ACV Auctions · Buyer Experience

ACV Drops
& My Buy Plan

From 341,587 listings to the one that fits. A personalized buy plan that does the navigating — so dealers stop guessing and start landing the cars that move.

Role
Product Design Lead
Context
ACV Auctions · 2026
Focus
Strategy · UX · Personalization

The concept film — "Drop it like it's hot." How Drops turns 341k listings into a buy plan a dealer can actually act on.

The opportunity

The funnel is wide. The middle is leaking.

341,587
Listings
Inventory available to buyers
6,240
Digital units sold
~1.8% listing-to-sale conversion
57%
Sell-through
~43% of inventory doesn't move

The friction isn't supply or demand — it's navigation. Buyers can't find their next car among 341k options.

Buyer reality

Today the buyer's day looks like this.

  • Browse, then guess. No system memory of what fits this dealership's lot, market, or budget.
  • Miss the moments. The right car comes up while they're in inventory search instead of on it.
  • Bid blind. No signal that a vehicle matches their plan or that a teammate is already on it.
  • Repeat tomorrow. The system never gets smarter from yesterday's wins or losses.

The product asks the buyer to do all the work the platform should be doing.

Research · Generative

We sat with the dealers who live in the feed.

Before pitching a buy plan, I led the design on a generative study with eight dealers — from one-a-month independents to 500+/year franchise buyers — to learn how they actually shop a marketplace this big: how they search, what they save, when they bid, and where the feed lets them down.

8
Dealers, in depth
45-minute sessions spanning franchise, multi-dealer, and independent buyers (BA-1 to BA-4)
~80%
Already use Saved Search
But an average of just ~1.7 each — a blunt, noisy stand-in for a real buy plan
<1%
Of bids from recommendations
The personalization gap — the platform almost never tells a buyer what to look at

Dealers already build a buy plan — by hand.

Nearly every buyer rebuilt the same plan out of saved searches, watchlists, and memory. The parameters they saved most weren't random — they were a buy plan waiting for a system to own it.

Most-saved search parameters
Make34%
Year33%
Odometer24%
Floor price22%
Green light16%
Model12%
01

The SRP is a control panel, not a decision.

Dealers scroll the feed to spot prospects and watch timers and statuses — but 88% only place a bid after opening the full vehicle page. They want the feed to pre-qualify, not just list.

02

Saved Search is the closest thing to a plan — and it’s blunt.

It floods them with launch alerts and can’t filter by condition, so many just switch notifications off — and miss the cars they actually wanted.

“Add a filter for time left in the auction. With so many 2-hour auctions running, it’s easy to miss a 20-minute auction at the top of the page.”Nate · Franchise buyer
03

They buy by “core” vs. “off-brand.”

Every dealer sorts the whole marketplace into their staple brands and the opportunistic off-brands they’ll dabble in — a personal buy plan they rebuild from scratch every morning.

04

They described Drops before we built it.

Asked what would help most, one buyer sketched the product almost exactly: a weekly email of cars launching that match my advanced-filter criteria. The buy-plan idea didn’t come from a strategy deck — it came from the buyers themselves.

The dealers were already building a buy plan by hand. Drops makes it the platform’s job.

Strategy

Four pillars. One personalized buy plan.

01

Personalize

A taste profile built from each buyer's habits — what they bid, win, pass on, watch — keyed to dealership, market and budget.

02

Explain

Every recommendation shows a "Why it fits" rationale — the buyer sees what ACV inferred and decides whether to trust it.

03

Customize

The buyer can override the algorithm — tighten or loosen any factor and watch matches shift in real time.

04

Coordinate

Team activity, notes and chat in-context so dealership groups stop bidding against themselves.

Pillar 01 · Personalize

The home page is the buy plan.

  • Weekly plan keyed to dealership, market and saved preferences
  • Day-by-day forecast — today's, tomorrow's, and the week's picks
  • Active filters surfaced as chips, editable in one tap
  • Replaces the search box as the starting point — no more cold start
→ Reduces time-to-first-action
My Buy Plan home

Pillar 02 · Explain

"Why it fits" — on every card.

  • Each card shows the rationale: buy band, mileage profile, seller history, lot gap
  • Match strength as a percentage — clear weighting, not a black box
  • The buyer can disagree and say why — feedback retunes the profile
  • Builds trust before it asks for a bid
→ Trust → engagement → bid quality
Why it fits rationale on a recommended vehicle

Pillar 03 · Customize

Override the algorithm. In one panel.

  • Presets: Balanced, Aggressive, Conservative, Top sellers only
  • Vehicles, condition, pricing, logistics, bidding rules, alerts — every dial in one place
  • Live footer: matches this week, avg match price, budget consumption
  • Changes apply immediately — the new plan previews before you save
→ The buyer is the final authority, never the algorithm
Tune Buy Plan modal

Pillar 04 · Coordinate

The team's activity, in-context.

  • Active Buying — your live bids, with current price and heat
  • Group Activity — teammates' bids, wins, notes and watchlist adds
  • Notes & team chat tied to the vehicle, not a side channel
→ Eliminates internal collision; lifts win rate

The hook · Drops

Live drops turn browsing into showing up.

  • Timed, curated drop events surface the week's strongest matches at once
  • "Just outside your buy box, but moving" — adjacents that expand wallet without losing relevance
  • Each strip is its own funnel — measurable independently
  • Directly attacks the 43% of inventory that doesn't move
→ Creates a reason to come back, on a schedule
Drops event Just outside your buy box

Modeled impact

What "good" looks like in four quarters.

MetricTodayTargetLift
Sell-through57%65%+8 pts
Listing-to-sale conversion1.8%2.5%+39%
Digital units sold (quarterly)6,2408,500+2,260
Time to first bid (median)baseline−40%faster
Repeat-buyer rate (4+ wk)baseline+15 ptsstickier

Even hitting half of the modeled lift moves +1,100 incremental units per quarter and clears ~27,000 more listings from inventory drag.

The buy plan does the navigating.

The buyer does the buying — and tells us when we're wrong.

PersonalizeExplainCustomizeCoordinate
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