Unleashing the Power of Google Analytics 4 for B2B Companies
The only problem that agencies might face is the incompatibility between Google Analytics Universal and Google Analytics 4 and the reduced data retention period (in GA4, it’s only 14 months). It means you’ll have to reconfigure the analytics completely, but you can avoid setting up events, as most of them are recorded automatically. Event analytics helps trace the entire user journey more accurately: from the first entry to the site or app launch to the purchase. The data will merge at one touchpoint if a user performs events on different devices.
For example, the two events should be incorporated if they added a product to the cart on a smartphone and a PC. Machine learning and NLP features in Google Analytics 4 allow you to see significant traffic trends — anticipate customer churn and conversion likelihood and create audiences for Google Ads based on GA4 forecasts. Also, IP anonymization is set by default in GA4 (which is good as it helps comply with most privacy laws without additional tools). At the same time, this could be better for business as it significantly reduces data accuracy.
Continuing the topic and revealing the usefulness of Google Analytics 4 specifically for the B2B segment, let’s consider a typical case of cooperation between a digital agency and a company selling something online. The agency does not decipher the data for the client to explain the usefulness of the work done, and the client, in turn, does not deal with sessions, clicks, uniques, devices, and other unnecessary terms but sees real users, regardless of the specifics of the interaction between a potential buyer and a product (transition through the browser of a mobile device, mobile application, or PC). Also, without additional settings, you can track up to 500 unique events for each site with data updating in real-time (not once a day, as with GA Universal).
Another meaningful point is that the number of audiences for the resource has doubled, and data sampling will now be carried out on the side of BigQuery, minimizing the possibility of losing any information. Essentially, GA has become more straightforward, precise, and more usable for the average user, which should be a minus for digital agencies — if the client can see all the data and have automatic conversion processing, why do they need an agency?
“It’s not enough to just have a map; you need to know how to read it,” Andrii Zhurylo, the founder of Dijust Development, draws an analogy. “This applies to GA4 and GA Universal and earlier versions. Getting data does not even guarantee its correct understanding, letting only to use it. Over decades of work, we have enough experience to say that we know what to do with the data. And what’s more, when working with a client, we teach the client’s representative to work with data, sharing our experience. With GA 4, this will become even easier, as ML tips can help see an anomaly in the data, a simple request for this or that product, which will help respond promptly to the case.”
So, we state the inevitable. GA 4 is ousting GUA 3, and that’s a fact. It’ll become more accessible and more visual, but conditionally speaking, a car manufacturer is still better off focusing on car production and leaving data analysis, website promotion, application, or brand as a whole to the corresponding specialists.
