Using AC Advanced
Load the event & listing that you want to have Autocriteria applied to.
Select the AC button to load Autocriteira Suggestions.
If the AC button is greyed out, autocriteria is not available at the venue and no suggestions will be applied.
When successfully loaded:
A message saying Autocriteria has been applied will appear.
The base section for autocriteria will highlight green on the map.
The base section will be present under the map in a blue box.
Sections will be selected off the map in blue highlights.
A dynamic row range will be applied to each section in the criteria.
AC Advanced had more flexibility to Alter suggestions based on the value slider and filters.
Value Slider: Each section and row is assigned a relative value within the venue. By adjusting the values on the slider, you will be able to include and exclude sections of certain values compared to your own.
The further into the negative values (inventory worse than your own) you go, the more expansive and aggressive the criteria become.
-100 to 100 - Price against everything
-100 to 0 - Price against only equal or worse inventory
0 to 100 - Price against only equal or better inventory.
Venue Level: Allows for venue-wide results to be returned, purely by what the data dictates. In some cases, this can lead to odd results where "irrelevant" sections share the same value score.
Section Level Filter: Filters results by only sections on the same section level as your own. I.E. 100s only price against 100s, 200s only price against 200s.
The data model may suggest limited premium sections/rows of less valuable section levels which match your listing's relative value. I.E - If you have row 20 in the 100s, Rows 1-3 from the 200s may be selected due to their premium. The value may match, but you may want to limit the criteria to the most relevant sections.
Zone Filter: Filters criteria only by sections in the same zone as your inventory. This is the most restrictive filter.
Filter Value: With dynamic row ranges, the data model may suggest limited premium sections/rows of less valuable zones which match your listing’s relative value. I.E - If you have club seats, Rows 1-3 from the best non-club seats may be selected due to their premium. You may only want to limit the criteria to club seats.
Rows Beyond Own: Filters the global max row range by the value provided. It adds the value from the filter to the base listings row. For example, if you have a row 3 and you input 5, the max row the model will allow from any section is out to row 8. Base Row + Rows Beyond Value = Max row range.
In AC Advanced, the data model may suggest worse rows from better sections that match your listing's relative value. I.E- If you have a 15-yard line seat in row 5, the data shows that rows 20-25 for 50-yard line seats would potentially have equal value.
If you have a premium row, up until a point if there’s scarcity you may want to try and maximize your value on the row. So you’d set the rows beyond your own to 5 and only take up to row 10 in those better sections.
5. Users can use these different filters to update results as they see best fit before saving. Users can also manually add/remove sections from the criteria.