Category: Competitive Intelligence (Page 1 of 2)

How PitchBreeze is Changing the Game in Sales Outreach – An Insider’s Perspective

Sales is a game of timing, relevance, and persistence. But for most sales teams, that means endless hours of research, tracking key events, and hoping to catch prospects at the right moment. What if there were a better way? Roman, co-founder of PitchBreeze, sat down with us to share his journey, challenges, and how PredictLeads data is helping redefine sales intelligence.

From Frustration to Innovation: The Birth of PitchBreeze

Before starting PitchBreeze, Roman and his team faced an all-too-common sales struggle: it took six years to close 19 out of their top 20 target accounts. Why? Because success required three key elements – right person, right time, right message – but achieving that consistently was painfully slow. Hours were spent monitoring key events and researching opportunities. This frustration sparked the idea: there must be a way to automate and optimize this process.

PitchBreeze started as an ambitious project: fully autonomous AI-driven outreach. However, the reality of market feedback forced a pivot. Roman recalls, “Facing the fact that we must pivot from our original idea of a fully autonomous AI outreach was really hard. But having unwavering support from my co-founder and family brought me back.” Instead of automating everything, the team focused on curating high-quality sales signals – removing noise and ensuring sales reps could act on reliable insights.

Finding the A-Ha Moment: The Power of High-Quality Data

One of the biggest challenges in sales intelligence is filtering through the noise. Many tools flood sales teams with data, but few help prioritize what actually matters. Roman shares a simple but effective mindset shift: “Instead of collecting as much information as possible, we focused on curating it the right way.”

PredictLeads played a key role in this evolution. By integrating our enriched sales signals, PitchBreeze improved its ability to surface relevant sales triggers. Roman noted, “PredictLeads data helped us cover gaps in sales research and find hidden insights in a structured way. Monitoring companies became so much easier, and having reliable sources improved credibility too.”

This shift wasn’t just about improving automation – it was about helping sales teams become more strategic and efficient.

Overcoming Resistance: The Battle Against “Sales Spam”

Not everyone is convinced AI belongs in sales. Roman recalls an early conversation with a Series B startup CEO who bluntly stated, “Templated outreach is like Voldemort – don’t even mention it by name. We do everything manually.” This pushback was a wake-up call. Many sales leaders still resist automation, fearing it will lead to impersonal, spammy outreach.

But here’s the irony: sales teams struggle to hit quotas, pipelines are dry, and outreach is often ineffective. The challenge isn’t automation – it’s bad automation. Instead of flooding inboxes, PitchBreeze’s approach prioritizes relevance and timing. As Roman puts it, “We focus on helping sales reps bring value instead of bombarding prospects with irrelevant cold calls and emails.”

The Future of Sales: Where AI and Strategy Meet

So, what’s next? Roman acknowledges the uphill battle: “The sales world is activity-driven >>make X calls, send Y emails<< but this philosophy is broken. AI spam is making it worse, and sales leaders are beginning to see the cracks.”

He believes the future belongs to companies that strike the right balance – leveraging AI to enhance, not replace, human connection. Looking ahead, Roman hopes PitchBreeze will be remembered as the company that “got it right” – helping sales teams engage meaningfully instead of drowning prospects in generic outreach.

As for what he wishes he’d known sooner? “Focus, focus, focus. Everyone says it’s the best startup survival recipe, but it’s easier said than done with all the feedback from the market.” No matter what happens, he’s proud of one thing: “My daughter seeing me as an entrepreneur – the first one in three generations.” 💜

Bringing It All Together

Sales teams today are navigating an increasingly complex landscape. With AI-powered sales intelligence tools like PitchBreeze, powered by high-quality data from PredictLeads, they have a better chance of succeeding without burning out. The key? Moving beyond raw data collection and instead leveraging curated insights to engage the right people at the right time.

The sales world is evolving. The question is – will your team evolve with it?

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

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

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

Job Listings → Supply Chains → Secrets Revealed 🤯

Supply chains are under great strain, and no… this is not another COVID post🤷. 

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? We’re here to help! 🙂

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

Unlock Business Insights with the 💜Clay + PredictLeads 💜 Integration

The Clay and PredictLeads integration is a game-changer for businesses looking to supercharge their prospecting and enrichment capabilities. This seamless connection enables users to access real-time data about companies, including the latest news, hiring trends, partnerships, and tech stack insights – all within the Clay platform. Whether you’re a sales professional, a recruiter, or an investor, this integration gives you the tools to make data-driven decisions and take actionable steps.

