Customer Analytics tools such as Google Analytics (consider only GA4, UA is just traffic analytics tool), AT Internet or Adobe Analytics do not see beyond the horizon of a web or mobile app. What happens afterword they do not measure. Yet for many eComm industries that build on long term customer relationship or just more complex sales funnel, that part of customer behavior is critical.
It's clear to any marketing manager that the web transaction (order), considered by web analytics tools as the end of the purchase funnel and by marketing platforms as conversion, may not actually end up getting paid. The ratio between undelivered orders and total orders as called the "undeliverability rate". E-shops selling consumer goods, have large volume of conversions, and are not impacted by undeliverability rate, despite it might be between 3 and 15 percent. But what about banks, insurance companies, real estate, car dealers or telecom companies, where the sales cycle is much more complex and this undeliverability rate varies significantly depending on the type of campaign, target audience or product.
From leadoff to subsequent sale, the "undeliverability rate" for the above types of sales is often greater than 90%, and at this point it is no longer possible to treat such a loss as a negligible constant. Unlike in an e-commerce, where the marketing manager is also fully responsible for the final sale, the marketing team in a bank, for example, is only one of many teams in the entire sales process. For example, marketing is responsible for acquiring the potential customer (online lead) at the beginning of the process and the bank advisor who may be at the end is responsible for the final sale. But how can the marketing team improve the quality of the leads delivered if the sales team cannot provide qualified feedback?
The root cause is that the moment a lead is acquired, for example via a form, the data is passed to another system, and then to another system, and so on, and the resulting state is never fed back from those sales systems to the web analytics or marketing systems.
With systems that can distribute customer events on a server to server basis conversion data can be delivered to target systems in real time. The data can also be enriched, before being sent to the target system. While this may not be of great importance for GA4, it is crucial especially for marketing technologies like Facebook, Google Ads, Sklik or other DMP/CDP tools that work with customer identity.
Thanks to a server to server measurement tool mHub Cloud, the conversion data can be not only enriched but also validated and cleaned before sending. A server to server method of integrating marketing systems, it addresses a key deficiency in passing customer and other traffic data from the browser and the lack of downstream system integration. Replacing the failure of 3rd party cookies will once again enable marketing data and is a huge opportunity to drive the entire sales cycle through customer identity with significant impact on marketing effectiveness.
We would not like the above described possibilities to make it sound that such server integration will allow circumventing the rules of working with personal data. Just because something is possible does not mean it is right.