After data collection and subsequent processing and transformation, the cleaned data is waiting in one of the tools and awaits analysis. We then help our clients with any data analysis and evaluation.
Data analysis options
We usually work on a combination of basic one-time audits, regular monitoring and in some cases large-scale and advanced solutions.
- Site Speed Analysis
- Shopping Cart Analysis
- Data UX analysis of a given page or part of the website
- Customer Analytics (who orders once and who orders multiple times, what are the order sizes) – possible customer definition that can then be worked with according to internal anonymous IDs in marketing channels
- Customer segmentation
- Google Analytics errors (comparison of server log and Google Analytics)
In addition to the analyses above, we also provide tailored outputs to meet your needs. Together we can define the data to be collected, then clean it and work with it according to what you need for internal analytics or work with marketing tools.
Our in-depth knowledge of web analytics and marketing experience can help you create an entire plan from data collection to final business decisions.
What are data analyses usually used for?
The most frequent analyses from our architectural workroom concern:
- evaluation of campaigns,
- financial marketing planning,
- evaluation of web editing,
- identifying content gaps and web usability limitations
Such outputs then lead to an improved user experience with the website (UX improvement) or an increase in the conversion rate of the website.
We like to identify areas for improvement that we can work on with the client and try to shorten and optimize the customer journey, i.e. remove as many obstacles as possible. If a client needs help clarifying confusion about web analytics or its nooks and crannies, we’re here to help.
Standard of our solution
We try to keep a certain standard for each client so that the analyses are comparable over time. At the same time, the analyses evolve technologically and keep up with the times (although the combination of these two criteria is sometimes a challenge).
Depending on the type of tool and the expected results, the level of automation that can be used varies.
Safety limits and requirements
Working with customer data requires maximum security. That’s why we work in Google Cloud, which offers countless security certificates.
We also urge clients to use anonymous IDs instead of email addresses and real user data. For example, Shoptet does not support this anonymous ID solution – we usually convert emails to anonymous user IDs ourselves.
Advanced data manipulation with post-analysis – when Excel or basic Analytics reports are not enough for you.
Server log analysis
From technical error detection to comparative audits with Google Analytics, server logs can provide valuable data.