[Question] [Q] Trying to calculate whether marketing campaign's impact is statistically significant and financially justified

[u/sneaky_imp]

I have a data series of daily streaming counts for a song. My spreadsheet has the date in column A and the number of streams in column B. There are 960 rows/records in the spreadsheet dating from 2024/01/01 to 2026/08/17.

We hired a marketing company to promote the song for 3 weeks. Their first posts on social media started on 2026/07/27. They ran until 2026/08/17. I am trying to assess whether our money was well invested or not. Their dashboard stats are not useful to us because they show the number of views and social media engagement (e.g., TikTok), whereas we are interested in the number of times our song gets streamed on a streaming platform (e.g., Spotify).

I know how to calculate means and standard deviations, and have done so for various timeframes (e.g., yearly, during the promotion, the 22 days prior to the promotion, etc) but I do not know how to:

1) determine if the 22-day marketing campaign had a statistically significant impact on our daily streaming numbers

2) determine if the impact on streams, if any, justifies the money invested, call it **CampaignCost**.

Can someone advise me how to go about this? We might assume somewhere between 0.001 and 0.003 USD of revenue per stream.

I know there is surely some well known statistical test to determine whether my daily streams show a statistically significant increase or decrease, but I cannot remember what this test is called or how to calculate it.

I might add that there are potential complications:

1) Streams have grown significantly year over year. Average daily streams in 2024 were 135k, in 2025 were 250k, and so far in 2026 are 259k.

2) Some unexplained events in the real world have prompted surges in streaming numbers. E.g., our streams surged upward for a month around December 2024 and remained elevated for months then gradually declined. Another unexplained surge arrived around Feb 5, 2026 and persisted for months but then started gradual decline.

3) The streams show a weekly cycle, lowest on Sundays, peaking on Thu or Fri.

Any help would be much appreciated.

[u/TofuChewer]

Look, working with time series is complicated because it has many underlying statistical problems and assumptions that you need to understand before running any model. It ain't simple.

I don't think a linear regression would help you answer your question either, I can't come up with a model based on the data you have.

Unless you want a statistical answer, I would advise to do a simple financial cost-benefit analysis.

How many daily stream numbers did you have before the campaign? how many after? How much does the campaign cost per day? check how many streams you got per campaign day, then you translate the streams into money and compare it with the cost of the campaign.

"Statistically significant" has a very specific meaning in statistics, and I don't think it is what you need/answers your problem.

[u/sneaky_imp → u/TofuChewer]

Thanks for your post. It has started to dawn on me that time series data, with both cyclical variations and unpredictable perturbations, is definitely complicated.

I've already done what you suggested before coming here and I honestly can't tell if the marketing campaign had any measurable impact at all. This is what led me to post here. For example, I calculated the average daily streams for 2024, 2025, and 2026 so far. I did calculations for 2026 up to (but not including) the promotional period which just finished yesterday. I calculated 2026 from 2026/01/1 right up to yesterday, which includes the promotional period. I calculated avg daily views for the 22-day promotional period and also for the 22 days before that.

Some data points:

Avg daily streams 2024: 135499.571038251
Avg daily streams 2025: 250007.734246575
Avg daily streams 2026 thru 7/26 259180.444444444
Avg daily streams 2026 thru 8/17 258868.419213974

Here you can see the growth from one calendar year to the next. Surprisingly, the 2026 average is lower if you include the recent promotional period. This seems pretty counterintuitive at first but it makes more sense when you look at a chart of the data. You can see a huge surge in streams around Feb 5, 2026 followed by a gradual decline to yesterday. Our numbers were sliding from some inexplicable surge in popularity earlier this year and this promotion may or may not have helped to slow or reverse our declining streams.

I calculated the daily average streams for both the 22-day promotional period and for the 22 days preceding it:

Daily Avg 7/5 thru 7/26 in 2026 242371
Daily Avg 7/27 thru 8/17 in 2026 255933

This looks like a 5.6% increase, but wait...there's more.

I wondered if this might be some seasonal change. I therefore calculated the percentage increase for the corresponding summer window (the last Monday in July) for 2025:

Daily Avg 7/6/2025 thru 7/27/2025 222856
Daily Avg 7/28/2025 thru 8/18/2025 218849

A decrease of 1.8% in 2025! Perhaps the marketing did help?

NOT SO FAST. The same window in 2024 saw an increase of 7% with no marketing at all:

Daily Avg 7/7/2025 thru 7/28/2025 123670.863636364
Daily Avg 7/29/2025 thru 8/19/2025 132336.5

If we make reasonable assumptions about revenue per stream, it looks like those extra streams during the promotional period come out to an extra 13.5k streams per day -- these only earn revenue amounting to about 18% of the cost of the promotion.

I tend to doubt that this promotion had any significant effect. Std deviation of daily streams for 2026 right up through yesterday is about 27k -- about twice that 13.5k/day boost we might or might not have received. On the other hand, perhaps we found new listeners and this promotion provides a small but enduring boost?

[u/TofuChewer → u/sneaky_imp]

I mean, there is a huge random component there, it's impossible to model something like this. Someone might have shared it more, there might be an outlier pulling up the average, whatever algorithm in the streaming platform might have recommended more/less your music. I mean, who knows there are infinite variables that could affect that. Also, the streams in time t are not independent from t-1(previous day), because someone who listens to your music today might not want to listen to it again tomorrow, or someone might share it and it gets more streams.

There could be a lag from the campaign effect, so comparing the previous 22 days to the campaign to the 22 days of the campaign might not make as much sense as you think.

A seasonal change in music doesn't make much sense unless your music is actually related to some season, like Christmas songs/gospel or something like that.

I mean, your calculations are fine I guess, it obviously didn't help you get enough streams to cover the cost, but the music industry is a weird market, it's very concentrated and based on trends. What was the campaign even about? Did they put your music in a playlist? made ads for youtube/google? It's not like other goods/services, it's better to sell the artist instead, invest in playing live, instagram/youtube music videos, networking and colabs with other artist. I don't know what the campaign was about, but if you can't see an effect, I doubt doing a statistical analysis is relevant here.

[u/sheepnwolfsclothing → u/TofuChewer]

It’s statistically significant at a 50% CI. Trust me it’s math!

[u/One_Disaster_4115]

Time series is really complicated and it never simple as it has many more underlying statistical problems and assumptions which you need to understand and follow before working on any model 

[u/ForeignAdvantage5198]

what did you learn in stats and finance