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Use cases

Where DarkMath fits, product by product.

Representative scenarios. Results from specific engagements are published only with approval.

DarkMatch

Separating similar identities in a shared household

Situation: A father and son share a name and an address. Rules either merge them into one impossible customer or leave a person to sort them out by hand.
What DarkMath does: DarkMatch compares the whole profile, including phones, vehicles, service history and generation signals, and keeps two distinct identities.
Result: Two accurate customers instead of one corrupted profile, with the reasons recorded.

DarkMatch

Unifying a fragmented customer

Situation: One customer lives in the CRM, the service system and a web form under different spellings and addresses.
What DarkMath does: Semantic matching links the variants, and the Golden Record keeps every source and merge reason.
Result: A complete view for service, marketing and measurement.

DarkMatch

From five records to one financial customer

Situation: A lender’s customers hold accounts across products and channels that never roll up into one relationship.
What DarkMath does: DarkMatch resolves the records into one identity per customer and household, ready for risk review and marketing.
Result: One relationship per customer, fewer duplicate mailings and less storage.

DarkMatch

Turning data hygiene into an advantage

Situation: Stale addresses and dead contact points quietly drain campaigns and inflate churn reports.
What DarkMath does: DarkMatch validates, repairs and updates records on a schedule, flagging records that can no longer be reached.
Result: Campaigns that reach live customers, and churn numbers you can believe.

DarkMirror

Finding audiences in a new market

Situation: A brand entering new regions finds that its audience model depends on fields the new market’s data lacks.
What DarkMath does: DarkMirror profiles the best existing customers and finds similar households using attributes that predict the missing fields.
Result: Reach in the new market without lowering the standard for who qualifies.

DarkMirror

Reaching Gen Z without age data

Situation: A marketer wants younger consumers, but most records carry no age field.
What DarkMath does: Semantic attributes infer life stage and generation from behavior, with a confidence level the planner controls.
Result: A younger audience built on behavior rather than cookies or explicit age.

DarkAgent

The Cognitive Data Graph as a CDP and DMP enhancement

Situation: A platform’s CDP stores profiles but can’t explain how they connect or answer questions across them.
What DarkMath does: DarkMath hosts a Cognitive Data Graph alongside the CDP: resolved identities, households and attributes with sources, queried through DarkAgent.
Result: Answers across connected data, without replacing the CDP.

DarkAgent

Conquest and prospecting lists and audiences

Situation: A sales team needs prospects who fit, at the right time, with a reachable contact point.
What DarkMath does: DarkAgent sizes the audience with contact coverage, applies suppressions and prepares the order and delivery for review.
Result: A list you can trust, with counts, coverage and a clear next step.

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