We detected 565 customers using Plerdy and 21 customers with estimated renewals in the next 3 months. The most common industry is Retail (27%) and the most common company size is 2-10 employees (35%). Our methodology involves detecting JavaScript snippets or configurations on customer websites.
Note: We are unable to detect churned customers for this vendor, only new customers
About Plerdy
Plerdy provides conversion rate optimization tools including heatmaps, session recordings, SEO checker, and pop-up forms to help businesses analyze user behavior and improve website performance. The platform combines UX analysis and CRO insights to identify design flaws and increase conversions without slowing down page speed.
🔧 What other technologies do Plerdy customers also use?
Source: Analysis of tech stacks from 565 companies that use Plerdy
Commonly Paired Technologies
i
Shows how much more likely Plerdy 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 that Plerdy users are primarily e-commerce and direct-to-consumer companies obsessed with conversion optimization and understanding their customer journey. The combination of analytics tools, fraud prevention, and attribution tracking tells me these are businesses running paid traffic campaigns where every visitor matters and margins are tight enough that they need to squeeze value from every click.
The pairing with Microsoft Clarity is particularly revealing. These companies are layering multiple session recording and heatmap tools, which suggests they're serious about understanding user behavior but may be working with limited budgets, since Clarity is free. The strong correlation with Truconversion and ClickRack reinforces this: they're stacking complementary analytics tools to get different views of the same problem rather than investing in a single enterprise solution. Attribuly's presence confirms the e-commerce focus, as it's specifically built for tracking Shopify attribution across multiple channels. Fraud Blocker appearing frequently suggests these companies are battling click fraud, which means they're likely running substantial Google Ads or Facebook campaigns where fraudulent clicks actually hurt their bottom line.
The full tech stack screams marketing-led companies in the growth stage, probably doing between $1 million and $20 million in annual revenue. They're sophisticated enough to understand they need these tools but not large enough to afford enterprise solutions like ContentSquare or FullStory. They're actively running paid acquisition, dealing with attribution challenges across multiple channels, and trying to optimize their conversion funnels without a huge analytics team.
👥 What types of companies is most likely to use Plerdy?
Source: Analysis of Linkedin bios of 565 companies that use Plerdy
Company Characteristics
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Shows how much more likely Plerdy 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
Country: UA
65.6x
Industry: Retail
7.4x
Industry: Advertising Services
4.0x
Country: AU
3.7x
Company Size: 51-200
3.2x
Industry: IT Services and IT Consulting
2.8x
I noticed that Plerdy users span a remarkably wide range of industries, but they share a common thread: they're primarily companies with digital storefronts or customer-facing websites where conversion matters. I see e-commerce brands selling everything from skincare to apparel, service providers like medical practices and marketing agencies, B2B software companies, financial institutions, and even nonprofits. What ties them together isn't what they sell, but that they need their websites to perform. They're building digital experiences where user behavior directly impacts revenue or mission success.
The stage signals are mixed but telling. I see mostly small to mid-sized companies, with employee counts clustering between 11-50 and 51-200. Very few mention funding rounds, and when they do, it's typically seed or Series A. Many emphasize years of experience (5+ years is common), suggesting established operations rather than fresh startups. They're past the experimental phase but haven't reached enterprise scale. These are companies in growth mode, professional enough to invest in optimization tools but agile enough to care deeply about conversion rates.
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