We detected 83 customers using Midbound and 13 companies that churned or ended their trial. The most common industry is Software Development (49%) and the most common company size is 11-50 employees (44%). Our methodology involves detecting JavaScript snippets or configurations on customer websites.
Note: We only track when a company installs the Midbound tracking script on their website (majority of customers)
About Midbound
Midbound identifies anonymous website visitors at the person level, revealing their names, roles, and contact details to help B2B marketing and sales teams uncover hidden demand, retarget qualified buyers who clicked ads but didn't convert, and optimize ad spend by tracking which campaigns drive ideal customer profiles.
🔧 What other technologies do Midbound customers also use?
Source: Analysis of tech stacks from 83 companies that use Midbound
Commonly Paired Technologies
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Shows how much more likely Midbound customers are to use each tool compared to the general population. For example, 287x means customers are 287 times more likely to use that tool.
I noticed something striking about companies using Midbound: they're running sophisticated B2B go-to-market operations that blend product-led signals with traditional sales motions. The cluster of tools like Koala, Dreamdata, Factors.ai, and Instantly.ai Visitor Identification tells me these companies are obsessed with identifying intent and understanding the buyer journey across multiple touchpoints. They're not just tracking leads, they're mapping entire account behaviors.
The pairing of Midbound with Koala makes perfect sense for this strategy. Koala excels at capturing product usage signals and website engagement, feeding behavioral data that Midbound can use to trigger timely outreach. Similarly, the combination with Dreamdata and Factors.ai reveals these companies want attribution clarity. They need to know which channels and touchpoints actually drive pipeline, which is crucial when you're coordinating inbound signals with outbound efforts. Add Instantly.ai Visitor Identification to the mix, and you see a workflow where anonymous visitors get identified, their behavior gets tracked across properties, and sales gets alerted at exactly the right moment.
The full stack reveals these are sales-led organizations with strong marketing support, likely at the growth or scale-up stage. They've moved beyond basic marketing automation and are investing in specialized tools that give them competitive advantages in timing and personalization. These aren't early-stage companies figuring things out. They're mature enough to have complex tech stacks but still hungry enough to invest in tools that promise better conversion through precision.
👥 What types of companies is most likely to use Midbound?
Source: Analysis of Linkedin bios of 83 companies that use Midbound
Company Characteristics
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Shows how much more likely Midbound customers are to have each trait compared to all companies. For example, 2.0x means customers are twice as likely to have that characteristic.
Trait
Likelihood
Industry: Software Development
25.3x
Company Size: 51-200
5.7x
Country: US
4.6x
Company Size: 11-50
2.5x
I noticed that Midbound's customers are predominantly B2B software and technology companies building tools that solve operational inefficiencies. These aren't consumer apps. They're creating platforms for specific professional workflows: research analysis tools, billing automation, compliance management, sales intelligence, workforce tracking, and marketing analytics. Many are enabling AI-powered automation in traditionally manual processes. A smaller segment includes professional services firms (marketing agencies, IT consulting) and niche B2B businesses in construction, healthcare, and manufacturing.
These are overwhelmingly growth-stage companies. The employee counts cluster between 11-200, with most in the 11-50 and 51-200 ranges. Funding stages span pre-seed to Series B, with seed being most common. Many have raised between $5M-$20M. They're past the garage stage but still scaling. They have real customers and proven product-market fit, but they're not yet established enterprises. The bios often mention specific customer counts or named brands using their product, suggesting they're in that critical phase of proving credibility and scaling go-to-market.
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