chore: Analytics. Question 2

[GabyGO2108]

Summary 💡

Answer the assigned question including data analysis.

Acceptance Criteria

• [x] What is our traffic telling us?

[GabyGO2108]

So, we already know that people that buy in this e-commerce tend to make purchases on workdays and on work hours, but what does the data says about the traffic? Well, here we have to clear that our datasets don't really have the amount of clicks or website visits our e-commerce had, so we're gonna have to come with a different angle to answer this one. So, let's take a look to the graph below.

As seen, data ranges from September of 2016 up to August of 2018, and we can also see the number of orders per month which is what can help us answer what the traffic tells us. Let's get down to it.

As we can see, 2016 was the year with the least amount of orders, and probably the least amount of visits; however it's not rare since we can assume that the business was jus beginning. In 2017, the e-commerce placed above 1000 orders, except for January. We can also appreciate that the number of orders increased in the following months, reaching its peak in November of 2017. Let's sum up what he have: so far orders range from 2000 to 6000 per month, which at least tells us that the traffic is somewhat constant, and that the buying habits of the people that buy here don't vary much. And here is our second most interesting insight: the peak of orders, as stated above, is November and not December; so what happened in November of 2017. Let's take a look.

Well, as seen the above graph, is not as if this particular month exceeded every day in revenue or orders, rather it was a specific date that provoked the peak. And what was that date? Turns out that November has the infamous Black Friday sale, and it just so happened to coincide happily in this case.

Bringing it all together we can derive three main observations from the given information:

1. It seems that buying habits are pretty much the same and remain the same.
2. Contrary to our first thoughts, it's not the holidays that draw the most buyers, but the Black Friday Sale. Probably because product give aways and promotions are better; would be interesting to find out.
3. It would be interesting to have the information regarding posts and social media interaction, since it is not clear if the amount of sales are impacted by this or not. For example, it catches our eye that March of 2018 recorded more orders than February. We considered things like the Carnaval and other festivities, however these are not famous for giving or exchanging gifts, whereas in February we have the 14th.

[larispardo]

Maybe I missed this, but why do we know the e commerce has more traffic on weekdays? Wonder if we could see some seasonality if we reduced the impact the natural growth of the company is having 🤔 As an interesting insight there, this about Black Friday became such a thing that companies like radio stations and tv stations have their best revenue months due to publicity in November since 2015, so companies also try to get as much adds out there in November as in December.

[GabyGO2108]

Hi, well in the past question it was determined that people buy more on weekdays than on weekends, however we speculate about traffic based on the data we have because the data dose not present clear traffic indicators (number of clicks, visits to the webpage, etc.).

As for the second question I really don't know how to reduce the impact of the natural growth, and I don't quiet understand what the suggestion is. I will ask the team, but if you could elaborate a bit more, that'll be awesome.