Built by Amazon sellers. Powered by the Hive.
HiveSeller's proprietary Swarm Intelligence algorithm builds, manages, and executes your Amazon ad campaigns — optimizing for RPV (Revenue Per View) and AEO (AI Engine Optimization for Alexa for Shopping, voice, and the AI shopping era) in one command center. Spend less time worrying about ad spend. Focus on running and scaling your business.
Curious first? See the HiveMind in action →
Swarm Intelligence
Our proprietary algorithm learns from every seller in the hive. Anonymized patterns flow back into your account as smarter recommendations.
RPV-optimized
Revenue Per View — the metric that catches leaks ACoS can't see and surfaces the campaigns quietly carrying your account.
AEO-ready
AI Engine Optimization. Your listings + ads tuned for Alexa for Shopping (Amazon's AI shopping assistant), voice shopping, and the era where AI does the buying.
Why HiveSeller is different
Every PPC platform claims "AI." Most are rule-based engines with a chatbot bolted on. HiveSeller is a different animal — here's the three reasons why.
We're not consultants who learned PPC to sell a SaaS. We are active Amazon sellers building the tool we needed and couldn't find. Every feature ships because a real seller (us, or one of our hive) hit a real wall and we built the answer.
A platform from sellers, for sellers.
Every account that joins makes the algorithm sharper for everyone. Anonymized patterns from across the hive flow back into your recommendations — so the platform you sign up for today is meaningfully smarter in 30 days, in 90 days, in a year. Most tools degrade; ours compounds.
Network effect, baked into the algorithm.
Other tools chase ACoS. We optimize for two things at once: RPV (the metric that exposes hidden waste + hidden winners) AND AEO (positioning you for the era where Amazon's Alexa for Shopping, voice assistants, and AI shopping flows do the buying). One platform, both fronts.
The metric of today + the discovery layer of tomorrow.
Why Revenue Per View
Every Amazon dashboard optimizes for ACoS. ACoS measures cost versus the sales it can attribute — fine for cost accounting, blind to the attention you actually bought.
Revenue Per View is the dollars earned per impression delivered. It tells you whether the eyeballs you paid for are actually buying — and reveals the campaigns that are quietly carrying your account vs the ones quietly leaking it.
Same ACoS · very different RPV
SP — Phone Mount Auto
✦ scaleSP — Phone Mount Brand
× leakSame 30% ACoS. One earns $0.078 per view — a real scaling opportunity. The other earns $0.006per view — paid attention that doesn't convert.
ACoS would tell you they're equally healthy. RPV tells you which one to scale and which one to fix.
Why AEO (AI Engine Optimization)
Alexa for Shopping (formerly Rufus) answers product questions in plain English. Voice assistants take orders without showing a search page. AI agents do the buying. The traditional ad slot is shrinking — and the listings that get cited by AI engines win the shelf.
AI Engine Optimization tunes your listings, keywords, and ad structure for how AI engines parse, cite, and recommend products — not just how the legacy search ranking sees them. HiveSeller's swarm already maps which buyer-question shapes convert in your category, and turns those patterns into actions you can approve.
Catches buyer-question search terms early
3+ word natural-language queries are the AI-shopping signal. The HiveSeller swarm flags them in your search-term report the day they appear.
Surfaces listing-copy gaps
If an AI engine couldn't answer 'is this dishwasher safe?' from your bullets, you're invisible to Alexa for Shopping and its peers. We score every listing for AEO-readiness.
One platform, two optimization layers
RPV + AEO simultaneously. Other tools force a tradeoff; we treat them as the same problem at two different time horizons.
“What's the best dishwasher-safe phone mount for my F-150?”
Stockout protection
The fastest way to incinerate an ad budget is to scale a winning campaign whose underlying product is one bad week from stockout. By the time Amazon's buy-box drops, you've already paid for clicks you can't fulfill — and you've lost the listing's organic ranking.
