Groups are likely the most important and key part of using Ecanvasser successfully. A Group reflects an exact segment of our database, when creating a Group from the Map tab, this segment will be based upon geography, as well as the filters applied.

Cutting a Turf (Creating a Group via the Map tab)

  1. Select Draw a Group
  2. Left click to plot a point on your map, and notice that as you pull your mouse away, a purple line comes out from your plot point

  1. Click a second time, in an appropriate location, and not only will a second plot appear, but a third plot will appear between the initial two (this will occur for every plot between now and the final one); while as you move your mouse away, you can see that you can continue to plot, as before.
  1. Repeat this process, until you have covered the required area, and complete the Group area by finishing on the same plot point you began. In the image below, you can see that final plot point has not yet been designated by selecting the original, as the purple link is still somewhat faded:
  1. As soon as we do close the loop, the Group appear in full:
  1. Should we wish to modify the Group at this time, we can do so by selecting any of the existing plot points, and dragging them in, or outwards, as we have done below to draw some nearby houses into the Group.

At this point, we can now:

   1.  Hit the Create Group button
   2. Input a Group Name
   3. Assign a Team
   4. Save Changes to create Group

Note: When you create a Group from the Map page, only Houses that are currently visible on the Map will be added to the Canvass. That is, if you have added a Filter, these houses will not be added to the Canvass list.

If you are performing a general Canvass of an area, this will not create an issue, as your Canvassers will be creating entries for all the houses they come across not yet in your Voter Database.

However, this function is incredibly powerful for when you wish to create a targeted Canvass of an area based upon any information you have in your Voter Database.

Did this answer your question?