Here’s a step-by-step guide to get started:

Step 1: Register at PredictLeads

To begin, create your PredictLeads account by signing up here. Upon registration, you’ll receive 100 free API calls per month – perfect for getting started.

  • Once your account is set up, navigate to your Dashboard to locate your API Key and API Token.
  • Keep these credentials handy since they’ll be essential for connecting PredictLeads to Clay.

💡 Need more API calls? Reach out to PredictLeads at info@predictleads.com or use this link

Step 2: Add PredictLeads to Clay

Now that you have your API credentials, it’s time to integrate PredictLeads with Clay.

  1. Open Clay and head to Settings > Connections.
  2. In the integration provider search panel, look for PredictLeads.
  3. Click Add Connection.

You’ll be prompted to:

  • Name your connection: Choose a descriptive name for your key.
  • Enter your PredictLeads API credentials: Use your API Key as the username and API Token as the password.

Once saved, Clay will generate a secure PredictLeads connection for you. 🎉

Step 3: Create a Workspace in Clay

With PredictLeads now connected, it’s time to build your workspace.

  1. Create a new workspace in Clay – > this is where you’ll manage the domains you want to enrich.
  2. You can either:
    • Import domains directly from your computer or CRM, or
    • Search for companies directly within Clay.
    • And more… It’s Clay, so you know they got you covered 😉

Step 4: Enrich Your Data with PredictLeads

Once your domains are added, it’s time to enrich them using PredictLeads’ datasets.

  1. Select the domains you want to enrich.
  2. Search for PredictLeads in the enrichment panel.
  3. Choose the datasets that suit your needs:
    • Find Most Recent News: Stay updated on product launches, funding rounds, or acquisitions.
    • Analyze Tech Stack: Gain insights into a company’s frequently mentioned technologies.
    • Find Open Jobs: Uncover hiring trends and identify growth areas.
    • Find Connections: Discover vendors, customers, and investors linked to a company.
  1. Configure your inputs and let PredictLeads do the magic.

Managing API Calls

Each enrichment will consume PredictLeads API calls, so keep an eye on your usage here

For additional API capacity, contact PredictLeads at info@predictleads.com.

Why Use the Clay + PredictLeads Integration?

This integration streamlines the process of gathering actionable insights. With just a few clicks, you can:

  • Personalize your outreach with relevant news.
  • Stay ahead of competitors by analyzing hiring trends and tech stacks .
  • Strengthen pitches with verified customer or vendor connections.

Whether you’re looking to close deals faster, identify investment opportunities, or build stronger partnerships, the Clay + PredictLeads integration is your ultimate tool.

🎯 Ready to try it out? Start by registering at PredictLeads and connecting it to your Clay account. Let us know if you have any questions – We’re happy to help 💜 💪

Happy enrichments! 🚀

NVIDIA’s Hiring Trends Unveiled: What They Tell Us About the Future of AI, Engineering, and Global Innovation

As one of the most influential technology companies, NVIDIA continues to shape the future of computing, AI, and engineering. Their hiring trends provide a unique window into not only their internal strategy but also broader industry shifts in talent demand, skill specialization, and geographic hiring hotspots.

After analyzing their recent job postings, here are the key takeaways that illustrate where NVIDIA -> and the tech world -> are heading.

A Focus on AI and Deep Learning Talent

NVIDIA is doubling down on talent in AI and deep learning, as evidenced by roles like “Deep Learning Engineer” and “Solutions Architect – Generative AI.” The required skills highlight a strong emphasis on:

  • Frameworks like PyTorch and TensorFlow.
  • GPU programming expertise in CUDA.
  • Knowledge of Large Language Models (LLMs) and deep learning inference optimization.

The takeaway? As AI becomes integral to industries ranging from healthcare to gaming, there’s a growing demand for engineers who can scale and optimize AI systems. NVIDIA’s investments show that these skills aren’t just niche – they’re foundational to future innovation.

Geographic Distribution: A Global Talent Network

NVIDIA’s job openings span key global tech hubs:

  • United States: With high-paying roles in Santa Clara, CA, NVIDIA underscores the continued dominance of Silicon Valley as a global innovation center.
  • India: Bengaluru and Hyderabad are becoming vital for engineering and software development, driven by NVIDIA’s push into areas like system design, physical verification, and datacenter optimization.
  • Israel: A hub for innovation in networking and automation, emphasizing NVIDIA’s commitment to hardware-software synergy.

This global hiring strategy reflects the need for distributed teams capable of driving innovation in different markets, leveraging both local expertise and global collaboration.

