Multi-Touch Attribution & Channel Mix

Incremental Revenue Optimization Dashboard

Resolving attribution conflicts with model-agnostic incrementality evidence

Period

Incremental ROAS

3.42

+8.2%

Total Spend

$847K

+12.1%

Attributed Revenue

$2.9M

+15.4%

Model Divergence

18.3%

+3.1pp

Avg variance across models

Platform-Reported Gap

+142%

Over-attribution detected

vs. Blended ROAS

Avg Touchpoints

4.7

+0.3

Per conversion path

Attribution Model Comparison by Channel

Revenue credit allocation divergence reveals which channels benefit from model choice vs. incremental contribution

Diminishing Returns Curves

Marginal ROAS by spend level — identify optimal budget ceiling per channel

Time-to-Conversion Distribution

Touch-to-conversion lag by channel — informs lookback window accuracy

Channel Performance Metrics

Channel	Spend	Data-Driven	Platform ROAS	Gap	Assisted %	Avg Position	Marginal iROAS
Paid Search	$287,400	4.21	6.85	+62.7%	34%	3.2	3.87
Facebook/Instagram	$215,800	2.84	8.12	+186%	58%	1.8	2.41
Display/Programmatic	$156,300	1.92	3.45	+79.7%	71%	1.4	1.54
Email	$42,100	5.67	12.34	+117.6%	22%	4.1	5.21
Organic Social	$38,600	3.14	—	N/A	65%	1.6	2.98
YouTube	$67,200	2.53	5.89	+132.8%	77%	1.2	2.19
Affiliate	$39,600	6.12	9.87	+61.3%	18%	4.5	5.78

Top Conversion Paths (Multi-Touch)

Most frequent channel sequences — reveals assisted conversion dynamics and priming effects

Display → Paid Search → Email → Paid Search

Conversions

1,847

Avg Revenue

$412

% of Total

12.3%

Organic Social → Facebook → Paid Search

Conversions

1,624

Avg Revenue

$387

% of Total

10.8%

YouTube → Display → Email → Paid Search

Conversions

1,392

Avg Revenue

$451

% of Total

9.2%

Paid Search → Email → Paid Search

Conversions

1,156

Avg Revenue

$398

% of Total

7.7%

Facebook → Paid Search

Conversions

1,089

Avg Revenue

$364

% of Total

7.2%

Data as of Dec 2024 • Model: Data-Driven with 30-day lookback • Incremental lift validated via holdout tests