Updated on August 28, 2023.
Have you ever had a prospect respond to your cold call or outreach email with, “I’m already in touch with person X from your org”?
Or worse, “I’m a customer who’s still looking for that custom drop I requested, can we focus on that first?” These are situations that can be entirely avoided with an iron-clad lead-to-account matching system.
For inbound, lead-to-account matching becomes a direct pipeline requirement. Without it, you’d end up having different decision makers from the same organization engage with your sales teams and account executives individually, in a broken, disconnected manner. In short, a colossal misallocation of resources and processes ensues.
What is lead-to-account matching?
Lead-to-account matching or named account matching is the process of mapping your inbound and outbound leads to the account or company they’re a part of. If not manually, it is done using fuzzy logic algorithms that take into account factors such as email address, domain name, IP addresses, and geography. The purpose of lead-to-account matching is to avoid redundancies in lead recognition and optimizing your pipeline for bottomline relevance.
Implementing lead-to-account matching ensures that leads from a company are mapped to the right AE, who carries maximum context about the company and what the leaders are trying to solve.
While this can be done manually, it can cause a lot of inefficiencies to your GTM motion and affect workflows across the funnel.
Second order effects of a poor lead-to-account matching system
Without a system that matches leads to their respective accounts and routes them to the right AE, your pipeline quality and management processes can get taken for a ride. Understanding what happens to your GTM without it will give us a better picture of the importance of lead-to-account matching.
- Spammy customer experience: Multiple BDRs and AEs contact the same leads multiple times, leaving a bad impression on the impending deal.
- Efficiency of your sales team: Different reps handle different leads from the same account without any cross-functional context or the variation in solution-awareness of the leads.
- Manual pile ups: Your sales and marketing functions go through a tedious point-solution chaos, as lead-to-account matching is done manually by looking up data from too many tools. The health of your CRM data can have harmful implications on poor lead-to-account matching and vice versa. Manual lead-to-account matching is an obsolete practice that can spell doom to your products growth and scaling aspirations.
- Marketing-to-sales handover: Without knowing the marketing resource, collateral, or campaign that piqued your prospect’s interest for a sign up, your sales folks can end up flying blind even while interacting with new leads from an existing account. This can especially spell doom to your ABM campaigns, where data is paramount for continued success and experimentation.
- Boardroom interventions: The most dreaded one of them all! Let’s face it, identifying pipeline problems and taking them to your quarterly check-ins with C-level execs isn’t going to cut it. Everyone’s grown so tired of the mudslinging between sales and marketing that it’s no longer an escape hatch you can trust. The sooner you realize that lead-to-account matching is a cross-functional problem that affects productivity, impact, and lead quality across the board, the better.
Automating your lead-to-account matching
Consider a demo request form across your website and ad landing pages. A Marketing VP, CEO, Sales Lead, and a few AEs of one company have individually booked a demo of your software – some organically, some through paid search ads, and a few from a LinkedIn campaign.
Now, these contacts may be in different stages of maturity such as evaluating, passive, interested, or awaiting quote.
With an automated lead-to-account matching system, you will be able to map the leads to the company, identify the medium (campaign, organic, etc.) that brought them in, and assign it to the AE who’s already handling this account.
Also read:
How does automated lead-to-account matching work?
Automated lead-to-account matching primarily maps leads to their respective account using fuzzy logic algorithms. Fuzzy logic is based on the human tendency to find patterns from a large volume of similar or dissimilar information.
When you get an inbound lead, your lead-to-account matching tool must match it against your CRM to check if they belong to an existing account. A basic matching rule would not be sufficient here, because the text may contain special characters, misspellings, nicknames, or varied company suffixes.
This is where fuzzy matching fills in the gap.
The fuzzy matching offered by your lead-to-account matching tool should ideally work on a wide range of identifiers or parameters such as:
- Email address
- Domain name
- IP address
- Acronyms
- Variations of company names
- Suffixes like stock codes
- Industry
- Geography
- Nicknames
- Syllables and regional spellings.
Examples of scenarios where fuzzy matching kicks in
Multiple company names
You’re getting a steady inflow of leads from an enterprise account. But the naming issue with large companies is that they can be represented differently with acronyms, corporations, stock market suffixes, and whatnot.
But with fuzzy matching, you can automatically identify that IBM, I.B.M., International Business Machines, IBM Corp are the same – and match them to a single named account called IBM.
Potato potahto: Lead duplicates
When you make a manual CRM entry for a prospect from offline or referrals, chances are that you may not have the complete name. Even the prospect may have used different variations of their names across your demand generation forms. Robert Doe could be Rob, R. Doe, or just Doe, resulting in multiple duplicate entries.
Fuzzy matching considers the probability of these variants being the same person, matches them with the email addresses, domains, and company names recorded – and segment them under one lead and one account.
Unifying sales and marketing data
You are planning to unify your sales and marketing data to get a complete view of your prospects’ journey. But there’s one problem, they reside in different tools that don’t communicate too well. Your demand generation leads are recorded differently in your CRM, and you need to clean up the data hygiene in your CRM.
Here, fuzzy matching will compare and match the records between both the tools, including empty fields in either tool such as address, pin code, and account ownership information. On the off chance that the named account matches aren’t completely positive, the fuzzy matching system can also send alerts about insufficient matches – after which, qualifying the match can be done manually.
Without fuzzy matching, you would stand to allocate a team of data professionals dedicated just to maintain CRM hygiene, write data retrieving scripts, and comb data through excel sheets. That’s hundreds of hours of insignificant manual work saved annually, which can otherwise be focused on mission-critical company problems!
How to choose the best lead-to-account matching software for your company?
What makes a value-driven lead-to-account matching software? The most important attribute is to add value across the funnel. When you’re evaluating one, ensure that you don’t fall into the pitfalls of a tool that doesn’t go beyond table stakes.
1. Don’t settle for the bare minimum of matching rules
Many tools, despite promising lead-to-account matching, are extremely basic in their matching rules. They don’t deploy fuzzy matching and settle for basic name and domain matching – which is totally obsolete for a company that’s ambitious and wants to scale fast.
For instance, RevenueHero extends beyond basic named account matching and maps every lead to the original AE who owns the account.
2. Look out for flexibility in custom mapping and routing rules
Your company might reach a point where the sheer number of contacts and accounts require more nuance in how they are matched. Some matches might need to be at a campaign-level so that an AE designated to handle specific promotion enquiries can handle those leads. The capability to generate unique links for different campaigns will come in handy here.
The routing needs to go as granular as assigning leads automatically based on account ownership, region, company size, and so on.
Whispered aside: RevenueHero lets you create lead-to-account matching and routing conditions in just a few clicks.
3. Ensure crystal clear marketing-to-sales handoff and attribution
Deploy a tool that can attribute every lead that flows through your demo request or get a quote form to your GTM efforts. Make lead recognition, lead-to-account matching, and routing an organization-wide effort that emphasizes collective pipeline success.
Fello, a sought-after lead generation platform in real estate, leveraged RevenueHero to run a fully personalized lead-to-conversion workflow across their inbound funnel.
The results: 2X higher form-to-demo conversions and a 30% increase in meeting conversion rate.
RevenueHero is a lead-to-account matching powerhouse you might want to check out
RevenueHero offers you the most advanced lead-to-account matching functionality with the added muscle of instant lead qualification, meeting scheduling and routing.
Find out how you can enable your high-intent leads to just jump on a call with you without the customary extra steps of email exchanges and agreeing on a time after manual lead qualification. Let’s talk!
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