Industry-Specific Innovation: Healthcare and Automotive

Some of NVIDIA’s most strategic roles reveal their push into vertical industries:

  • Healthcare: Roles like “Solutions Architect – Healthcare” emphasize NVIDIA’s ambition to power AI-driven diagnostics, remote patient monitoring, and personalized medicine. Their deep learning technologies are enabling transformative changes in digital health.
  • Automotive: With the rise of autonomous vehicles, NVIDIA’s automotive team is expanding rapidly. Positions like “Senior Account Manager – Automotive” show how they’re targeting Tier 1 OEMs in markets like China to advance autonomous driving solutions.

These trends highlight how NVIDIA is applying its core AI and GPU technologies to drive innovation in two of the most rapidly evolving industries.

The Rise of Cross-Functional and Collaborative Roles

NVIDIA’s hiring isn’t limited to purely technical roles. Job openings such as “Customer Program Manager” and “Solutions Architect” highlight the importance of cross-functional expertise:

  • Collaboration with internal teams and external customers.
  • Bridging the gap between technical engineering and real-world application.
  • Driving projects from concept to execution.

As products become more complex, roles that require technical know-how combined with strategic collaboration are gaining prominence.

Skills in Demand: What Employers Are Looking For

NVIDIA’s job descriptions offer a clear snapshot of the skills companies are prioritizing:

  • Programming Languages: Python, C++, and CUDA remain critical.
  • Tools and Frameworks: Familiarity with Docker, Kubernetes, TensorFlow, and PyTorch is non-negotiable for many roles.
  • Emerging Areas: Skills in distributed systems, AI inference optimization, and silicon performance modeling stand out.

For professionals, staying ahead means continuously investing in skills that align with these trends.

Competitive Compensation and Growth Opportunities

NVIDIA’s salary ranges – some reaching over $390,000 annually—demonstrate the premium placed on top talent in engineering, AI, and software development. This not only reflects the complexity of their projects but also sets a benchmark for what the industry is willing to pay for expertise.

Final Thoughts: What This Means for the Industry

NVIDIA’s hiring trends provide a roadmap for where the tech industry is heading:

  • AI and deep learning are transitioning from cutting-edge to essential.
  • Global hiring strategies are here to stay, with companies leveraging local talent for global innovation.
  • Industry-specific applications of technology, like healthcare AI and autonomous vehicles, will define the next decade.

For businesses and professionals alike, staying ahead means recognizing these trends and adapting. Whether you’re looking to hire top talent, pivot your skills, or align your business strategy, NVIDIA’s approach offers valuable lessons.

Want to dive deeper into these insights?

At PredictLeads, we enable businesses to track hiring trends, company signals, and emerging demands. If you’re curious about NVIDIA’s job data or want to analyze trends for other companies, you can register with PredictLeads and try the following API call:

https://predictleads.com/api/v3/companies/nvidia.com/job_openings?api_token=[API Token]&user_email=[Email]

Curious about how hiring trends can inform your strategy? Let’s connect.

AI Adoption and Sector Shifts Through Job Openings Data

Artificial intelligence is changing the job market, prompting significant shifts in workforce needs across various sectors. By analyzing job postings, investment companies can gain insights into which industries are reducing their hiring for roles likely to be automated. This helps them understand potential revenue impacts and growth opportunities.

Detecting AI Adoption Trends
AI tools are increasingly integrated into business functions, ranging from data analysis to customer service and legal assistance. For example, paralegals, traditionally performing research and document review, are being replaced by AI systems that can quickly and accurately handle these tasks. This trend is highlighted in Nexford University’s article “How Will Artificial Intelligence Affect Jobs 2024-2030,” which underscores the growing use of AI in roles previously performed by humans. Monitoring job postings can reveal decreases in hiring for such roles, indicating a shift towards AI-driven solutions.

Strategic Insights for Investment
Investment companies must stay ahead of market changes to make informed decisions. A decline in job openings for traditional roles, such as customer service representatives or paralegals, in sectors like customer service, sales, and legal services can signal a move towards AI automation. This information is crucial for identifying industries at risk of revenue loss due to a lack of automation foresight, helping investors focus on more promising areas.

For example, companies like Google and Duolingo are already replacing human roles with AI technologies. Google has integrated AI into its customer care and ad sales processes, while Duolingo uses AI for content translation, reducing the need for human contractors.

