Lead & Attribution
Goal: make source truth dependable enough to connect demand creation to booked and completed revenue.
- UTM taxonomy and lead source tracking
- Multi-touch attribution and first-touch vs. last-touch views
- Offline attribution via MMM
This plan assumes the first win is not a fancy dashboard. It is a trusted operating framework: clean funnel definitions, cleaner source tracking, a cross-brand scorecard Jacqueline can use weekly, and enough closed-loop visibility to tell what to scale, what to fix, and what to test.
By the end of 120 days, Jacqueline should have one trustworthy scorecard, one shared language for source and funnel stages, one practical testing rhythm, and a clearer view of where to standardize first. Once the systems are instrumented cleanly, the team can run tests faster, see impact sooner, rule out weak ideas quickly, and scale strong ideas across brands with more confidence.
This working example shows how the 120-day plan can turn into an operating view: portfolio health, Beehive pilot drilldown, funnel leakage, channel and campaign performance, offline media attribution, testing priorities, budget moves, and forecasting. Values are illustrative until IHS source systems are validated.
This is how I would frame the role near the top: six connected workstreams that move from cleaner attribution to better funnel control, stronger unit economics, tighter operational linkage, cleaner data connections, and more useful automation.
Goal: make source truth dependable enough to connect demand creation to booked and completed revenue.
Goal: make stage-level leakage visible so marketing, intake, and booking can improve together.
Goal: give leadership a clearer read on efficiency, payback, and where to scale or pull back.
Goal: connect acquisition quality to service outcomes instead of stopping at lead volume alone.
Goal: reduce silos by making the core systems speak the same language and hand data off cleanly.
Goal: cut reporting lag and manual effort while making the measurement layer easier to trust and use.
These are the operating companies currently listed under Intermountain Home Services. The measurement layer should let Jacqueline compare demand quality, booking efficiency, and growth performance across them without flattening away meaningful brand differences.
Intermountain can build an edge by measuring all the way from first touch through completed service, then into repeat and referral behavior. That is the bridge between marketing and true revenue operations.
Channel, campaign, and offer begin the demand path.
Call tracking, form capture, and speed-to-response start shaping quality.
This is the clearest early proof that media and call intake are working together.
The revenue event needs to connect back to the source and campaign.
Follow-up and lifecycle marketing turn one-time jobs into higher LTV.
The cleanest downstream quality signal is a customer who returns and refers.
Publicly visible evidence suggests Intermountain is partly standardized at the ops layer and still siloed at the web and tracking layer. That is a good starting point for a MOps analyst because the first 120 days can create clarity without forcing everything into one sprint.
Catalog CMS, GTM container, analytics tags, ad pixels, call tracking, scheduler, and the handoff into ServiceTitan where visible.
Rank the broken handoffs by business impact so the first fixes are tied to better decisions, not just cleaner dashboards.
Get spend, leads, calls, calls per day, booked jobs, services booked per day, CAC, ROAS, and revenue into one first-pass view by brand.
| Brand | Spend | Calls / day | Services booked / day | CAC | ROAS |
|---|---|---|---|---|---|
| Superior | $185K | 41 | 8.3 | $746 | 4.2 |
| SameDay | $140K | 34 | 7.1 | $654 | 4.0 |
| Beehive | $92K | 24 | 5.2 | $590 | 3.6 |
| Diamond | $88K | 22 | 4.7 | $620 | 3.4 |
Set standards for GTM, UTMs, event names, lead-source logic, and the offline conversion handoff into reporting.
Harden the first-pass scorecard so it is dependable enough to use in weekly leadership conversations.
Give Jacqueline a Power BI scorecard that is simple enough to scan weekly and detailed enough to act on.
| Workstream | Status | Focus |
|---|---|---|
| Tracking governance | In place | UTMs, GTM, source logic |
| Scorecard v2 | Live | Calls, bookings, ROAS, CAC |
| Cross-brand view | Live | Compare brands weekly |
Turn the scorecard into a weekly scale / fix / test rhythm grounded in ROAS, CAC, booked-job rate, and services booked per day.
Connect source quality to calls, booked work, and early revenue outcomes where the data already supports it.
Separate media issues from booking, service, and follow-up issues so channels are not blamed for downstream operational leaks.
ROAS is healthy, calls per day are rising, and services booked per day is holding above target.
Lead volume looks fine, but booked-job rate is lagging. Review routing, offer quality, and response speed before adding spend.
Reported ROAS is strong, but incrementality is not clear yet. Run a controlled test before treating it as pure growth.
Compare CAC, ROAS, booked-job rate, calls per day, services booked per day, and early payback across brands.
Prioritize the first branded search, geo, offer, or routing tests worth running once the measurement layer is trustworthy.
Recommend where shared governance should go first so the biggest silos are addressed in the next quarter.
Increase spend where ROAS is holding, CAC is stable, and services booked per day is rising.
Hold spend where calls are coming in but booked-job rate or service completion is weak.
Run quick tests where reported efficiency looks strong but incrementality is still uncertain.