Account-Based Marketing (ABM) begins with grouping your leads and contacts at an account level, not at the individual level. Too often, I see sales and marketing organizations kick-start ABM by matching leads to contacts and accounts using domain information (i.e. email domain, website), otherwise referred to as domain-based matching. Unfortunately, this approach causes highly inaccurate matching and becomes a perpetual problem by incorrectly associating records.
At LeanData, we pride ourselves on our best-in-class matching. Having worked with clients of various sizes across multiple industries, we’ve encountered many in-house solutions that our products ultimately replaced due to low quality matching. Many of these in-house solutions could not scale, were difficult to maintain, or were unable to keep up with changing business processes. Spoiler alert: Our field tests have shown that LeanData matching is up to 190% better.
The most common implementation of domain matching compares the lead’s email and website domain against account website and contact email domains in your CRM database. At first glance, this seems like a great idea. However, this approach is completely unreliable for the following reasons:
False Positive Matches
- Bulk domain matches
- Matching any of the hundreds of bulk email domains (i.e. yahoo.com, gmail.com, rocketmail.com). This averages 11% – 15% of domain matches.
- Matched domain, different company
- Two records with the same non-bulk domain, but the companies are obviously completely different when looking at the record holistically (i.e. completely different company names). This averages 15% – 25% of domain matches.
- Incorrect inferred company
- Another incorrect match uses inferred company information proxied via IP address. Cable / internet operators are often the confirmed matches, resulting in Comcast, TWC, AT&T, and Verizon being your largest prospects.
False Negative Matches
- Mismatched domain, same company
- Without the ability to fuzzy match domain, the slightest discrepancy results in missed matches (up to 15% of misses from what we’ve seen). Most troubling is that this is often seen with large companies (i.e. us.ibm.com vs. ibm.com, 3m.com vs. mmm.com)
- Non-domain company information signals
- While domain matching seems “good enough”, what about target account leads who use their personal email? Best-in-class matching should leverage numerous factors such as company name, address, and phone, not simply domain. This typically represents more than 20% of your missed matches.
These bad matches cause numerous downstream problems:
- Leads are routed to the wrong sales rep, account manager, or account executive, and the lead is never followed up with
- Leads with gmail, yahoo, etc. from target accounts don’t get the right attention
- Leads that appeared good (matched target account “Verizon”) turn out to be consultants or students using Verizon internet services
We’ve seen that incorrectly matched and routed leads are as harmful as missed matches. Incorrect routing causes a follow up delay, and results in sales and marketing teams looking at the implementation with skepticism. This in turn leads to distrust and the desire to work outside of the very systems put in place to help these teams.
At LeanData, intuition isn’t good enough, which is why we worked with our customers to run head-to-head comparisons against their in-house match technology. In one case, LeanData showed 86% better matching, and in another case 192% better. We saw these results repeated across every customer who took the match comparison challenge.
If you utilize the domain-based approach and don’t think your implementation suffers from any of these issues, take a closer look. Once you do, ask yourself how much time is wasted trying to maintain your solution, and how much missed matches cost you in terms of mishandled leads and missed opportunities?
Request a Demo, and we’d be happy to show you what you’re missing, especially if you don’t currently utilize any matching. Challenge… accepted!