Amazon growth,explained.

Amazon PPC waste isn't always obvious. It doesn't announce itself on the campaign dashboard. It hides in search term reports, in match-type overlap, in auto campaigns that have never been harvested, and in exact-match bids on keywords where no one actually buys.

Start by pulling your search term report for the last 90 days. Filter for spend over $50 and ACOS over your break-even threshold (roughly: 1 divided by your gross margin %). Every row in that filtered set is a candidate for negation or bid reduction. The goal isn't to negate every inefficient term on the first pass — it's to identify the structural waste: terms with high spend and zero orders that have been running for 30+ days.

Next, look at match-type overlap. If you have the same keyword in broad, phrase, and exact within the same campaign or ad group, you're bidding against yourself. The correct structure: harvest performing search terms from broad/phrase, promote them to exact in a separate campaign with controlled bids, then negate them from the originating broad/phrase campaign. This is table-stakes account hygiene that a surprisingly large number of accounts never implement.

Third, audit your automatic campaigns. Autos are powerful discovery tools, but only if you harvest them. Pull the search term report for your auto campaigns specifically. Any term with 3+ orders and acceptable ACOS should be moved to a manual exact campaign. Any term with 10+ clicks and zero orders should be negated. Left unmanaged, auto campaigns are the single biggest source of structural PPC waste on Amazon.

Finally, check for product targeting campaigns targeting your own ASINs. This is common in accounts that were set up quickly — you end up paying for traffic that was already coming to you organically. Negate your own ASINs from competitor targeting campaigns, and review whether your own-ASIN defensive targeting has positive ROI or is just spend for the sake of shelf presence.

A percentage-of-ad-spend agency earns more when you spend more. That's not an accusation — it's the math. If an agency charges 12% of ad spend and you're spending $50,000/month, they earn $6,000. If your spend increases to $80,000, they earn $9,600. The incentive to recommend higher budgets is structural, not malicious.

This creates a predictable pattern: agencies under a percentage model will tend to recommend scaling spend before conversion rate is optimized; they are slow to cut underperforming campaigns because cutting campaigns cuts their fee; and they rarely recommend reducing spend as a diagnostic step, even when the account data clearly suggests it.

Aligned incentives change the math. At Hiloha, we charge a $1,500/month base plus 5% of the incremental Amazon revenue growth we create. We do not take a percentage of your ad spend — ever. That means we have zero structural incentive to inflate your spend or drag out waste. Our 5% commission only triggers on the upside we actually deliver; if we don't grow you, we don't earn it. Cutting a wasted campaign doesn't hurt us — it helps us. Recommending a spend reduction to improve ROAS efficiency is something we can say honestly, because our fee is tied to your revenue growth, not your budget size.

The question to ask any agency you're evaluating: 'What happens to your revenue if we cut our ad spend by 30%?' A percentage agency loses 30% of their fee. An agency paid on growth has every reason to support you making that decision if the data warrants it — because a leaner, higher-ROAS account is the foundation for the growth that does earn them a commission.

Neither model is inherently evil — the percentage model works fine if the agency is disciplined and aligned. But the incentive structure is real, and sellers should understand it before signing. The model you choose shapes the advice you'll receive.

Amazon's A9/A10 algorithm is a conversion-weighted relevance engine. It cares about two things: does this listing match the query (relevance), and when shoppers land on it, do they buy (conversion)? Organic rank is the product of both signals, not just one.

Relevance is established through your title, backend search terms, bullet points, product description, and A+ content. The title carries the most algorithmic weight and is also the first thing a shopper reads — it has to serve both. A good title structure for most categories: [Brand] + [Primary Keyword] + [Key Feature/Use Case] + [Size/Count/Variant if relevant]. Keep it under 200 characters. Avoid keyword stuffing — Amazon has penalized overtly-stuffed titles, and a readable title converts better anyway.

Backend search terms remain underutilized. You have 500 bytes per field. Use all of them. Prioritize: synonyms, misspellings that are actually searched, Spanish equivalents if your audience includes bilingual shoppers, and long-tail phrases that don't fit naturally into the title or bullets. Do not repeat keywords already in the title — the index picks them up from the title regardless, and duplication wastes your backend space.

Conversion signals are where most SEO guides stop short. Amazon knows your session-to-order rate, your click-through rate from search results (influenced by main image and price), and your return rate. All of these feed into rank. A listing with excellent keyword coverage but a poor main image, confusing pricing, or a weak review profile will be outranked by a better-converting listing with slightly thinner keyword coverage. The SEO work and the conversion work are inseparable.

