Tag: PredictLeads (Page 5 of 6)

How Experts Use PredictLeads Data to Drive Smarter Outreach & Growth 🤔

February 21, 2025 /

To enhance your sales strategy, consider using PredictLeads data for your outreach. The best sales and marketing teams know that data is the foundation of relevance. Whether you’re crafting hyper-personalized outreach, identifying high-intent leads, or building a smarter go-to-market strategy, having the right insights at the right time makes all the difference.

At PredictLeads, we’re excited to see industry leaders leveraging our data to build more efficient, scalable, and highly relevant outreach strategies. Recently, some of the best in B2B sales, GTM, and demand generation have shared how PredictLeads enhances their workflows – and we want to highlight their incredible insights.

How Experts Are Using PredictLeads data for sales outreach

Across LinkedIn, industry professionals have been tagging PredictLeads and showcasing real-world applications of ourJob Openings, Technographic and News Events dataset.

📌 Job Openings as a Sales Trigger

🔹Soheil Saeidmehr (ColdIQ) and Dan Rosenthal (ColdIQ) incorporate job data into ABM (Account-Based Marketing) strategies. By combining hiring signals with firmographic and technographic data, they’re ensuring outreach messages are laser-focused on real buyer needs.

🔹 Hermann Siering (Noord50) points out how job vacancies can be a powerful trigger for outbound sales. If a company is hiring for a marketing role, why not introduce them to marketing automation software that can help their growing team? By scraping job postings with PredictLeads, sales teams can identify high-intent prospects before competitors do.

🔹 Davidson B (Zerocac) takes this further by highlighting how 57+ sales triggers, including hiring data, can boost GTM efficiency. If your sales team is still relying on manual research, you’re missing out on automated intent signals that help you reach the right accounts at the right time.

📌 Technographic Data for Smarter Targeting

🔹 Michel Lieben (ColdIQ) recognizes that B2B data is evolving, and relying on traditional databases isn’t enough. Instead, companies are turning to PredictLeads for real-time technographic insights, helping them find companies that use specific tools.

🔹 Andreas Wernicke (Snowball Consult) howcases PredictLeads, emphasizing how deep tech stack insights can determine whether a prospect is a good fit before outreach even starts.

🔹 Eric Nowoslawski (Growth Engine X) explains how technographic data can be used not just for competitor switching campaigns, but also for identifying complementary integrations. If a company already uses a relevant tool, your solution may be a perfect fit for their existing stack.

📌 Combining Multiple Signals for High-Intent Outreach

🔹 Dvin Malekian (Warmleads.io) and Elom Maurice A. stress the importance of layering multiple signals – technographic data, hiring patterns, and company news – to build hyper-targeted outreach lists. With PredictLeads, sales teams can enrich data without manually cross-referencing multiple sources.

🔹 Benoit Lecureur (gyfti) and Papa A. Sefa (Leveraged Outbound) highlight PredictLeads as a core provider of raw intent data, which can then be enhanced through tools like Clay and Smartlead for fully automated campaigns.

🔹 Hammad Afzal (Netsol Technologies) incorporates PredictLeads into a 2025-ready GTM stack, using our data to identify high-intent accounts and track job changes that indicate buying readiness.

📊 Why PredictLeads Data Gives You an Edge

Traditional cold outreach is a numbers game – but without the right insights, it’s just noise. Instead of blindly messaging tens of thousands of prospects, top-performing teams use data to turn cold emails into highly targeted, relevant outreach.

With Hiring signals, Technographic insights, and News Events data, teams can:

✅ Reach the right accounts at the right time based on real buying signals
✅ Personalize at scale without sacrificing efficiency
✅ Cut through the noise by focusing on companies that actually need their solution

Cold outreach isn’t the problem  – irrelevant outreach is. PredictLeads helps you change that.

THANK YOU! 🙏 💜

We’re incredibly grateful to all the content creators and industry experts who have shared how they use our data. There are many more insights out there, and we’d love to feature even more strategies!

💡 Have you used PredictLeads in your sales or marketing process? Drop your experience in the comments or tag us on LinkedIn – we’d love to hear from you!

#B2BData #SalesIntelligence #GrowthMarketing #SalesEnablement #OutboundProspecting #ABM #GTM

How Job Data Reveals Supply Chain Shifts: Insights from Volkswagen, EVs, and Global Labor Trends

January 6, 2025 /

Supply chains are under great strain, and no… this is not another COVID post🤷. However, we can gain valuable supply chain insights from job data to better understand current challenges.

Welcome to the “bright” present, where Lizard people and Illuminati decide that global labor shortages, geopolitical disruptions, and the rapid push for sustainability are something that businesses worldwide must adapt to.

