See what is working — every capability

Attribution that finally adds up — across every location and every channel

A single attribution view that combines what is happening online (paid, organic, email) with what is happening offline (calls, foot traffic, POS), at every location, in your finance team's language.

Benchmark each location against the peers it should actually be compared to

Per-location performance framed against the peer cohort that actually matches — tenure, vertical, market tier, insurance mix, service mix, LTV cohort.

Brand voice consistency across every AI-generated output, at every location

Score every AI-generated output against your brand voice — auto-publish what is clearly on-brand, route the borderline cases to one batched review queue, send the rest back for a redraft.

Cannibalization risk scoring — on demand, not six weeks per study

For every candidate territory, get a continuous cannibalization risk score against your existing units — with the methodology preserved for FDD Item 12 audit defense.

Demographic data, per territory, refreshed automatically

Continuous demographic data for every territory you operate or evaluate — refreshed automatically as the underlying datasets update, joined to drive-time trade areas.

Draft the quarterly LP letter on day one, not week four

Per-portfolio-company quarterly LP letters drafted from the same reporting data that already feeds the board deck and the monthly exec summary — so the narrative is consistent and the numbers reconcile.

Eighteen acquisition targets a quarter. Foot traffic within minutes, not six weeks.

Live foot-traffic data from Placer.ai, SafeGraph, Near, Cuebiq, and Foursquare — joined to your territory analysis with trade-area visit volume, competitor share, and cannibalization risk scored immediately.

Evaluate prospective territories without the six-week wait

Competitor density, trade-area analysis, FDD Item 12 and Item 19 compliance, and cannibalization scoring — for every prospective territory, on demand, without a six-week consultancy engagement.

Every call, every location, one analytics view — even when each franchisee uses a different tool

Pulls call data from every platform your locations use (or each franchisee uses on their own) and joins it into one consolidated view — already linked to the customer who made the call.

Every territory grant — checked against every state's FDD rules — before you sign

The eighteen states with FDD registration or filing rules each have their own cycles. The system tracks every one of them against your actual territory record, so a grant cannot slip through unregistered.

Know exactly how many people walked into each location last month — and which marketing dollar brought them

Mobile data, in-store sensors, and ad-platform store visits — pulled into one per-location view that ties to your customer records.

KPI reporting your CFO and your franchisees can both trust

Cohort-framed KPIs — CAC, LTV, churn, retention — sliced by location, brand, channel, and time, with the methodology preserved so finance, ops, and board can all read the same numbers.

One attribution model for the whole brand misses what each market is actually doing

Per-location attribution that reflects how each market actually buys — Google Ads in Denver, walk-in foot traffic in Austin, direct mail in Tampa — joined to the same customer across every touchpoint.

One customer journey across every touchpoint — at every location

Join calls, foot traffic, POS, web, email, and reviews into one per-customer journey per location — with HIPAA, GDPR, and CCPA rules applied where they need to be.

One master record per location — reconciled across every source, propagated everywhere automatically

One trusted record per location, reconciled across POS, Google Business Profile, Yext, HR, and your CMS — and when anything changes, every marketing surface updates automatically.

Outlier alerts that compare each location to its real peers

Flag the locations that are genuinely out of pattern — judged against their peers, not the network average — and route every flag to a root-cause sketch.

Peer-cohort benchmarking for every location

Compare each location to its real peers — by revenue, traffic, market type, service mix, seasonality, and age — not to a misleading network average.

Per-location forecasting that does not wait for month-end

Sales, leads, conversion, CAC, LTV, churn, ROAS, GBP impressions — forecasted per location, per month, refreshed weekly.

Per-location reporting that does not wait for month-end

Every marketing source — paid media, GBP, POS, email, calls, foot traffic — feeds one record per location, refreshed daily, ready to roll up.

Real-estate listings joined to the rest of your territory analysis — not in a separate Excel file

Continuous commercial real-estate listings (CoStar, LoopNet, Crexi, Reonomy, ATTOM, CoreLogic) ingested per territory and joined to the same analysis already scoring competitors, demographics, and foot traffic.

Root-cause attribution for multi-location KPI drops

When a location underperforms, get an honest sketch of the cause — campaign, channel, cohort, season, local market, competitor, weather, or an ops event — instead of a 6-week investigation.

Score 200 candidate markets continuously, not one $80,000 study at a time

A single per-market score that combines competitor density, cannibalization risk, demographics, territory rules, foot traffic, and franchise-system performance — so picking the next location stops being a quarterly study.

Square in one market, Toast in another — every receipt joined to the same customer record

Continuous POS receipt integration across every vendor your locations actually run — Square, Toast, Clover, Lightspeed, Shopify POS, Revel, Aloha, Micros — joined to the customer record so the receipt closes the attribution loop.

Stop spending four weeks drafting the same board deck every quarter

A complete board deck — narrative, market-by-market revenue, channel ROI, wins, concerns, forward outlook — drafted on day one of quarter close, pulling from the data your monthly reports already use.

What is the right marketing mix in Denver versus Austin versus Tampa?

Continuous, per-market marketing mix modeling that pulls from your real attribution, foot-traffic, and call data — not a $700,000 quarterly engagement.

When revenue moves, you should know why — before the board asks

A per-market view that decomposes every revenue swing into price, volume, mix, and channel — so the question 'why did this happen?' has an answer on day one.

Where should you spend next quarter — by market — and how confident is the recommendation?

A continuous view of where the next dollar should go, by market, grounded in your actual revenue drivers, attribution, competitor density, and trade-area data.

Why do your top units hit 22% EBITDA and your strugglers 8% — and what is the actual cause?

Per-franchisee performance correlated against territory quality, competitor density, demographics, foot traffic, and operator behavior — so the conversation with each franchisee is grounded in data.

Your monthly executive summary should be ready day one — not week three

Narrative plus metrics, drafted automatically per market, so the CMO is reviewing and editing on day one instead of pulling data from twelve sources for three days.