HiveSeller's Inventory tab tracks every SKU's current units, reorder trigger, and supplier lead time. The advisor reads this table BEFORE recommending any scale-winner action — so a campaign whose underlying SKU is in “reorder now” status never gets the green light to spend more, no matter how strong the PPC metrics look.
Velocity computed automatically
Daily units-sold rate is derived from your spProductAds purchases — no manual data entry beyond the initial stock count.
Reorder triggers + lead-time math
Status flips to reorder_now the moment days-remaining falls under your lead time, so the warning lands before you'd actually stock out.
Wired into the action engine
Every scale recommendation is gated on inventory status. The platform won't queue 'pour more spend into this winner' when the winner is about to go OOS.
Days remaining: 8 (lead time: 14d). Reorder triggered. Status: reorder_now.
125 days of stock at current velocity (4/day). Plenty of runway — scaling fits.
3 units in stock vs trigger of 5. Inventory critical — pulling bid 40% to slow burn.
FLEET LEARNING
Tesla's fleet of cars share what they learn about every road condition. HiveSeller's fleet of accounts share what they learn about every PPC decision. Your account never sees another seller's numbers — but you inherit every category-wide pattern they've already discovered.
Every action we recommend gets scored 14 days later. Rules that consistently make money keep firing; rules that consistently don't get flagged for review. The 25 PPC rules we ship with aren't locked — the Hive grades them.
When 'iphone holder' converts in cat-furniture accounts but kills CVR in phone-mount accounts, the Hive knows. Your search term suggestions come pre-filtered against the patterns sellers in your category already proved out.
Most ACoS 'benchmarks' online are vibes. Ours are the actual median + quartiles from sellers in your category — recomputed every Monday. You see your real percentile, not what some blog post made up.
When the Hive spots a pattern the 25 hard rules don't cover — a category-specific waste term, a zone-specific bid heuristic — it surfaces the candidate for review. Promoted patterns become rules everyone benefits from.
A taste — anonymized benchmarks the Hive publishes
Phone mounts
18.2%
median TACoS
top quartile < 11%
Mid-AOV consumer electronics
Cat furniture
24.7%
median TACoS
top quartile < 14%
Long consideration cycle
Kitchen accessories
21.4%
median TACoS
top quartile < 12%
Heavy gift-giving spikes
Home office
16.8%
median TACoS
top quartile < 9%
Recurring B2B + B2C overlap
Sample values shown. Real benchmarks recomputed every Monday from the live fleet — visible to you the moment you connect.
Your data never appears in another seller's view.
Fleet learning aggregates only. The cross-category benchmark tables don't carry an account_id column — by design, not just policy. Your campaigns, your keywords, your conversion data stay inside your account. The patterns that cross over are anonymized aggregates with 3-seller minimums — never individual rows.
Convinced? Drop your email
Private beta — one email is all we need. We'll let you in the moment access opens, plus the occasional PPC insight mined from the hive.
How the Hive works
COLLECT
Real data from every campaign, keyword, and search term.
ANALYZE
AI finds patterns the spreadsheets missed.
OPTIMIZE
Decisions queued for your approval — never silent edits.
EVOLVE
The Hive grows. Every customer's outcomes feed the hive.
Swarm Intelligence
Patterns across the hive
Real Data & Analytics
Your campaigns, visualized
Manage All AMZ Ads
Sponsored Products, Brands, Display
AI-Powered Optimization
You approve, AI executes
Inventory-Aware Ads
No spend on SKUs about to stock out
FAQ
A note from the team
We're Amazon sellers. We built HiveSeller because we needed it.
We were tired of paying expensive agencies to do things we knew could be automated. We were tired of AI tools that promised intelligence and delivered rule trees. We were tired of optimizing for the metric our competitors optimized for. So we built the platform we wished existed: one that learns from every seller in the hive, surfaces the metrics that actually move revenue, and gets us back to running our businesses instead of babysitting bids. If that sounds like the tool you've been looking for, we built it for you too.
— The HiveSeller team