Texas Ethics Commission data Release v1.4 Source snapshot September 17, 2026 Latest eligible reported transaction September 15, 2026
Canonical Vendor

Matchstick Media

Resolved vendor identity assembled from reviewed Texas Ethics Commission payee records.
Canonical vendor · Vendor ID 206021 · Resolution: Indexed Canonical Identity
Total Payments
$30,017.15
Client Filers
2
Payments
7
Activity Range
09/30/2021–02/25/2022
Largest Payment
$13,565.75
Graph: 2 connected filers · 7 payments · $30,017.15 represented
Canonical vendor assembled from reviewed Texas Ethics Commission reported payee identities. Source records remain unchanged.

Reported Names

Payee names preserved from the reported/curated source layer and resolved to this canonical vendor.

Top Client Filers

Canonical client relationships from vendor_clients_canonical.
#FilerPaidPaymentsLast Payment
1Smith, Gina D. (Dr.)$25,017.15602/25/2022
2Bradley, Stormy D.$5,000.00109/30/2021

Shared Client Network

Other canonical vendors paid by the same filer clients. Ranked by shared-client count. This is a structural overlap measure, not evidence of affiliation or coordination.
Vendor Shared Clients Focal Coverage Peer Clients Network Overlap
Ascent Strategic
Vendor ID 21074
2 100.0% 2 100.0%
Conversion Creative
Vendor ID 74297
2 100.0% 2 100.0%
ANEDOT
Vendor ID 16982
2 100.0% 642 0.3%
Method: Focal Coverage = shared clients ÷ this vendor's client count. Network Overlap = Jaccard similarity: shared clients ÷ union of both client sets.

Recent Reported Payments

DateClient FilerAmountDescription
02/25/2022Smith, Gina D. (Dr.)$1,603.08Media Buy
02/24/2022Smith, Gina D. (Dr.)$2,265.25Media Buy
02/22/2022Smith, Gina D. (Dr.)$2,265.25Media Buy
02/17/2022Smith, Gina D. (Dr.)$3,515.82Media Buy
02/15/2022Smith, Gina D. (Dr.)$1,802.00Media Buy
02/02/2022Smith, Gina D. (Dr.)$13,565.75Media Buy
09/30/2021Bradley, Stormy D.$5,000.00Media Production
Evidence basis: A canonical vendor identity was resolved using the curated vendor layer. Raw reported-payee statistics remain separate from canonical vendor statistics so the source record and analytical identity are distinguishable.