1
$\begingroup$

I wonder if anyone can help.

I have a set of data on event ticket sales. I have information on eventdate, location, capacity, cumulative sales, sales date, total sales.

I want to be able to build a model which takes a minimum input of The number of tickets currently sold and days until the event and it would return a value for predicted total tickets sold.

I think I need to use a time-series model or a Survival model, but I am unsure how structure my data and construct it in this instance.

Does anyone have any, tips/pointers/guidance?

Thanks

$\endgroup$
0
$\begingroup$

If you are aware of the capacity of the event, you could model the probability that the accumulated sale of the event will reach 100%. That is, sample the cumulative sale of tickets per event and choose the probability distribution that best characterizes the time random variable (exponential, gamma, weibull). I recommend you to read the following article: Forecasting Event Ticket Sales (Suher,2008)

I regret the lateness of my answer, but there are similar questions in the forum (search: ticket sales), however yours summarizes quite a lot the information that is generally available.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.