Modern business is impossible without the use of the Internet. It doesn’t matter if you sell or produce anything. Consumers need information, and the easiest way to get it is to search the network. In addition, the effectiveness of using various communication channels is not always amenable to study, but for the Internet it is quite simple to do. One of the most popular and visual methods is considered to be cohort analysis. Like other research methodologies for causation in consumer behavior, it requires the accumulation of statistical information. The Internet allows you to do this "invisibly" for the artist. Indeed, almost every action of the site visitor is recorded here - from the date of the first visit to the amount of time spent on each page.
Statistics at the service of marketers
It is unlikely that today there are still those specialists who interpret the word “marketing” as “advertising” and “sales”. Of course, these are two important components of marketing activities. But the basis nevertheless lies in the study of demand and consumer behavior. And then everything transforms into a search for opportunities to meet these needs.
And since it was a question of study and analysis, it means statistics to help us. Careful accumulation of a database of customer features allows you to thoroughly study demand and use the results of the analysis to the maximum advantage for yourself.
Most often, marketers use correlation and regression analysis; they are interested in descriptive and predictive methodologies for consumer research. All this requires the identification, for some signs, of the most significant (or interesting for business) customer groups. It is such a union that offers us cohort analysis.
Statistical Analysis and Commerce
In sales, it is necessary to clearly understand the causal relationship in the actions of customers. Cohort analysis allows us to do this by grouping consumers according to several criteria. Most often, a segment with a common characteristic (shopping, buying, etc.) stands out, combined by the date the event was completed. In statistics, it is customary to talk about a group of people (objects) that demonstrate similar behavior and signs. A simple example of a cohort is visitors who first went to the store a week before the New Year. Having studied their behavior, it is quite possible to draw conclusions about the effectiveness of advertising and commercial efforts.
Analytics
Google developers have long come to the aid of marketers. They offer many services for studying e-commerce statistics. You can now conduct cohort analysis in Google Analytics. Previously, it had to be done through forced segmentation of the audience. It was rather laborious and inconvenient. However, cohort analysis is now done automatically. The analyst can only configure the report parameters according to their requirements.
Report data is displayed in a timeline and table. In the settings, you can change four groups of parameters that cohort analysis uses.
The type of cohort is a common characteristic that unites a specific group of site visitors. Size can be grouped by time: exact day, week, month. If you select the "week" parameter, for example, the report will group all first-time visitors to the site for a given week into one cohort.
Then you can change the "indicator". Variability here concerns page browsing, session duration, number of users, etc. And the last parameter is “date range”. Thanks to this function, it becomes possible for the analyst to track the actions of the cohort during the time period from the established starting point to the current date. When choosing a grouping by day, remember that cohorts will be formed in rows, and dynamics of visitors' behavior in columns.
How to use analysis results
After examining the reports, you can track the frequency of consumer returns to the site. A comparison of quantitative indicators with the plan for placing content on the pages of the site will make it possible to understand what exactly interests and attracts customers.
For example, according to the analysis, a group of visitors stands out, which returns to the site with "enviable constancy." Having raised the plan for the placement of advertising materials on holding some kind of promotions or presenting new items in assortment at the time of the first visit by these clients of your pages, it is quite possible to draw conclusions about what attracted the attention of potential customers. This information allows you to increase the efficiency of the company. This is how cohort analysis is used in marketing. It makes it possible to distribute the advertising budget even more purposefully and efficiently and create effective communication channels.
What to look for
For the effective use of any statistical tools, it is necessary to carry out preparatory work. After all, a correctly posed question in a problem guarantees its quick solution.
What needs to be done before using cohort analysis? Ask yourself a few questions:
- Why is there such a dynamics in sales?
- How to choose a time period (for an advertising campaign, for example)?
- How to determine the time of distribution to get a great response?
The hypotheses put forward will help to more clearly determine the parameters of the cohort analysis.
Conclusion
Having familiarized with the capabilities of basic cohort analysis in Google Analytics and got an idea of its functional features, a marketer is quite capable of not only increasing website traffic, but also turning a potential client (casual visitor) into a consumer.
The formation of individual reports will give a visual representation of the features of the target audience, it will allow you to understand its reaction to your activity, regardless of whether you post an information article or a promotional offer on the site. Any marketing efforts should be economically justified. Cohort analysis, CLTV, Unit Economics - any methodology for studying consumer behavior is aimed at identifying the cost-benefit ratio and its optimization.
But do not go too far. Daily monitoring will give a misconception about the reasons for consumers to visit the company's website. It is long-term monitoring of representatives of one cohort that will allow us to track and correctly interpret changes in customer behavior.