Traditional data sources like financial reports and production metrics have long been the “go-to” of supply chain analysis. However, an often-overlooked resource – job openings – offers unique and interesting insights into a company’s operational strategies and supply chain shifts.

Let’s be honest -> the market is volatile (to say the least), and consulting firms are looking into multiple data sources to understand what’s happening.
Enter job data, a real-time indicator of a company’s priorities, challenges, and strategic moves. For supply chain professionals, analyzing job openings can provide early warnings of risks, identify opportunities, and gain competitive intelligence to stay ahead.

The Shifting Landscape of Supply Chains

Let’s examine some of the biggest forces shaking up global supply chains today:

  • Geopolitical Instability
    The U.S. CHIPS Act and Europe’s push for local manufacturing are changing trade dynamics. Companies are moving operations closer to key markets, creating both challenges and new opportunities across industries.
  • Labor Shortages
    The U.S. faces a shortfall of 80,000 truck drivers, pushing up costs and causing delivery delays. Globally, competition for talent in critical sectors like warehousing and logistics is intensifying.
  • The EV Transformation
    The automotive industry is racing to electrify, but not everyone is winning. For instance, Volkswagen (VW), Europe’s largest carmaker, faces a 64% profit slump and plans to close plants and cut tens of thousands of jobs due to struggles with EV adoption.
  • Automation and AI Integration
    Companies are heavily investing in robotics and AI to streamline operations. According to recent reports, the global warehouse automation market is projected to reach $35 billion by 2025, expanding at a compound annual growth rate (CAGR) of 12% from 2021 to 2024.

Traditional metrics like quarterly reports lag behind these changes. In contrast, job postings provide unfiltered, real-time insights into how companies are addressing these challenges.

The Volkswagen Crisis and its Supply Chain Wake-Up Call ⏰

The recent Volkswagen (VW) crisis exemplifies how job data can reveal deeper supply chain issues. Facing stiff competition from Tesla and Chinese EV makers, VW’s inability to keep up with market demands has led to plans for plant closures and job cuts (worthy mentions are also EU and its bureaucrats). The automaker’s net profits plummeted by 64% in Q3 2024 compared to the previous year.

The crisis highlights broader challenges:

  • Labor Shifts
    VW subsidiary Audi plans to halt EV production at its Belgium plant, affecting 3,000 jobs. German automakers have collectively shed 46,000 jobs since 2019, with more to come.
  • Technology Gaps
    As competitors like Tesla dominate EV sales globally, VW’s slower adoption of cutting-edge EV technologies has been costly.

Analyzing job data could have provided early warnings, such as fewer postings for high-tech roles or shifts in hiring priorities away from EV development.

Supply Chain Insights with Job Data

Now lets focus on the main event! PredictLeads’ Job Openings Dataset (woop woop 🎊). 

Here is where we have uncovered over 192 million job postings across 1.7 million websites since 2018. Here’s how this data can help out.

  1. Spot Emerging Trends
    A surge in logistics job postings in Mexico aligns with North America’s reshoring efforts.  Fun Fact => Mexico is now the largest importer to the U.S. ($43.7 billion) ahead of China ($39.9 billion). 🌮
  2. Identify Bottlenecks Early
    Aggressive hiring for similar roles in specific regions often signals labor shortages. Logistics companies scrambling to recruit truck drivers last year foreshadowed higher transportation costs and delays.
  3. Evaluate Supplier Resilience
    Job postings reveal supplier priorities. Companies hiring sustainability officers likely align with green initiatives, while those focused on automation are investing in efficiency.

Example: Semiconductor Shortages

The global chip shortage offers another compelling case. Months before the crisis peaked, companies like TSMC and Intel ramped up hiring for “Supply Planning Professionals” and “Procurement Specialists.” Tracking these trends could have allowed businesses to diversify suppliers or stockpile inventory before shortages disrupted industries.

The Advantage

PredictLeads’ Job Openings Dataset offers insights for supply chain professionals:

  • Job Titles and Categories: Understand where companies are investing resources.
  • Salary and Seniority Data: Understand labor market competition and hiring priorities.
  • Geographic Trends: Map hiring hotspots to identify growth or risk areas.
  • Technology Mentions: Spot the adoption of ERP systems, robotics, or AI.

With 7 million active job openings and 53 million new postings detected last year, this dataset provides a real-time pulse on global hiring trends.

Conclusion: Turning Job Data into Strategy

The Volkswagen crisis, semiconductor shortages, and the EV transformation remind us that supply chains are in constant flux (fancy talk for “nobody really knows what’s going on”). Job data offers a proactive, actionable lens into these shifts, enabling businesses to anticipate risks and seize opportunities before competitors.

As global supply chains will continue evolving in 2025, leveraging real-time job data could be the key to staying resilient and competitive.

