Category: Competitive Intelligence (Page 2 of 2)

AI Adoption and Sector Shifts Through Job Openings Data

July 9, 2024 /

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.

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. These systems 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. It helps 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. Meanwhile, 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. They can focus on high-growth sectors. Sectors such as AI development, advanced manufacturing, and healthcare innovation are likely to attract more investment. This is 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. It informs 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. However, 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. Meanwhile, smaller businesses are facing more challenges.

This chart helps visualize the employment dynamics and how different-sized businesses have been affected over the years. It provides 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. It enables better-informed investment decisions. Utilizing datasets like those from PredictLeads can provide the detailed, real-time insights needed to stay ahead of market shifts. This helps 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. 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. They provide investment firms with the necessary tools to make informed decisions.

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How Blueprint Supercharges Sales with PredictLeads Data

May 13, 2024 / / 0 Comments

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

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

May 10, 2024 / / 0 Comments

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. This shift underscores the role of platforms such as PredictLeads in providing vital data insights in the realm of pension funds private markets.

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!

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The Untold Story of Data Analytics in Boosting B2B Marketing

March 25, 2024 /

Data analytics B2B marketing PredictLeads is reshaping how companies engage customers in today’s digital landscape. With the rise of AI and big data, marketers no longer rely on guesswork — they leverage actionable insights from datasets like job openings to anticipate industry shifts, personalize campaigns, and drive higher engagement.

AI’s not just about making tasks easier – it’s about making marketing smarter!
Picture this: AI dives into job opening data and picks up on which industries are booming and what skills are in demand. This goldmine of info helps marketers craft campaigns that hit RIGHT WHERE THEY NEED TO.

The real magic of AI in marketing? Personalization. AI spots patterns in how users behave and what they like, so messages can be tailored just for them. No more spammy, one-size-fits-all ads. It’s all about sending the right message, to the right person, at the right time.

Predictive analytics is another ace up AI’s sleeve. By looking at trends, like which job sectors are heating up, AI can predict where the market’s headed. This means businesses can adjust their strategies on the fly, staying ahead of the curve instead of playing catch-up.

But, it’s not all smooth sailing. With great data comes great responsibility. Issues like data privacy and ethical AI use are “kinda” big. Plus, the success of AI-driven marketing hinges on the data’s quality.

In a nutshell, as AI tech evolves, its role in marketing only gets juicier. It’s all about digging into data-driven insights and riding the wave of personalized marketing. But, it’s crucial to play it smart and ethical. Get it right, and AI won’t just be a tool
>> it’ll be your competitive edge in nailing customer engagement.<<

At the World Economic Forum’s Growth Summit, economist Richard Baldwin made a great point: “AI won’t take your job IF YOU KNOW HOW TO USE IT.” Add some Good Data into the equation, and you’re golden. 🥇

Interested in seeing how PredictLeads’ Job Openings datasets can revolutionize your marketing and sales? We’d love to chat!

Reach out at info@predictleads.com for more info. 💜

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Case Study: InReach Ventures & PredictLeads

October 12, 2021 /

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

There’s a few major data challenges VC’s often face. These include 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. It explains how PredictLeads company intelligence data helps InReach Ventures. This assists them in discovering new companies and tracking 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. This helps us to find startups from all over Europe. This data, along with other types, allows us to look at how companies are growing. We can see whether they’re growing their team, getting new customers, or forming new business connections. In addition, we see if they’re partnering with different companies. “

PredictLeads
Venture capital growth driven by PredictLeads data

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. It involves the InReach team focusing on what we’re good at. Meanwhile, we work with partners that are better than us in certain areas. This 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. However, we had never been able to prioritize it. They assist in finding news events around a particular company. Identifying company customers through logos/connections is really interesting for us. And, 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. However, how much innovation is happening in venture capital in the past 10 years is very limited. I think there is a change now. Data and software are being seen as a way for venture firms to innovate their model.

The issue that traditional VC firms first face is cultural. At their core, they are not a technology firm but a professional services organization. Where we think we have an advantage is that we started as a technology, product, and engineering organization. Thus, we take a very data-driven approach to venture capital. That’s where we think we will long term hold the advantage.

We started doing this earlier. Traditional venture capital will start to utilize data over time, but they are not tech or engineering organizations at their core. Short term, data and tech will play a broader role. This occurs as the whole industry starts using them. It’s becoming more of a buzz as data demand increases.”

What are some of the trends in Venture Capital?

“My co-founder and Investment Partner Roberto laid out 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 help us discover that a startup exists in the first place. Then it tells us whether there’s something interesting happening that we might want to talk to them about.”

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Company Intelligence Data in Your Sales Enablement Platform

January 25, 2021 /

Sales enablement platforms are only as powerful as the data that fuels them. The more context and insights you have on prospects, the better your chances of engaging the right buyers, at the right time, with the right message.