Economic Impact of AI
The economic implications of AI are substantial. A McKinsey report predicts that AI could add $13 trillion to global economic activity by 2030, primarily through labor substitution and increased innovation. However, this growth comes with job displacement. Monitoring job opening trends helps investment firms gauge which companies and sectors are reducing their workforce due to AI, identifying potential risks and opportunities.

Recent examples include:

Understanding AI adoption through job postings allows investment companies to anticipate market shifts and focus on high-growth sectors. Sectors such as AI development, advanced manufacturing, and healthcare innovation are likely to attract more investment due to their proactive adoption of AI technologies. This foresight helps investors mitigate risks and capitalize on new growth opportunities.

Additional Data from the ADP National Employment Report
The ADP National Employment Report for June 2024 provides a comprehensive overview of job trends. According to the report, private employers added 150,000 jobs in June, marking a slowdown in job creation for the third straight month. “Job growth has been solid, but not broad-based. Had it not been for a rebound in hiring in leisure and hospitality, June would have been a downbeat month,” said Nela Richardson, Chief Economist at ADP​ (ADP Media Center)​.

This data underscores the importance of monitoring employment trends to understand the broader economic impact of AI and inform strategic investment decisions.

The chart titled “ADP Employment: Establishment Size Year-over-Year Percent Change” tracks the year-over-year percentage change in employment across different establishment sizes from 2011 to 2024. 

Here are some key points:

  • Trend Analysis: The chart illustrates fluctuations in employment growth across different establishment sizes over the years. A notable drop is observed around 2020, corresponding with the COVID-19 pandemic’s impact on employment. Post-2020, there is a marked recovery, with larger establishments (500+ employees) showing a more robust recovery compared to smaller establishments.
  • Recent Trends: As of June 2024, the growth rates have stabilized, though smaller establishments (1-19 employees) show slower growth compared to larger establishments. This indicates that larger companies are recovering and possibly investing more in automation and AI technologies, while smaller businesses are facing more challenges.

This chart helps visualize the employment dynamics and how different-sized businesses have been affected over the years, providing valuable context for understanding the broader economic landscape and the impact of AI on employment.

For more detailed insights and statistics, the full ADP Employment Report is available here.

Conclusion

By analyzing job openings data, investment companies can gain valuable insights into AI adoption trends and their impact on various sectors. This approach helps identify industries reducing traditional roles due to AI, enabling better-informed investment decisions. Utilizing datasets like those from PredictLeads can provide the detailed, real-time insights needed to stay ahead of market shifts, mitigate risks, and seize growth opportunities in an AI-driven economy.

  • Job Openings Data: Since 2018, there have been 166 million job openings detected.
  • Data Availability: Job openings data is available for 1.6 million websites.
  • Recent Trends: Last month, there were 5 million job openings, and over the past year, approximately 50 million job openings were recorded globally.
  • Active Job Openings: Currently, there are about 7 million active job openings uncovered by PredictLeads.

These statistics underscore the vast amount of data available to track AI adoption and its effects on the job market, providing investment firms with the necessary tools to make informed decisions.

💜How Blueprint Supercharges Sales with PredictLeads Data💜

Navigating the sales landscape with data isn’t just about collecting information – It’s about turning it into actionable insights. This is exactly what Blueprint has mastered using PredictLeads.

🤘Let’s dive into how they do it. 🤘

Data at Work: Real Insights, Real Growth

Blueprint uses PredictLeads to perform deep technographic scoring, analyzing data on 500 new technologies each week. This isn’t just about knowing what’s out there -> it’s about predicting market trends and identifying emerging competitors, providing a clear advantage in crafting timely and relevant sales pitches.

Jordan Crawford, the founder of Blueprint, puts it simply: “It’s not about having more data, but about having the right data that you can actually use.” This is where PredictLeads shines, offering depth with actionable insights.

Key Stats and Strategic Decisions

With PredictLeads, Blueprint isn’t just collecting data -they’re strategically deploying it.

Here’s how:

  • Job Openings Data: By analyzing the hiring trends of potential clients, Blueprint can pinpoint when companies are expanding and tailor their pitches to meet these growth phases.
  • Technology Adoptions: Tracking 636 million technology adoptions helps Blueprint stay ahead, suggesting when companies are likely to need their cutting-edge solutions.

A Relationship Built on Success

Blueprint’s partnership with PredictLeads goes beyond data. It’s about continuous support and collaboration, which Crawford describes as unparalleled. “PredictLeads always finds a way to make it happen,” he says, emphasizing the personalized support that helps Blueprint leverage data effectively.

For those eager to dive deeper into this use-case, you can check it out here.

