How we reduced the number of false leads for the client E.ON?

How to approach setting up advertising systems so that the leads are high-quality and the conversion rate into contracts or sales increases? We effectively solved this problem for our client E.ON, whose business relies on the submission of a contact form on a target URL page, and who are among the Czech leaders in supplying energy, solar panels, and heat pumps. In this article, we will focus on how to reduce the number of generated false leads and what steps to implement to improve the current situation.

Main problems caused by false leads

• Increased cost per lead:

  False leads increase the actual CPL (Cost per Lead) and lead to inefficient use of the marketing budget.

• Loss of time and efficiency:

  The client’s sales team must handle every lead, which results in decreased productivity and team morale.

• Distorted data:

  Campaigns are optimized based on incorrect and lower-quality data, which again leads to poor results.

Strategic approach to reducing the number of false leads and lowering the cost per converted lead

Definition of false leads The first and crucial step is to correctly define a false lead. Based on data from our campaigns and in cooperation with the client, we identified the following types of leads that were considered "false":

• Customers who were unaware of the submitted lead or were children.

• Users who filled out the form for a different purpose (e.g., job seeking).

• Non-existent or incorrect contact details.

Optimization and analysis of collection forms:

• Adjusting individual form fields to achieve the ideal balance between ease of completion and accuracy.

• Adding security features (reCaptcha).

• Implementing a tool for monitoring website flow for further evaluation (e.g., Smartlook, Hotjar, Microsoft Clarity).

Adjustments in advertising systems and campaigns:

• Tightening the exclusion of pages where the ad was displayed (for example, excluding all URLs containing the endings "au," "ru," "biz").

• Excluding targeting of mobile applications.

• Excluding job portals from placements and other visually or content-wise inappropriate websites.

• Limiting geo-targeting campaigns from "Current location + Interests" to only "Current location" (not recommended according to Google best practices).

• Checking the display of RDA ads to ensure that the product or service offered is clearly recognizable from the headline, description, and image (while trying to follow Google’s recommendations, such as not using headlines longer than 25 characters even though the maximum range is 30 characters).

Offline conversion import:

• Linking data from CRM with advertising systems so that information on closed leads is uploaded retrospectively. This step ensures higher quality campaign optimization through smart bidding.

• Evaluating the resulting CRM data and not relying solely on data from Google Analytics and other tools.

Result Thanks to the implementation of these measures, we achieved a significant reduction in fake leads for E.ON. The rate of low-quality leads dropped from 70-90% to a stable value between 6-9%. This not only improved the quality of leads but also reduced costs and increased the productivity of the team working with these leads.

Key recommendation For companies using PPC campaigns to collect leads, we recommend:

• Carefully defining what constitutes a quality lead and focusing on its verification from the initial stages.

• Investing in UX/UI, as websites have a significant impact on the overall result.

• Regularly analyzing and adjusting ad targeting, especially in the content network.

• Implementing tools for offline conversion import and linking CRM data into advertising systems and reporting.

With these steps, we can dramatically increase the efficiency of PPC campaigns and the sales team by ensuring a higher quality of generated leads.