SlideServe
Menu
Préférences
© SlideServe · v2026

Maximizing MD VoteBuilder

yoshi avatar
58 diapositives · 859 Views · Jul 20, 2014

Maximizing MD VoteBuilder. Brandon Cloud, MDP Data and Political Director bcloud@mddems.org | 410.269.8818 . Agenda. Background of VAN Where does data come from? What data is included? Cost Structure Central Committee Usage Basic Features Phone Banks, Mailings, Walk Lists, Volunteers

Maximizing MD VoteBuilder - slide 1
01 / 58Maximizing MD VoteBuilder
1 / 17

Télécharger la présentation

Maximizing MD VoteBuilder
Une image / un lien ci-dessous est fourni (tel quel) pour télécharger la présentation

Politique de téléchargement : le contenu du site vous est fourni TEL QUEL pour votre information et votre usage personnel ; il ne peut être vendu, concédé sous licence ni partagé sur d’autres sites sans l’accord de son auteur.Le contenu vous est fourni TEL QUEL, pour votre information et votre usage personnel uniquement. Téléchargez la présentation en cliquant sur ce lien. Lors du téléchargement, si vous ne parvenez pas à télécharger une présentation, l’éditeur a peut-être supprimé le fichier de son serveur.Pendant le téléchargement, si vous ne parvenez pas à obtenir une présentation, le fichier a peut-être été supprimé par l’éditeur.

F I N

Plus de contenu associé

Transcription de la présentation
  1. Maximizing MD VoteBuilder Brandon Cloud, MDP Data and Political Director bcloud@mddems.org | 410.269.8818

  2. Agenda • Background of VAN • Where does data come from? What data is included? • Cost Structure • Central Committee Usage • Basic Features • Phone Banks, Mailings, Walk Lists, Volunteers • Advanced Features • Scores • Phone Features • MiniVan

  3. Glossary of Terms VoteBuilder (VAN) • Software which allows users to manipulate and utilize the State Database of registered voters

  4. Background of VAN • Voterfile • List of registered Voters • Includes Voter’s Voting History and Method • Includes Voter’s Contact Information • Includes Voter’s Party

  5. DNC Standardization • DNC Standardization • Check Districts, Vote History, Vote Method, Number of Voters and Voter Statuses • Standardize Format of Parties, Vote History, and Precincts • Address Standardization (a key to Matching)

  6. DNC Appends Appends • Ethnicity/Religion • Census Data • Geocodes for Walking • Primary and Second Phone Appends • National Change of Address (NCOA) • Address Types • Consumer Enhancements • Deceased File Matching

  7. Cost Structure Statewide • $8,600 Congressional/Large County Executive • $4,300 State Senate and At-Large House of Delegates • $2,300 Split House of Delegates District (like 37A/B, 35A/B) • $1,150 County Council • $600-1,150 depending on the size of the county Smaller races (including municipal) are also available and range in price depending on size

  8. Cost Structure Cost Includes: • One time fee through entire election cycle • Any training necessary • As many individual user accounts under the Committee as needed • Ongoing support/troubleshooting

  9. Central Committee Usage • Maryland Democratic Party provides free access to each County Central Committee • The Chair of the Central Committee is the arbiter of access • Using VAN Central Committees can recruit and track volunteers, track donors, build and retain information about attendees to events, and of course- contact voters

  10. Basic Features

  11. Basic Features

  12. Quick Look Up

  13. Quick Look Up

  14. Quick Look Up

  15. Create A List

  16. Create A List

  17. Create A List

  18. Create A List

  19. Cutting Turf

  20. Cutting Turf

  21. Cutting Turf

  22. Cutting Turf

  23. Creating Walk/Call Lists

  24. Creating Walk/Call Lists

  25. Creating Walk/Call Lists

  26. Creating Walk/Call Lists

  27. Creating Walk/Call Lists

  28. Other Tasks with “My List”

  29. Other Tasks with “My List”

  30. Other Tasks with “My List”

  31. Other Tasks with “My List”

  32. Other Tasks with “My List”

  33. Other Tasks with “My List”

  34. Data Entry

  35. Data Entry

  36. Data Entry

  37. Data Entry

  38. Data Entry

  39. Data Entry

  40. Advanced Features

  41. Advanced Features

  42. Advanced Features

  43. Advanced Features

  44. Advanced Features

  45. Advanced Features

  46. Advanced Features

  47. Advanced Features

  48. Scores

  49. Scores • Scores are models created using many different data points • They attempt to take traditional targeting and increase the effectiveness by adding new dimensions • For example not all 0-3’s and 3-3’s are created equal- so the model improves upon that

  50. Scores