Questions? PredictLeads is here to help! 🙂

(+ This is our first blog for 2025 → thank you so much for reading 🙏)

AI Adoption and Sector Shifts Through Job Openings Data
Understanding Pension Funds’ Strategic Shift to Private Markets with PredictLeads’ Data
Use Data Enrichment to Filter and Prioritize Prospects

Partnering up with Clay :)

September 3, 2024 /

As PredictLeads partnered up with clay.com, it seemed only natural to then go work with clay in the literal sense. This new phase marks the exciting PredictLeads Clay partnership, further enhancing collaboration.

As much as we try it’s really challenging for all of us to look at the camera at the same time 😀

Jokes aside, it was an interesting coincidence though not planned to happen :). Eva booked us for a nice evening of working with clay (literally). Through this collaboration with clay, the PredictLeads Clay partnership certainly extended beyond just business.

Screenshot

When working with clay to create a finished ceramic product, two primary steps are needed when heating / firing the clay:

There were also two types of “tables” we were working at. This was the “Pottery Mill”.
  1. Bisque Firing (First Firing): The purpose is to transform the raw clay into a hard ceramic state. This firing removes moisture from the clay and drives out organic materials. The temperature for bisque firing in our case was 950°C (1,750°F).
  2. Glaze Firing (Second Firing): After bisque firing, the piece is coated with glaze, a glass-like coating that provides a smooth, glossy finish. The glazed piece is then subjected to a second firing, known as glaze firing. This firing melts the glaze and forms a glassy, non-porous surface on the ceramic piece. In our case Glaze firing temperature was 1,250°C (2,345°F).
Till the next team meetup! 🙂

We’re still waiting for the clay shop to go through these two steps and we can’t wait to see what we produced :). Ultimately, this hands-on experience is all part of what makes the PredictLeads Clay partnership such an enriching experience.

Cheers, PredictLeads

Unlock Business Insights with the Clay + PredictLeads Integration
Why Companies Rely on PredictLeads Data for Accuracy Instead of LLMs
Finding Top performing Companies

Introducing PredictLeads’ New Technology Detection API Endpoint

August 21, 2024 /

We are excited to announce a new API endpoint from PredictLeads designed to help you discover which companies are utilizing specific technologies. Whether you’re tracking the adoption of CRM systems, cloud computing platforms, enterprise resource planning tools and more, this API offers a powerful way to gather and analyze technology usage data across the web.

How It Works

Our new endpoint allows you to ping a specific Technology ID and receive a detailed list of companies and websites utilizing that technology. This data can be invaluable for market research, sales prospecting, competitive analysis and more.

Example API Endpoint

You can use the following endpoint to start exploring technology detections:

https://predictleads.com/api/v3/discover/technologies/[TECHNOLOGY ID]/technology_detections?api_token=[API_token]&api_key=[API_Key]

Here are some Technology IDs you can use to test the API:

What You Get

When you query this endpoint, the API returns data about where the technology has been detected, including:

  • Company Information: Details about the company using the technology.
  • Subpage Detections: Specific subpages where the technology has been found.
  • Technology Details: Information about the technology, such as its name, description, and category.

Sample cURL Request

Here’s an example of how you can make a request using cURL:

curl –request GET \

  –url https://predictleads.com/api/v3/discover/technologies/70392f20-b531-53cc-afa6-26416c0d582d/technology_detections \

  –header ‘X-Api-Key: {your_api_key}’ \

  –header ‘X-Api-Token: {your_api_token}’

Additional information can be found in our docs “here”. 

Interested in Trying It Out?

We’re offering 100 free API calls to anyone who wants to test this new endpoint. Sign up at PredictLeads and start exploring + Feel free to let us know if there are any specific technologies or IDs you’d like to check the coverage of.

Note on Development

Please note that we are continually improving this endpoint, and your feedback is essential. If you encounter any issues or have suggestions, feel free to reach out to our support team.

Technology Data Snapshot

  • Technologies Tracked: ~15,000
  • Technology Adoptions Detected Since 2018: ~636 million
  • Websites Tracked: ~47 million
  • Technology Identifications Last Month: ~18 million
  • Technology Identifications Last Year: ~193 million

We look forward to seeing how you use this new feature to enhance your business intelligence and decision-making processes!

How Hiring & Tech B2B Sales Signals Help Close More B2B Deals?
Use Data Enrichment to Filter and Prioritize Prospects
Introducing Key Customer Data

Boost Your Lead Generation and Email Campaigns with Connections Dataset

July 25, 2024 /

Hey everyone! Today, let’s dive into how personalized sales outreach with data can revolutionize your approach and make connections more meaningful.

In sales, finding and engaging the right prospects can feel like searching for a needle in a haystack. Sending non personalized emails is just a thing of the past and companies offering sales solutions are looking into data to add that personalized touch that increases those reply rates that we all like.

