Google Ads agency
You already have advertising campaigns, but you want to get the most out of them? We will conduct an audit and give a guarantee! We work according to the payment model for KPI project. We set up and maintain Google Ads, make reports, help improve the site.
What do we suggest?
Conducting audit of advertising campaigns, site and analytics systems, looking for growth points.
Watch a full audit of the services sector.
The name of the client is not specified, as the work is carried out under the NDA.
We investigate the payback in the context of advertising campaigns, keywords, devices and other parameters, pointing to obvious deviations.
Investigate competitors for prices, site content, where the traffic comes from, and so on.
The screenshot shows a strong degree of traffic intersection in user paths before purchase, when standard Google Analytics reports are incorrect and you need to do a custom attribute model (channel conversion model).
Based on the audit, we develop a payment model for KPI and a forecast of changes in KPI.
The agency's remuneration changes on the screen depending on the number and value of leads received per month.
We are preparing a media plan to change the project's targets taking into account our participation, seasonality, market size and other factors.
We collect all data into Google Analytics or ROIStat and build online reports.
All data is collected in Google Analytics, integrated with the CRM-system.
We make complex reports for ourselves and simple reports for you to «keep an eye on the pulse».
We agree on a map of search coverage and launch campaigns.
To be clear about which search queries should and should not be advertised, we make a coverage map that we agree with you.
Learn more about the process of client and agency integration.
You can see in real time how the tasks, deadlines and status in the Asana.com task system are progressing
This is the most complicated process in advertising campaigns, we will give you a couple of examples with pizza and prices. You can order this service separately.
In the pizza delivery project, conversion depended on the temperature outside the window, so we wrote a script that increased coverage in bad weather and vice versa.
In most online stores, 80% of revenue comes from products that are priced below the market average, so we take this into account when calculating rates, but the mechanism is more complicated than with pizza.