The Hot Spot and the Algorithm – Mutually Exclusive?
Hot spots and the algorithm are important topics of discussion, among couriers. Tires, batteries and transmission fluid are not, unless someone’s tire is flat. In fact, it’s been awhile since the last time I had an in-depth conversation about transmission fluid.
I’ve had those conversations, but only when the transmission was broken.
Hotspots are a feature of the Doordash app. Not only are they useful, but they are also an excellent tool for scouting a rush.
For the courier just beginning deliveries, the hot spot is similar to a beacon. The closer the courier is to the beacon, the better. The beacon (hot spot) signals there are merchants with a rush in business.
The Hot Spot
Couriers that are close in proximity to the hot spot, will see an increase in offers, from that area. However, it is not always from the particular merchant, that is marked as the hotspot.
The screen shots are from the Doordash app, and show an example of zones and hot spots. Notice the difference in the intensity of the red coloring. The zones that are dark red are hot zones. Inside these zones, are the hot spots.
Obviously the darker color zone, is a busier zone, and should draw the courier, as a moth to the flame.
The Algorithm Cafe
The algorithm is a part of the delivery apps, therefore, it learns. Not only does it learn, it plays. Experienced couriers and drivers spend time learning the algorithm, and it, them.
For example, imagine the algorithm as a waiter at a nice dining cafe. This cafe has two tables, and the courier sits at one. The waiter brings a menu to the table, but it only has one item listed.
The courier can decide on that menu item, or pass it up for another item. If the courier passes, the waiter will bring another selection, but it will not be similar to the first. Or it will, it depends on the waiter’s sense of humor.
The waiter also notices things about the courier. For example, has the courier selected that item before, and if so, why not now? So, the waiter asks for a reason why, after the item is dismissed.
Similarly, if the courier has never selected that item before, but now has, the waiter will bring more items that are similar, in the future.
The idea is to tailor a good delivery experience for the courier. One that has the potential for positive earnings. The app works best when couriers accept deliveries, therefore, finding deliveries that a courier prefers, is a win win.
As far as mutually exclusive, they are not, in my experience and in my opinion. In the cafe example above, there are two tables, or zones. The waiter remembers which one the courier prefers, and what side of the table the courier sits on.
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