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Hootie2012-06-18 17:22:17
Electronic commerce
Hootie, 2012-06-18 17:22:17

Average number of visitors to online stores by month?

Greetings,
perhaps the topic is poorly formulated, in general, the “average temperature in the hospital” is of interest in order to find out the “seasonality”.
Let's say in September to expect a powerful influx of customers, and in January to dry the crackers.
I would like to see graphs with the average number of visits per month.
Google/Yandex search did not give the desired results.
Thanks in advance.

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7 answer(s)
V
Victor Glembitsky, 2012-06-18
@Iforgot

1) Go to Yandex.Direct
2) Press the word selection
3) Drive in your region (if you don’t have the entire online store)
4) Drive in the target query (let’s take the “electronics store” in Russia in general) - here you need to think about what queries ask, to more accurately say the peaks, you need several queries
5) Click above "by months"
6) Assess your interest

A
Anatoly, 2012-06-18
@taliban

What product? I suspect an influx of conders in the summer, windows in the fall, and snowboards in the winter. Or do you sell everything? Then the flow will be constant plus minus some error =)

A
Artyom Tsyplakov, 2012-06-18
@grimich

www.google.com/trends/
www.google.com/insights/search/

S
skomoroh, 2012-06-18
@skomoroh

I can say from experience:
in electronics,
peaks in December, when all gifts are bought and state offices drain budgets for the year, and in September, when everyone buys devices drowned-lost over the summer
in children's goods
, peaks in May, when everyone is preparing for vacation and in August, when everyone is preparing for school, the
seasonal recessions are almost the same for everyone, there is a recession in January, almost at zero, well, in the summer they don’t order at all

V
Vyacheslav Golovanov, 2012-06-18
@SLY_G

For cosmetics last year (month - the ratio of sales in this month to the average for the year):
January 0.63
February 1.03
March 0.86
April 0.95
May 0.70
June 0.71
July 0.66
August 0, 92
September 0.97
October 1.23
November 1.30
December 2.02

M
Mikhail Lyalin, 2012-06-18
@mr_jok

highly dependent on the range of goods

R
Ruslan Fatkhutdinov, 2012-06-18
@Phelix

wordstat.yandex.ru
Regions, seasonality, queries, etc.

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