Account Based Marketing - ABM
Along with the core team, we provided leadership for MarketerHire's ABM initiatives by suggesting the ABM's initial phase and layering several experiments to determine the ideal user journey funnels, ICPs, and distribution channels.
Along with the CRO project to help optimize the user journey, and better understand audiences and their pointpoint conversion catalyst.
The image anove shows the conversion lift patterns durring weekdays starting from the 20th Aug with the project launch
How we shipped Experiments Quickly, and drove 408% Conversion Uplift
How a Three-Layered Personalization Strategy 5Xed Conversion Rates
What you'll learn
How to combine firmographic, CRM, and behavioral personalization
How personalization can 5X conversions from stable traffic
Why testing speed is key to successful experimentation
What you’ll need
A reverse IP lookup service to de-anonymize visitors
A website personalization platform that connects to your CRM
A data enrichment tool to help identify key contacts within accounts
⚠️ The Problem
On-demand talent platform MarketerHire had a ton of traffic coming in. Paid, organic, referral, social—everything was looking good.
Problem was, their traffic wasn’t converting into inquiries, opportunities, or deals. We dug into MarketerHire’s homepage, we learned why. The homepage had:
Universal messaging: A static website communicated MarketerHire’s primary value prop. While it was strong, it wasn’t relevant to every visitor.
Static user journeys: Every visitor hit the same website and went through the same user journey—regardless of their unique challenges, needs, and goals.
If we were going to turn MarketerHire’s traffic into inquiries and customers, we knew both of those problems had to change.
📜 The Hypothesis
MarketerHire funneled diverse visitors into a generic website. Hachimi’s hypothesis was that by segmenting traffic and delivering diversified experiences, we could increase conversion rates.
We identified eight personalization levers:
Lack of personalized messaging
Static user journeys
Account-level pain point
Value prop copy
Leading page structure
Campaign traffic segmentation
And we planned to pull those levers with a three-pronged personalization strategy.
💡 The Solution
Layer 1: Firmographic
We connected a CRO solition to the B2B data platform, Clearbit. (Although other customer data platform like 6sense would also work.) Using Clearbit Reveal, we de-anonymized traffic and segmented it based on company size, industry, revenue, and other firmographic data.
We analyzed each segment and identified personalization opportunities around messaging, user journeys, engagement layers, and other levers.
Take company size, for example:
“Startups typically experience budget pain points,” says Hachimi. “For SMBs, the bottleneck is recruitment and hiring speed.”
Instead of a generic headline, we focused on the most common pain point among smaller companies: budget. Different industries triggered changes, too.
We changed what marketing talent he highlighted on the homepage depending on what industry visitors worked in.
Services companies saw services experts. Consumer tech businesses saw B2C specialists. Apps saw marketplace experts. ...And so on.
Layer 2: CRM
The first layer focused on new visitors—people MarketerHire knew little about. But they also received a lot of returning visitors from prospects, leads, and existing customers.
“We already know what journey they've been through,” Hachimi explains. “We know what sort of pain points they’re facing.”
The second layer checked if visitors were in the company’s CRM. If they had records for a visitor, we personalized the homepage using information like:
Contact-level data: Mention individual buyers and stakeholders by name.
Unique pain points: Hyper-personalize messaging to specific pain points like hiring a programmatic marketer for a consumer tech company.
Account manager details: Replace anonymous contact forms with the direct contact details for the account’s assigned contact manager.
Layer 3: Behavioral
MarketerHire’s third and final personalization layer was behavioral. In other words, personalizing the homepage depends on what the visitor has done on the website.
We used two main tactics:
Campaign: We matched homepage messaging to campaign messaging. For example, if someone clicked a D2C-focused ad, the homepage adapted its messaging to D2C pain points, goals, and services.
Past behavior: Actions speak louder than words. We personalized MarketerHire’s website based on visitor behavior—the pages they accessed, blogs they read, forms they filled out, and so on.
Across all three tiers, We treated each personalization segment as an experiment. We’d make a change, study the impact, and assess the outcome. Some experiments worked. Many micro experiments (copy tweaks, design changes, and so on) delivered solid conversion gains of between 12 and 15%.
But others fell flat.
Those negative personalization experiments were just as valuable. We cut poorly performing messaging and refined MarketerHire’s positioning.
On a macro level, the gains were enormous. We drove a 408% uplift in total conversions per month. Without adding any more ad spend or increasing traffic, we captured 100 extra leads.
We provided a support layer to MarketerHire by impleneting a stack of rapid experimentation on site conversion through AB testing tools and plugins, targeting accounts and visitors based on their fundamental interests and business pain points, and deliver the necessary copy, messaging and creative on site to optmizae traffic conversions.
Recording and ongoing over 20%+ improvements in conversion rate, and total lead growth on a monthly basis.
Brandzen partnered with MaakterHire to assist the core team with an ongoing project, addiing value in the directions of ABM (account based marketing) Strategy implementation, infrastrucutre development, CRO experiments, and more