Review velocity is the third signal most sellers don't fully control. Amazon's organic ranking algorithm favors listings with recent reviews over listings with a large but aging review base. Enrolling in the Early Reviewer Program (where eligible) and using the Vine program for new launches is standard practice. But the most durable review strategy is simply shipping a product that works as described.

Amazon states that A+ Content can increase conversion rates on average. That's a directional claim, not a guarantee. The more honest framing: A+ is the best tool you have for answering the objections shoppers have after reading your bullets. Used well, it removes purchase friction. Used poorly, it's a vanity branding panel that doesn't move conversion at all.

The modules that actually convert are the ones that answer the question 'why this over the alternative?' Comparison charts — using the A+ comparison module or building one in image form — are among the highest-performing elements because they do the shopper's evaluation work for them. A shopper who would have left to compare your product against a competitor doesn't have to leave if you've already built the comparison.

Technical detail modules are the second high-performer. If your product is in a category where specifications matter (supplements, electronics, tools, skincare), a well-designed ingredient/spec breakdown module in A+ extends what the bullets can't fully communicate. It also supports backend indexing — Amazon's algorithm indexes text inside A+ content.

Premium A+ (available to brands with high Brand Registry compliance scores) adds a video module and interactive hotspot features. The video module in particular is worth the effort: short-form product demo videos inside A+ have consistently shown above-average engagement. Keep them under 90 seconds, lead with the product in use.

The most common A+ mistake is treating it as a brand story canvas. Shoppers on Amazon are in purchase mode, not brand discovery mode. A+ that opens with 'We believe in quality...' and buries the product specs loses against A+ that opens with the problem solved.

Answer Engine Optimization (AEO) is the discipline of structuring your brand's digital presence so that AI-powered answer engines — ChatGPT, Perplexity, Claude, Google AI Overviews — cite and recommend your brand in response to buyer intent queries. For ecommerce brands, this is becoming an increasingly important channel as buyers shift from Google keyword searches to conversational queries.

A buyer asking 'What's the best collagen supplement for women over 40?' is no longer getting a list of ten blue links. They're getting a synthesized answer from an AI that has read thousands of sources, reviews, and product pages. If your brand is well-represented in that source pool — good reviews, authoritative product descriptions, clean structured data, visible press mentions — you show up in that answer. If your brand is invisible outside of Amazon's walled garden, you don't.

The foundational AEO move for most ecommerce brands is getting a brand website with real content: honest product descriptions, ingredient/specification transparency, use-case guides, and FAQ content that anticipates the questions buyers ask. AI crawlers index this content. A website that reads like a press release doesn't help you. A website that actually answers the questions buyers have — clearly and specifically — does.

Structured data (JSON-LD schema markup) is the second layer. Product schema, FAQ schema, Organization schema — these are machine-readable signals that help crawlers understand what your brand is, what your products do, and what questions they answer. This is non-optional for brands serious about AEO.

Reviews are the third pillar. AI answer engines aggregate review sentiment at scale. A brand with consistently strong reviews across Amazon, third-party review sites, and its own website has a structural AEO advantage. The answer engines are, in essence, doing what a smart shopper would do: reading the reviews and summarizing them.

Amazon product photography exists on a spectrum from 'required to list' to 'actively increases conversion.' Most sellers operate near the left end of that spectrum without realizing it. The gap between studio-grade creative and acceptable-quality images is visible in the data: click-through rate, add-to-cart rate, and conversion rate all correlate with image quality — particularly main image quality.

The main image has one job: get the click. Amazon's algorithm measures CTR from search results, and it is directly influenced by your main image and price. A main image should show the product clearly, at scale, with enough context for the buyer to understand what they're getting at a glance. White background is the Amazon standard, but 'white background' doesn't mean 'phone photo against a white wall.' It means a clean, well-lit, high-resolution image where the product is the hero.

The secondary images answer objections in order. Think about the questions a buyer who's never heard of your brand would ask while standing in a store aisle, reading the back of the package. Those questions are your image brief. Image 2: what is this, exactly? Image 3: what does it do / how does it work? Image 4: who is it for / when do I use it? Image 5: what am I getting (size, count, quantity reference)?

Lifestyle images are the most common creative investment and often the least conversion-efficient. A lifestyle image of someone smiling while using your product doesn't answer objections — it reinforces brand feeling. That's valuable, but it should come after the functional images have done their work. Too many accounts flip the order: strong lifestyle, weak functional content.

Video is the highest-leverage creative investment for most categories. Amazon's data consistently shows that listings with video outperform listings without. The video brief is simple: show the product being used by a real person, in a real context, solving a real problem. Under 60 seconds. No generic music bed and logo animations — buyers skip those.