If you have any questions, please don’t hesitate to reach out to us at: info@predictleads.com

We are here to help:)!

💜Stay Awesome💜
PredictLeads team

Understanding Pension Funds’ Strategic Shift to Private Markets with PredictLeads’ Data

As global pension funds like CalPERS increasingly redirect investments from public equities to private markets, the demand for precise, actionable insights grows significantly. This strategic transition, aimed at securing higher yields and reducing market volatility, is particularly highlighted by pension funds’ systematic moves towards assets like private equity and private debt.

The Role of PredictLeads’ Data in Navigating Private Markets

Job Openings Data:

PredictLeads’ Job Openings Data provides real-time insights into hiring trends directly from company websites, reflecting growth and expansion activities within specific sectors. An increase in recruitment, especially within sectors like private equity and private debt, often suggests robust sector health and promising profitability prospects. For pension funds diversifying their portfolios into these private markets, such insights are critical. They help align investment strategies with sectors that demonstrate strong growth potential, making this data invaluable for funds adjusting to the dynamic conditions of private markets. Additionally, pension funds can use this data to identify emerging industries or regions where new skills are in demand, providing an early indicator of economic shifts that could influence long-term investment decisions.

Business Connections dataset:

The Business Connections dataset from PredictLeads employs advanced image recognition to scan and categorize logos on company websites, unveiling key customer relationships often obscured in conventional financial reports. This dataset is especially valuable for pension funds engaging in scoring potential (startup) investments. Identifying major clients, particularly public companies, allows funds to assess a startup’s credibility and market traction. Companies with esteemed, stable clients can be scored higher, indicating lower risk and potentially higher reliability as investment opportunities. This insight is crucial for informed decision-making in public market investments.

Pension funds can leverage this data to assess the market reach and network strength of potential investments, ensuring a more comprehensive risk assessment and decision-making process. Furthermore, this dataset allows pension funds to monitor the customer base stability of current investments, providing ongoing risk management and insight into market position changes.

Broader Market Implications:

The shift of pension funds toward private markets not only reshapes their investment strategies but also influences broader market dynamics. By utilizing PredictLeads’ alternative data, such as Job Openings and Business Connections, pension funds can gain deeper insights into the risk and potential of their private market investments, which are crucial for informed decision-making in an environment where traditional metrics fall short. 

Moreover, this strategic use of alternative data helps pension funds anticipate market trends, adapt to economic changes, and identify investment opportunities early, maintaining a competitive edge in an increasingly complex financial landscape. Whether through pinpointing emerging sectors with job openings data or evaluating the robustness of potential investments with key customer analysis, these datasets provide critical insights that enhance and refine investment strategies.

Conclusion:

As the trend of pension funds moving towards private markets continues to grow, the importance of alternative data becomes increasingly central. Datasets like PredictLeads’ Job Openings and Business Connections dataset provide essential tools that enable large institutional investors to execute their strategies with greater precision and confidence. By leveraging these alternative data sources, pension funds can more effectively navigate the complexities of private markets, aligning their investment approaches with the most promising opportunities for sustainable returns.

Got questions? Don’t hesitate to reach out at info@predictleads.com!

Case Study: InReach Ventures & PredictLeads

InReach Ventures uses technology to help scale venture capital and make
investments in early stage startups throughout Europe. They built their own
proprietary software and developed a new model of investing to discover and invest in the most promising startups.

There’s a few major data challenges VC’s often face including data quality and the
time, effort and cost it takes to acquire or crawl data.

Here is a short interview with Ben Smith the Co-Founder / Partner / CTO of InReach Ventures and how PredictLeads company intelligence data helps InReach Ventures discover new companies and track growth signals for companies of interest.

How do you identify growing companies?

“InReach combines data from lots of different data sources. Some of that is around signals on how a company is performing like PredictLeads data, which helps us to find startups from all over Europe. This data, along with other types, allows us to look at how companies are growing, whether they’re growing their team, if they’re getting new customers or new business connections or partnering with different companies. “

PredictLeads

Are there any specifics on how PredictLeads data is being used?

“With job postings in particular, outside the general idea that a company is growing positively, it gives us an idea whether there is real substance behind a company. Seeing that a company has a product and engineering DNA and are looking to invest more in it is a positive.”

What challenges were you able to overcome with PredictLeads data?

“It’s all about how best we leverage our own product and engineering resources. Having the InReach team focus on what we’re good at and working with partners that are better than us in areas is an important point of leverage.”

