Identify anonymous B2B website visitors

From anonymous tracking to real leads

It sounds banal at first: By no means all visitors to a B2B website exit from anonymity as part of their visit — be it via a contact request, a live chat or a newsletter subscription. If you compare the number of daily website visitors with the sales inquiries prompted by these visits, only a fraction go “online” — in most cases less than 1 percent. It is noticeable that those responsible in B2B marketing regularly shrug off this low conversion rate. They are satisfied with the finding that the flow of visitors consists largely of “personas” who are not relevant for B2B sales, such as end users who have “lost their way” while googling, students thirsty for knowledge, job seekers, competitors, partners — and last but not least employees of existing customers with whom they are already in contact.

However, the same marketing managers would also consider the following numbers game to be quite realistic — if not too careful —: Even if all visitors who are not relevant to sales together produce a whopping 90 percent of web traffic, out of 100 visitors there would still be 10 contacts from companies that visit the web presence of a B2B company with specific business interest. These 10 contacts presumably also contain one contact who — see above — “reveals” himself via request on average on a daily average. Conversely, this means that 9 contacts (or still 90 percent of the “real” potential) are lost as a sales opportunity — they disappear again in the anonymity of the Internet.

Sites or users? The change of perspective

Common web analysis tools such as Google Analytics, Etracker, Webtrekk or Adobe Analytics are conceptually not well prepared to tap into this remaining 90 percent of sales potential. This is primarily due to the fact that they all rely on page-related website analysis (“How many visitors were on which page for how long?”) are specialized. A visitor-specific view (“Which pages did a visitor visit when and how often?”) , which is necessary for a comprehensive assessment of the company-specific website “commitment,” they only make possible in cumbersome ways. A second shortcoming: The precise resolution of visitors' IP addresses is often not the focus of these tools for data protection reasons alone. This is because the IP address is regarded as an identification feature for natural persons whose storage and evaluation is subject to consent under data protection law. In addition, private individuals and small organizations usually go online via dynamic, daily changing IP addresses of their Internet service providers. Even with complete IP address storage, the tracking tool would only ever “see” the respective Internet service provider, not the consumer behind it.

From the IP address via the network domain to the company

For B2B companies, these data protection and identification problems do not arise — or at best in a significantly mitigated form. This is because many of the companies that are the target focus of B2B sales teams go online via their own IP dial-in addresses. This has two advantages for website tracking: Since they are not a natural person as an organization, they do not need their consent to process their IP address and to store the corresponding visit activities based on a balance of interests — provided that no cookies are set during tracking. Secondly, since the IP address is linked to the company, a so-called reverse DNS lookup can often be used to infer the company domain from this IP.

However, the conclusion from the IP address via the reverse domain to an organization with a unique company name and address is only possible after further reconciliation: If the reverse domain is found as homepage information in a company database such as Hoppenstedt, Bisnode, Dun & Bradstreet or Hoovers or in the company profile on LinkedIn or Xing, the complete company name including address data can be assigned to the originally anonymous website visitor. However, this enrichment has its drawbacks: For example, the reverse domain can be a “technical” company domain that refers to the (internal or external) IT service provider. Alternatively, the (sub) domain of a subsidiary, sister or parent company that provides Internet access centrally is displayed.

Which tracking provides the best results?

In order to avoid misallocations of IP and company data, providers employ “classic” website visitor recognition tools such as LeadForensics, SalesViewer and WiredMinds Matching teams. They manually check the matches between reverse domain and company database entry suggested by their software — and correct it if further information (e.g. the specific dial-in point or further referrer information) makes this appear plausible. This approach is economically attractive for software providers' customers. Because once an assignment has been made with a customer, all customers benefit from that point on. All customers share the high cost of manual initial verification (and finance it through monthly volume-based software fees).

In recent years, “classic” providers, who work with their own tracking scripts and chargeable company databases, have been facing new competition: tools such as Leadberry, Leadboxer, Leadfeeder and Snitcher obtain tracking data via the Google Analytics API — this saves the considerable effort of developing tracking in-house. They bring Google data into a view that is, as it were, turned from head to toe: As is usual with all B2B recognition tools, all pages visited are now displayed in a bundle for each visitor. The matching and data enrichment of the IP and domain information provided by Google is often automated via API queries against the company master data that companies maintain on their profile pages in business networks such as LinkedIn. This process saves money, making some of the GA-based tools some of the cheapest solutions on the market. However, due to their design, they have several disadvantages:

• They can only ever be as good at basic recognition as Google Analytics — and Google is by no means the standard in this regard.
• The Google Analytics-based tools access an anonymized data base, because Google generally sets the last three digits of the IP address, which is between 0 and 254, to 0. In terms of correct recognition of the reverse domain, this reduced data accuracy is a decisive shortcoming.
• In addition, automated matching is also very susceptible to errors, which has a negative effect on the number of leads identified.

That is why none of the providers working this way has in our tests Be sufficiently convincing. All of the web applications mentioned above are lagging behind the solutions with their own tracking snippet and manual matching.

Hidden potential

B2B tools for company identification present bundled website visitor information that was previously scattered in the depths of traditional analytics tools. Easier accessibility opens up new ways of generating leads for marketing and sales. How they handle the newly acquired knowledge in detail and what workflows look like depends heavily on preferences and the tool used. With the increased number of providers in this market and the continuous development of existing solutions, B2B company identification represents a promising tracking alternative. This will make it easier for marketers to identify sales-relevant target companies in the future and lose fewer website visitors to the anonymity of the Internet.

‍

Also read our Test of LeadForensics, SalesViewer and WiredMinds LeadLab tools and the Test the B2B website tracking of the Hubspot, Pardot and Marketo tools in comparison with SalesViewer

‍