Marketing Attribution · Business Intelligence
A UK pet-food subscription brand replaced last-click assumptions with a cross-validated channel attribution engine.
A UK-based direct-to-consumer raw pet-food subscription brand lacked visibility into how its marketing channels performed. Innovatics built a channel attribution dashboard using seven unified customer-journey tables and four attribution models across the full funnel, revealing LTV:CAC by channel and replacing last-click assumptions with cross-validated evidence.
Outcomes
Proof, Not a Promise
The dashboard replaced channel assumptions with measurable evidence — tying every budget decision to long-term customer profitability rather than last-click guesswork.
The Challenge
What blocked confident budget decisions.
Three challenges blocked confident budget decisions.
- Channel measurement was inconsistent — each single-touch attribution model credited different channels, making performance comparisons unreliable.
- The customer journey view was incomplete — the team couldn't track the path from first interaction to registered member, hiding conversion drop-offs along the way.
- Profitability signals were unclear — shifting engagement patterns month-to-month made it hard to identify which channels consistently delivered the highest-value customers.
Without a durable, cross-validated way to measure channel influence, growth decisions rested on last-click instinct rather than evidence.
Our Solution
What we built.
Innovatics built a channel attribution solution inside the client's existing data and BI environment.
- A unified customer-journey data model — purchase, engagement, channel, geography, device, attribution, and coupon data transformed into seven connected tables tracking the path from first interaction through conversion.
- Four attribution models running side by side — First Touch, Last Touch, Markov, and Shapley — eliminating dependence on any single method and validating channel influence across consistent signals.
- Decision-ready dashboard views spanning an executive overview, TOFU / MOFU / BOFU analysis, LTV:CAC channel profitability, attribution validation against coupon tracking, and flexible filters.
Technology stack
What we used.
The client's existing data warehouse and BI environment, a unified customer-journey data model across seven tables, and four attribution models running side by side.
Data Foundation
Journey Model
Attribution
Surfacing
The dashboard in action
Assumptions replaced with measurable evidence.
The dashboard replaced channel assumptions with measurable evidence.
- Marketing leaders can see which channels influence acquisition, conversion, and customer value across the entire funnel — not just which channels generated the last click.
- Because performance is validated across four attribution models, budget decisions rest on consistent signals that hold up to scrutiny rather than competing channel claims.
- LTV:CAC analysis by channel ties investment to long-term customer profitability instead of short-term conversion volume.
- Filters for channel, geography, device, page, month, attribution model, and lookback window let the team investigate performance from any angle.
The deeper return
Innovatics turned fragmented marketing data into a cross-validated attribution engine that moves every budget dollar toward the channels creating the highest-value customers.
From the engagement summary
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Working on channel attribution or LTV:CAC visibility?
If something here landed — the multi-model approach, the LTV:CAC framing, the unified journey model — talk to a senior team member. No pitch deck. Just a discussion about what you're trying to figure out, build, or change.