Case 01Media
Which vendor do I cancel first?
Rank every provider by cost per sold unit against closed deals in your DMS, not against clicks they self-reported.
The ledger ranks every provider by cost per sold unit against deals matched in your DMS, rather than against conversions the provider counted itself. Where several vendors claim the same car, all of the claims are shown side by side against the one sold unit, which is usually the moment the argument ends.
The bottom two are normally obvious inside a week of data. What surprises most stores is the middle: a channel with a higher cost per unit that produces customers who service with you for years, and a cheap channel that produces one-time buyers. Attaching service revenue to the deal often reverses the ranking outright. The full argument is in why last-click is a billing convenience.
Needs: DMS read access and your media invoices
LedgerDMS sync
Case 02Retention
Who is about to leave for the independent down the road?
Service intervals stretch before a customer defects, so the graph flags the lapsing pattern while they are still yours.
Defection is gradual and visible before it happens. Service intervals stretch first: the customer who came every five months starts coming every eight, then stops answering the reminder. By the time a retention campaign notices, the relationship has already moved down the road.
The graph reads that pattern against warranty status, equity position and the service history on the same record, so retention spend goes to the people actually at risk rather than to everyone who has not visited this quarter. The resolution layer that makes one service history and one sales record the same person is NexusID.
Needs: Repair order history and CRM consent state
NexusIDNexusActivate
Case 03Equity
Which customers can trade up without payment shock?
Equity position, lease maturity and service history on one record, so the trade-up list is built from payoff math.
Most trade-up lists are a mailing list sorted by purchase date, which is why they convert badly and irritate the people on them. The useful version needs equity position, lease maturity and payment history on the same record, so the question becomes arithmetic rather than a guess.
With the deal, the payoff and the service history resolved together, the list is the set of customers who can move into a newer unit at a comparable payment. That is a very different conversation from a generic upgrade offer, and it is built from facts already in your DMS.
Needs: Deal records with payoff data, current inventory
NexusIDNexusActivate
Case 04Search
Is assistant-driven search sending me buyers?
Referrals from AI assistants are captured, resolved and reconciled like any other source, so the channel is measured rather than guessed at.
Shoppers increasingly start in a chat window rather than a search box, and most analytics files that traffic under direct or unattributed because there is no referrer to read. The channel then looks like it does not exist, which is a bad reason to ignore a source of high-intent shoppers.
Referrals from assistant surfaces are captured, resolved to the same NexusID as every other touch, and reconciled against the sold unit like any other source. Volume is smaller than paid search and intent is markedly higher. The connector that puts your inventory in those answers is layer five on the platform page.
Needs: The inventory connector and first-party tag
AI commerceLedger
Case 05Compliance
Did we advertise a price we cannot honor?
Advertised price and disclaimer language are checked against current rules before publication, and blocks are logged with the rule that fired.
Every advertised price and disclaimer is checked against current state and federal rules before it publishes, not audited afterwards. That ordering is the whole point: a price that never went live is not a violation, and a price caught next quarter already is.
Blocked items are written to an append-only log with the rule that stopped them, the content it stopped, and the timestamp. That record is what your attorney will ask for, and it is the same audit schema described on the technology page. Rules enforced include the FTC Safeguards Rule, CA SB 478, TCPA consent state and CCPA deletion.
Needs: Nothing extra, governance runs across every layer
GovernanceAudit log
Case 06Group
Are two of my stores bidding against each other?
One graph across the group makes overlapping audiences and duplicate spend on the same shopper visible.
Inside a group, the same shopper often sits in two stores CRMs under two slightly different names, and both stores pay to reach them. Neither store can see it, because each one only has its own version of that customer.
One resolved graph across the group makes the overlap visible, and suppression can then be set at group level rather than negotiated store by store. Anyone already in an open deal is suppressed before an audience is pushed, so budget is not spent re-acquiring somebody the group already has. This is the problem group executives raise first.
Needs: Each rooftop DMS and CRM, in any combination
NexusIDNexusActivate
