Why Your Current De-anonymization Solution Isn’t Working
When COVID-19 forced a new work-at-home paradigm, many assumed – or perhaps wished – that the interruption to our daily routines would only last for a few weeks. But we now find ourselves six months into our “new normal”. With many workers faced with the continuation of work-from-home policies for the foreseeable future, the importance and value of digital engagement continues to increase. And while quantity of engagement is easy – for many, time spent online has increased dramatically –at Dun & Bradstreet, we have always believed that it’s the quality of the engagement that counts.
Understanding your customers and prospects is a requirement for any successful B2B marketing strategy, and it’s especially important as part of an account based marketing strategy. In ABM, accurately targeting and identifying digital visitors is what drives success in every aspect of your efforts. It’s an integral part of an omnichannel marketing strategy that can turn your strategy from a base hit to a grand slam.
But quality digital engagements aren’t necessarily easy to come by. Just think about how many times you have stared at a blank screen with the entire internet at your fingertips, but no real desire to engage with anything. Sure, traffic volumes are up everywhere you look, but how can you be sure the extensive resources being devoted to outreach, support, and customer success are translating into increased quality of engagement and, ideally, sales?
The value of good, accurate data has only become more apparent with each passing month of the COVID-19 pandemic. As more activity has continued to migrate online, we have found ourselves having different facets of this discussion with our partners, and even amongst ourselves.
Know Your Audience
One of the foundational pieces to even being able to take a stab at answering the question posed above starts with online account de-anonymization to identify what business visitors are engaging with your site. You need a confident understanding of who your visitors are before you can begin to target them across digital channels, confirm successful outreach efforts, and attribute downstream activity to your initial ABM strategy. Personalizing the website to highlight content of interest? Enriching your web analytics to allow for better journey analytics? Refining audience segments in your DMP? None of this is possible without a confident understanding of who is on the other side of the screen.
At Dun & Bradstreet we see two underlying methodologies that can help identify targets for your B2B ABM strategy while remaining sensitive to privacy considerations: IP address lookup and cookie matching. Each has its strengths and weaknesses. We’ve found that’s it actually a combination of the two that brings the best results and is most resilient to changes in user behavior. This is especially important today with the changes we’ve experienced, such as widespread work-from-home.
IP Address Lookup
IP address lookup is simple in theory: for any given IP address, there are a variety of sources, both public and private, that provide signals as to ownership and usage. IP assignments are not static, however: they shift over time and the frequency of those changes has been increasing. While it used to be a safe assumption that most medium and large companies held static leases for pre-defined blocks of IP addresses and it was mostly residential customers who were subject to dynamic IP addresses, the combination of increased SD-WAN adoption and VPN usage has brought corporate IP addressing closer to the residential model of unpredictable change. Dun & Bradstreet’s interest lies in identifying corporate IP addresses that can be converted to leads for ABM in the B2B space.
Cookies are different in nature but subject to similar trends: while in theory they can precisely identify an individual and retain that information indefinitely, they’re fuzzier and less resilient in the long term. This has culminated in the announced sunsetting of third-party cookie support by Chrome, which is the functional equivalent to their discontinuation across the industry.
An Imperfect Science
Some common ways that de-anonymization of website visitor information for B2B ABM business purposes can return faulty matches include:
- Matches that we refer to as “network intermediaries”: ISPs, cloud providers, hosting companies, SD-WANs, and any other sources of website traffic that don’t truly represent the day-to-day usage of a specific IP address
- Retaining matches despite shifts in user location, whether due to normal network management practices or the current shift to working from home
- Conveying the appropriate level of confidence in the match and, on the other hand, avoiding the natural tendency to (over) emphasize larger and more recognizable companies by virtue of their prominence
- Navigating the family tree for larger organizations to arrive at the most precise and appropriate result rather than rolling everything up to the worldwide headquarters
All of these problems can skew the incoming data, and as the first stage to any ABM campaign, that unwanted noise can lead to incorrect targeting, inefficient spend, and poorer outcomes. Sure, there may be a lot of traffic from Amazon, Google, Facebook, and other well-known technology companies, but what proportion of that is actually employee traffic rather than ad verification bots or cloud customers? Likewise, most Verizon traffic is from their extensive residential and mobile footprint, but what about their media and digital divisions?
Filtering Out the Noise
Parsing these issues in a way that drives true ABM success – differentiating the signal from the noise – is at the core of Dun & Bradstreet’s Visitor Intelligence offerings. An accurate understanding of business website visitors, their business-based identity, and their behavior leads to better segmentation and targeting, which is the first decision point of many ABM tactics and one made all the more important due to the work-from-home situation.
With Dun & Bradstreet’s recent acquisition of Orb Intelligence and MadObjective, we are better positioned to increase overall de-anonymization rates for B2B ABM and refine our classification models for the many possible sources of erroneous matches. The initial results have been promising. Despite our concurrent attempts to expand our ISP classification efforts to include as many new entries as possible, we still saw a rise in our resolution rates across the board. As a happy side effect, the large shift in internet traffic due to the pandemic has also improved our understanding of ISP and corporate networks while our extensive cookie coverage has blunted much if not all of the downside.
Digital Transformation Continues
Business is constantly evolving, and what we’re experiencing is a layering of shifting work environments onto an already fast-paced digital transformation. Acknowledging that this trend is occurring is half the battle. Fortunately, we have the insights and tools to help you continue to foster strong connections with prospects and customers no matter how they choose to engage as they adapt.
Nan Zhang is a Product Director at Dun & Bradstreet overseeing Visitor Intelligence and IP matching. His background is in digital marketing and advertising, including paid search, programmatic display, user deanonymization, and attribution. Thorny data problems are his favorite type of problem.