Job Openings Dataset as well as the News Events Dataset are incredibly useful and widely adopted for uncovering new leads and improving sales outreach. However, there is a unique dataset that is gaining significant attention. This dataset, which is not yet widely used due to its limited availability, holds great potential for transforming sales strategies. Here is why:

We all know that companies like to put logos of other companies they work with, on their website to gain credibility. Since those logos are often not backlinked, PredictLeads has built an image recognition system that connects these logos with company domain names. By checking the company’s Case studies pages, testimonials, “Our customers” sections and more allows PredictLeads systems to identify them as customers, partners, vendors, sponsors and more.


Here’s a quick rundown of how the Connections Dataset can revolutionize your sales efforts and how it’s used to target High-Value Prospects.

Identifying and Prioritizing Key Prospects

First up, let’s talk about finding those high-value prospects. With the Connections Dataset, you can pinpoint companies that already have significant relationships with your existing clients or partners. This means they’re more likely to convert because there’s already some trust and relevance built in.

How to Do It:

  1. Analyze Data: Dive into the Connections Dataset to find companies that share multiple connections with your current network.
  2. Prioritize Prospects: Rank these companies based on the number and quality of shared connections.
  3. Sales Outreach: Focus your efforts on these high-value prospects. Make sure to highlight the mutual connections and the benefits of joining an established network.

Example: A SaaS company finds that several of its clients are partners with a leading industry player. By targeting this player and emphasizing the mutual benefits, they can craft a top notch outreach that’s hard to ignore.

Next, let’s make your emails shine. 

Personalized outreach campaigns are the way to go because they address the specific needs of each recipient. By referencing the target company’s partnerships or integrations, your emails can be way more relevant and engaging.

How to Do It:

  1. Gather Insights: Use the Connections Dataset to get detailed insights into the target company’s partnerships and integrations.
  2. Personalize Emails: Craft email content that references these relationships, making it super relevant.
  3. Automate Personalization: Use AI tools to scale this personalization process, ensuring each email is tailored to the recipient’s context.

Example: An AI-powered email platform identifies a potential client’s recent partnership with an e-commerce platform like Shopify. They send a personalized email campaign highlighting success stories of similar clients who benefited from this integration. Boom -> relevance and appeal.

Warm Introductions through Mutual Connections

Finally, let’s talk about using mutual connections for warm introductions. These can significantly boost your chances of successful engagement. The Connections Dataset can help you leverage existing relationships to approach leads with more trust and credibility.

How to Do It:

  1. Map Networks: Use the ConnectionsDataset to map out mutual connections between your company and target leads.
  2. Request Introductions: Reach out to these mutual connections for warm introductions, explaining the mutual benefits.
  3. Follow-Up Strategy: Develop a follow-up strategy that leverages the credibility of the mutual connection.

Example: A lead generation company finds that one of its key clients is also a partner of a high-value prospect. They request an introduction from the key client, who provides a warm referral, significantly improving engagement chances and improves their data-driven sales outreach.

Utilizing AI for Enhanced Personalization & amplify the Impact with automation

AI can take your use of the ConnectionsDataset to the next level by automating the analysis and personalization processes. Here are some tips: 

  1. Automated Analysis: AI analyzes the dataset to identify patterns and insights, like high-value prospects and mutual connections.
  2. Scale Personalization: AI personalizes email content at scale by incorporating insights from the dataset into email templates.
  3. Predictive Analytics: AI uses historical data to predict which prospects are most likely to convert, helping prioritize efforts.
  4. Continuous Learning: AI systems learn from campaign outcomes, refining algorithms to improve future personalization and targeting.

Example Implementation:

An AI-powered email platform integrates with the Connections Dataset, analyzing the dataset to identify key relationships and generating personalized email content. It predicts which prospects will respond positively and continuously refines its personalization algorithms.

Conclusion

Since 2019, over 170 million business connections have been detected, with business connections data available for 38,5 million websites. Last month alone, there were approximately 12 million business connections, and around 57 million over the past year. The Connections Dataset is a goldmine for lead generation companies and those using AI for personalized emails. By providing detailed insights into company relationships, it helps you target high-value prospects, create relevant and engaging email campaigns, and leverage mutual connections for credible engagements. Combined with AI, it automates these processes and achieves personalization at scale, leading to higher engagement rates and better sales outcomes.

Feel free to let us know if you or if you’d like to learn more. We’re here to help:)!

How 🟣PredictLeads + Pipedream🟢 Help Founders Score and Reach Out to Leads with Relevant, Timely Signals
Company Intelligence Data in Your Sales Enablement Platform
Use Data Enrichment to Filter and Prioritize Prospects
« Older posts Newer posts »

© 2026 PredictLeads Blog

Theme by Anders Noren — Up ↑