CDLX vs CNET

Cardlytics, Inc. Common Stock vs ZW Data Action Technologies Inc — Valuation Comparison 2026

CDLX

Advertising Agencies
Cardlytics, Inc. Common Stock
Quality
4.3
out of 10
Value Trap
33
LOW
Price
$0.71
Last close
Models
7/13
Active
VS

CNET

Advertising Agencies
ZW Data Action Technologies Inc
Quality
4.9
out of 10
Value Trap
47
WARN
Price
$0.70
Last close
Models
10/13
Active

Model-by-Model Comparison

ModelType CDLX Fair ValueCDLX Upside CNET Fair ValueCNET Upside
Bayesian DCF Intrinsic $0.81 +33.8% $0.23 -67.0%
Earnings Power Value Intrinsic $0.23 -68.9%
EROIC Spread Intrinsic $•••.•• ••.•% $•••.•• ••.•%
First Chicago Scenario $•••.•• ••.•% $•••.•• ••.•%
ML-RIV Intrinsic $•••.•• ••.•% $•••.•• ••.•%
PWERM Option-Based $2.69 +277.3% $1.97 +179.5%
Regime Cross-Sectional Relative $•••.•• ••.•% $•••.•• ••.•%
Sentiment SOTP Hybrid $•••.•• ••.•% $•••.•• ••.•%
CUCE Ensemble Ensemble $•••.•• ••.•% $•••.•• ••.•%
FTNN Topology Relative $•••.•• ••.•% $•••.•• ••.•%
🔒

Unlock Full 13-Model Comparison

Access all valuation models for CDLX vs CNET — including EROIC Spread, First Chicago, Markov DDM, PWERM, and 7 more.

Access Full Analysis — From $27/mo →

CDLX vs CNET — Which Stock Is More Undervalued?

CNET scores higher with a 4.9/10 quality rating vs CDLX's 4.3/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Cardlytics, Inc. Common Stock (CDLX) and ZW Data Action Technologies Inc (CNET) across 13 institutional-grade valuation models reveals how each company's intrinsic value stacks up against its market price. CirclFi's engine processes SEC EDGAR 10-K and 10-Q filings, FRED macroeconomic data, and GDELT news sentiment to generate independent fair value estimates daily.

CDLX currently trades at $0.71 with a QOC of 4.3/10, while CNET trades at $0.70 with a QOC of 4.9/10.

Both companies are analyzed with models spanning intrinsic (Bayesian DCF, EPV), scenario-based (First Chicago), regime-switching (Markov DDM, RCMH-DCF), machine learning (ML-RIV, FTNN Topology), and ensemble methods (CUCE).