This issue seems to be raised in some form or another quite often, but I’m not sure my particular solution has been proposed, so first, the problem:
Currently “limit orders in queue” only serves to remove gigs from search results, which is both badly communicated, and detrimental to sales overall. Badly communicated, because a) there is no actual limit, buyers are still free to submit orders if they manage to find the gig* and b) the gig is actually just not being properly advertised during that time, which leads into the second issue; sales are being negatively impacted. This negative impact is simple enough to imagine, but if a buyer would have ordered a gig from me - even if there was a wait-time associated with some functional queue - they will instead abandon the search, settle for a similar service, or find the gig another way, and we’re back to problem a.
*I advertise my Fiverr gig on Instagram and Reddit, which means that it is trivial for buyers to find it, regardless of the so-called “limit” that I set.
And now, the solution. I have two, one being more costly to implement, but far more functional:
Orders simply cannot be placed on a gig that has reached its queue limit (this is less preferable, but would likely be cheap to implement)
When a buyer attempts to order a gig that has reached its limit, they are notified that this is the case and that their order is now pending. The seller is not made aware of this order, and the buyer can cancel their pending order at any time before it enters the seller’s queue. Upon an existing order in the seller’s queue being completed or canceled, the pending order with the highest priority (the one with the earliest date) will be immediately added to it.
This second solution is exactly what I assumed was the case when I read that I could set a queue limit. The existing functionality is poorly communicated and largely detrimental. Not only is the second solution more intuitive, but it will dampen the negative effect on sales - especially in cases where orders are not extremely time-sensitive.
Thank you for coming to my Ted talk.