List of PredictLeads Customers
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Since 2010, our global team of researchers has been studying PredictLeads customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased PredictLeads for Sales Automation, Sales Engagement from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using PredictLeads for Sales Automation, Sales Engagement include: Primer, a United States based Media organisation with 31 employees and revenues of $8.0 million, Loyee, a United States based Professional Services organisation with 19 employees and revenues of $3.0 million, Blueprint, a United States based Professional Services organisation with 10 employees and revenues of $1.0 million and many others.
Contact us if you need a completed and verified list of companies using PredictLeads, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The PredictLeads customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Blueprint | Professional Services | 10 | $1M | United States | PredictLeads | PredictLeads | Sales Automation,Sales Engagement | 2024 | n/a |
In 2024, Blueprint incorporated PredictLeads Job Openings data into its GTM analytics to identify target accounts, timing signals, and messaging triggers that improve campaign relevance and timing. The deployment used PredictLeads as a SaaS data feed to support Blueprint's go-to-market and CRM process area, aligning the implementation to the Sales Automation,Sales Engagement application category.
Implementation focused on the Job Openings dataset as the primary input for timing-based GTM signals. PredictLeads Job Openings data was configured to generate account-level timing signals and messaging triggers, and to enrich account records used in campaign selection. Configuration emphasized event-driven signal generation and message orchestration consistent with Sales Automation,Sales Engagement workflows, enabling automated alerts and sequence initiation for outreach.
The PredictLeads feed was integrated into Blueprint's GTM analytics layer and CRM workflows, with signals mapped to account and opportunity attributes to drive targeted outreach and campaign segmentation. Operational scope centered on the go-to-market, sales, and marketing functions at Blueprint, with the Job Openings dataset feeding campaign criteria, prioritization queues, and messaging rules used by CRM-driven outreach.
Governance established signal thresholds and messaging trigger rules to standardize when accounts were surfaced for outreach, and the rollout emphasized embedding Job Openings signals into existing campaign workflows. The case highlights Job Openings as the primary dataset used for timing-based GTM signals and reports improved campaign relevance and timing as the intended outcome of the PredictLeads integration.
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Loyee | Professional Services | 19 | $3M | United States | PredictLeads | PredictLeads | Sales Automation,Sales Engagement | 2025 | n/a |
In 2025, Loyee implemented PredictLeads to enhance its Sales Automation,Sales Engagement capabilities. PredictLeads data was integrated into Loyee.ai's sales intelligence and enrichment engine to drive account scoring and dynamic segmentation, supporting CRM-driven outbound and SDR workflows for the United States and Loyee.ai's global customers.
The deployment centralized PredictLeads as a data layer feeding the enrichment engine, with automated ingestion of prospect and firmographic signals into account scoring models and segmentation logic. PredictLeads provided the enrichment and intent signals used to populate CRM fields and to flag accounts for outbound sequences and SDR prioritization, aligning predictive scores with cadence orchestration.
Operational coverage focused on sales and SDR functions, with the same enrichment and segmentation pipelines applied across U.S. operations and extended to international customer workflows. Governance and process changes embedded PredictLeads-derived scores into CRM-driven workflows, instituting segmentation rules that trigger SDR follow up and adjust outreach priorities in real time.
The published case study notes the integration cut research time by approximately 80 percent and improved pipeline quality, outcomes reported after PredictLeads went live, with the timeline cited as an implementation estimate based on the case study context.
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Primer | Media | 31 | $8M | United States | PredictLeads | PredictLeads | Sales Automation,Sales Engagement | 2025 | n/a |
In 2025, Primer implemented PredictLeads to operationalize intent and technographic signals for paid media audience targeting. The deployment used PredictLeads in a Sales Automation,Sales Engagement context to build sharper, dynamic B2B audiences that feed the marketing process area for paid media campaigns.
Implementation centered on PredictLeads Technologies data and the explicit Technologies and technographic filters as the core dataset, configured into audience segmentation and enrichment workflows. PredictLeads was configured to generate targeted lists and to push recurring updates, reducing stale segments and improving match density for downstream ad platforms.
Integrations were established directly to Meta, Google, LinkedIn and Reddit to synchronize audiences for campaign delivery, with connectors mapping technographic attributes into platform accepted identifiers. Operational ownership and execution scope focused on Primer marketing and paid media teams, and the timing of the rollout is estimated from the PredictLeads case study and product updates referenced on both sites.
The case study explicitly cites that using PredictLeads Technologies and technographic filters improved match rates and reduced wasted ad spend for paid media campaigns, outcomes that anchor the implementation rationale. Governance moved toward centralized audience provisioning and filter driven segmentation as the primary workflow change to ensure consistent audience definitions across ad platforms.
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