ere, Yandex.Metrica services (let’s take it as an example) or Google Analytics (albeit with some nuances, but the sequence of actions is the same) will help us.
Dmitry Pronin
To determine the basic non-branded denmark whatsapp data traffic, you need to create a new report in Yandex.Metrica: Reports => My reports => New report.
We will see a report on all current traffic sources (if there is one on the site at all). Next, you need to cut off all traffic except non-branded search traffic for the required region/regions (the SEO specialist will focus on this). We remove:
- brand phrases;
- other regions;
- other PS channels and services.
To do this, we form several rules in the report, according to which we configure the display of the segment. We work in the “Visits in which” tab:
1. We cut off transitions from other sources:
Visits where => Sources => Source Type => Enable => Search Engine Referrals => Apply.
2. Visits where => Sources => Search engine => Exclude => Yandex:
- Yandex.News;
- Yandex.Work;
- Yandex.Market;
- Yandex.Real Estate.
3. Visits in which => Geography => Location => select the calculation region:
4. Visits in which => Sources => Last source => Search phrase => All conditions => we write brand words in asterisks, before each word we put an exclamation mark. Basic Unbranded Traffic.
Let’s consider omnichannel strategy: a new consumer experience this process using the example of the Didmarko online store . From the list of queries, you need to cut off branded ones:
- !*didmarko* — we cut off all requests that contain “didmarko”: didmarko ru, didmarko.ru, didmarko company , etc.
- !*did*marco* — we cut off everything before “did”, everything between “did” and “marco”, and everything after “marco”: did-marco, did marco internet , etc.
Determining the seasonality coefficient for the site’s target areas
Determining seasonality will help when adjusting base traffic and forecasting growth.
To determine seasonality, we use the mask selection method (in Yandex.Wordstat).
[INFO] A mask request is the main request in a cluster, which contains the entire list of loop requests.[/INFO]
The mask is suitable for the site lack data if both the mask itself and all queries from the trail can be taken for promotion by traffic. For example, Basic Unbranded Traffic for the page the mask “buy a refrigerator” is not suitable, since its trail includes requests like “buy a used refrigerator “ or “buy an Atlant refrigerator”:
If the site does not offer refrigerators of a certain color, brand, model, etc., we adjust the demand by excluding the corresponding words. In a similar way, we collect masks for all the main sections of the site.
Then it is necessary to collect the demand for each mask for previous months (also via Yandex.Wordstat):
This is how you need to do it with each mask and sum up the demand for all masks for each month.
By calculating the average demand for masks for the year and dividing the demand of each month by the average, you can obtain the seasonal demand coefficient.