For B2B companies in the digital sector, lead generation is often a crucial phase in customer acquisition. Especially in the process between the user’s first attention for their advertising measures and the transmission of the contact forms, one loses a lot of potential customers and orders. This article describes how web analytics can help with these hurdles.
Many people know it: You are looking for a specific topic or problem and you get a suitable and appealing advertisement. After clicking on the ad, you will be redirected to the target URL and in many cases landed on a detail page or landing page. However, many (especially B2B) websites are simply not set up well enough there, so that as a user you have a bad website experience and, on the other hand, the company hardly receives any inquiries from users. The similarities between the user’s needs and the company’s offer are too few and so the user leaves the website.
Lead generation often fails because of smaller things. Starting with the user experience, which is becoming more and more essential, to individual form fields that can be named as an attribute or call to action. Also, there are other competitors who in many cases offer the same advantages and use similar advertising measures.
To focus on the target group and at the same time stand out from the competition, you need information and data on the effectiveness of the respective lead generation measures.
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In many cases, you get all the lead’s entered data sent with the form submission, but you can usually capture a lot more valuable information automatically. On the one hand, a professional tracking setup and comprehensive, uniform data (same lead IDs, etc.) help.
A great advantage arises when you build different tools marketing automation, web analysis, CRM) with the same lead data. Of course, the applicable data protection must be taken into account. As soon as you have decided on an overarching data structure, you can transfer this uniformly for all tracking codes, for example using tag management tools.
Furthermore, you can record the entire path of the user and the individual touchpoints with a tracking setup and use them for analyzes and remarketing measures (addressing interested parties again). To be able to record this data, you need:
As soon as the setup of the tracking, including the lead track, has been completed, all important data about lead generation and touchpoints, as well as user actions, can now be evaluated in a user-friendly and automated manner.
If you get information about possible optimization and advertising measures in online marketing, you get concrete recommendations for action and a long pro list of why you should use these measures. As a rule, however, only 20% of all measures bring the greatest benefit and many are too cost-intensive. Often, different channels are also better suited to supporting the customer journey than leading the user directly to the conclusion.
The good thing about these measures is that you can measure and evaluate them. All you need is a web analytics tool such as Google Analytics and an individual setup that corresponds to the goals and requirements of the data. To be able to measure the success of the traffic channels and campaigns, the following things must be considered:
However, you should allow yourself some time for this process and work your way into this topic. Before starting the implementation, the tracking and the setup should be set up correctly and, above all, sustainably to avoid wrong decisions.
Many implementations and adjustments of landing pages, detail pages, and forms are based on hypotheses and often there is still no real success after a while. In this case, web analysis can be used to analyze user behavior more precisely and understand the actions. Why do users jump off after calling up the landing page? Does the content of the website match the advertising measures and the promised initial information? Which elements does the user interact with and how far does he move on the page?
Furthermore, you can incorporate specific measures that anonymously record user behavior to see exactly how the user behaves on the respective page and where he breaks off. Another advantage is that the forms can be evaluated in detail. Which form fields are used and which are skipped?
On average, it can be assumed that the abandonment rate of form usage performs field increases by 20%. Thus, one is faced with the challenge of conveying a lot of information about the lead on the one hand and wanting to cause as few abortions as possible on the part of the user at the same time. Ideally, the most effective component of the form can be found through web analysis data and automated tests. This is possible by identifying unused and breaking form fields through the analysis and leaving them out in the first generation of the lead to increase the conversion rate.
In addition to the forms, there are also many other touchpoints and ways in which the user is guided from the interested party to the conclusion. Among other things, when analyzing the customer journey, one should concentrate on the phase in which the user is and with which advertising material he is being addressed there. It is often crucial that the content of the advertising material and landing pages match the user’s intention and that he can find the relevant information on the website that was suggested to him in the advertising material. Also, you should check the user’s path on the website more closely and further open the doors for successful contact through appropriate measures.
Professional web analysis can be very helpful in lead generation by providing the right information. And by highlighting the measures you can take to best address your target group in which phase of the acquisition, at which location, and at what time, to achieve the desired deals for the website or app. And above all, because it provides valuable data for optimization and user behavior.
Ultimately, only small screws often have to be moved to achieve significantly more effectiveness in lead generation. Web analysis and conversion rate optimization help here.