Why did you decide to subscribe to PredictLeads data?

“PredictLeads helped us by doing some of the work that we had always planned but never been able to prioritise. Finding news events around a particular company and identifying company customers through logos/connections is really interesting for us and also it’s something that takes significant time and effort to get right.”

What’s your view on the VC industry using data and what are the biggest challenges on the horizon in the industry?

“The value of data, machine learning and a data driven approach to capital is an ever growing trend. The point of venture capital is to fund innovation and how much innovation is happening in venture capital in the past 10 years is very limited. I think there is a change now where data and software is being seen as a way for venture firms to innovate their model. The issue that traditional VC firms first face is that culturally at their core, they are not a technology firm but a professional services organisation. Where we think we have an advantage is that we started as a technology, product and engineering organisation, taking a very data driven approach to venture capital. That’s where we think we will long term hold the advantage because we started doing this earlier. Traditional venture capital will start to utilise data over time, but at their core they are not tech or engineering organisations. Short term, data and tech will play a broader role in terms of the whole industry using it as it’s becoming more and more of a buzz and as data is becoming more demanded.”

What are some of the trends in Venture Capital?

“My co-founder and Investment Partner Roberto layed out the the data trend in VC well in his blog post: The Full Stack Venture Capitalist

How do you see PredictLeads to help you achieve your long term goals?

“Two things PredictLeads does and will continue to do is that it helps us discover that a startup exists in the first place and then tells us whether there’s something interesting happening that we might want to talk to them about.”

Company intelligence data in your Sales enablement platform

You’re already aware that the more insights and data you have on your prospects, the better. Exactly how could you take advantage of this data and how could it be integrated into your sales enablement platform?

Sales enablement platforms are without a doubt incredibly valuable to sales teams. They have endless use cases as illustrated in the “SalesTech Landscape” below – such as engaging clients with smart messaging tools, improving productivity with easy to use sales resources, identifying leads and scoring them, and of course, the CRM that helps you stay on top of customers and prospects.

In the CRM, all the information you have on your customers should be tracked, which can be made manually by the SDR itself or automated using a 3rd party system. Data like company name, contact information and demographics is usually logged into the CRM and creates a long lead list of prospects. For sales teams to become successful they usually need more information than this. Here’s how sales intelligence like company intelligence data can enrich sales enablement platforms and improve the performance of SDRs using it:

Personalized Outreach

All SDRs have heard the importance of being personal. No prospect wants to listen to some robot pitching their idea without knowing a single thing about them, their company or understanding what value their product can give them.  

PredictLeads can provide insights to increase Personalization such as: 

  • News Events alerts like “Company X receives Y Award” can give you an icebreaker to open up the conversation by congratulating them and letting them know you did your homework. 
  • Key Customers data insights can help you identify if you and the customer share the same partners or clients to build familiarity and trust. 

Sales Triggers

Imagine you have this very long list of leads in your CRM. You start making phone calls from the top but cannot seem to move the deal forward even though you’re having great rapport with prospects. The most likely reason is you’re not reaching out to the right prospects, the ones that are in the buy mode. Companies are not always looking to invest in products for many reasons. Maybe they’re already satisfied with what they have, or they don’t  currently have the budget to invest in new software or the product that you’re selling. With sales triggers you can identify companies with signals indicative of growth – meaning the company is more likely to invest. 

Examples of Sales Triggers PredictLeads provide are: 

  • Company signs new client.
  • Company launches new product. 
  • Company received financing.
  • Company increases headcount. 
  • Company made a new integration. 
  • Company expands facilities.

Targeting Leads

When sourcing for leads, most CRMs provides search functions with filters that help you target the right prospects. With more company data you can advance these search filters to create a more targeted approach. The more filters you can use, the better you can target prospects matching your ideal target persona.

How PredictLeads data can be used as filters for Targeting: 

  • Technologies used in the company can help you identify prospects that are more likely to have an interest in buying your product. For example, if you’re selling a Salesforce extension product you’d want to target companies that are actually using Salesforce. 
  • Companies Hiring for X category, if you’re selling a Marketing automation product you can filter companies hiring for Marketing category as they’re more likely to have a need for your product. 

These are just a few examples on how company intelligence data can be integrated into your CRM or other sales enablement tools, and I’m sure there are hundreds more creative ways. One thing is for certain though – sales teams will benefit from using this data, because it’ll be doing all the research for them. This means that they can focus on what brings them most value – selling.

Fanny

« Older posts

© 2025 PredictLeads Blog

Theme by Anders NorenUp ↑