But here’s the challenge: most CRMs still rely heavily on static lead lists. Company name, contact info, and a few demographics are entered manually or pulled from third-party systems. That’s useful, but it’s not enough to win competitive B2B deals.

What separates good sales teams from great ones is company intelligence data — fresh, dynamic signals that reveal when a prospect is in buying mode, which technologies they use, and how their business is evolving.

Why Sales Enablement Platforms Need Enrichment

Modern sales enablement tools already cover a wide range of use cases — from client engagement and messaging to productivity workflows, lead scoring, and customer relationship management (CRM). But without enriched intelligence, they leave SDRs guessing.

Integrating real-time company data into these platforms transforms them into proactive sales engines, helping teams:

  • Personalize outreach with timely insights
  • Spot and act on sales triggers faster
  • Target accounts that fit their ICP with precision

Let’s break down how.

Personalized Outreach: Relevance That Resonates

Every SDR knows personalization is key. Yet most outreach still feels generic. Why? Because teams lack the depth of data needed to connect with prospects on a meaningful level.

How PredictLeads helps:

  • News Events: Alerts like “Company X receives Y award” or “Company Z expands into Europe” give SDRs instant conversation starters. Congratulate them, show awareness, and stand out.
  • Key Customer Data: Identify shared partners, vendors, or clients to build credibility and trust from the first touchpoint.

This is personalization powered by intelligence — not guesswork.

Sales Triggers: Spotting Buying Intent Early

A long list of leads is useless if none of them are ready to buy. Companies don’t purchase continuously; timing is everything. That’s where sales triggers come in.

Signals PredictLeads surfaces:

  • Signing new clients (expansion momentum)
  • Launching new products (budget reallocation)
  • Receiving fresh financing (capital to invest)
  • Rapid headcount growth (new tools needed)
  • New integrations (ecosystem alignment)
  • Facility expansions (scaling operations)

These triggers highlight when a company is in growth mode — and therefore more likely to invest. SDRs can focus energy where deals are most likely to close.

Targeting Leads: Going Beyond Firmographics

Most CRMs allow basic filtering by industry, location, or company size. Useful, but blunt. Company intelligence data takes targeting to the next level.

How PredictLeads data improves targeting:

  • Technology Stack Detection: Selling a Salesforce extension? Filter only for companies actually using Salesforce.
  • Hiring Signals: Pitching a marketing automation tool? Target companies currently hiring marketing roles — clear evidence of a growing need.

The result is a more surgical approach to building lead lists, ensuring SDRs spend time on accounts that actually match their ICP.

The Bottom Line

Static data can only take sales teams so far. To stand out in today’s crowded B2B landscape, sales enablement platforms must be powered by real-time company intelligence data.

With PredictLeads, SDRs no longer waste hours on research or cold leads. Instead, they get actionable insights, sharpen their targeting, and spend more time on what matters most — selling.

Because the best sales strategy isn’t just about more leads.
It’s about the right leads, at the right time, with the right context.

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Hiring Intent Data During the Pandemic: What the Numbers Reveal

May 28, 2020 /

At PredictLeads, we analyzed hiring intent data for 5,000 US-based companies across multiple sectors to understand how the pandemic reshaped workforce demand. Our goal: to see how hiring intent correlated with the economic consequences of Covid-19.

By March 19, 2020, the first US states had entered lockdown. Within a month, more than 90% of the US population was under some form of restriction. This unprecedented pause in business activity left a visible mark on job openings across industries.

Below, we highlight how three sectors—Information Technology, Consumer Discretionary, and Industrials—were affected during this period.

Information Technology: From Growth to Contraction

Our hiring intent data shows a sharp decline in IT job openings starting March 25, 2020, when nearly 20,000 positions were slashed in a single day.

  • March: The US unemployment rate rose from 3.8% to 4.5%. In the IT sector, job openings fell by 6.8%, with 47,000 listings removed in the final week of the month alone.
  • April: Unemployment skyrocketed to 14.4%, coinciding with an additional 70,000 IT job openings withdrawn—a 12.8% monthly drop.
  • May: Another 51,000 openings disappeared between May 1–28. If job listings correlated directly with unemployment, this trend suggested a further rise to nearly 21% unemployment by month’s end.

By late May, IT hiring intent had decreased by 10.1% compared to pre-lockdown levels.

Industries included: software & services, computer hardware, IT services.

Consumer Discretionary: Non-Essentials Hit Hard

The Consumer Discretionary sector—covering leisure products, entertainment, restaurants, and non-essential retail—experienced similar declines.

As lockdowns spread, demand for non-essential goods and services plummeted. Our hiring intent data showed clear contraction, with companies scaling back recruitment or freezing headcount entirely.

Industrials: Construction & Manufacturing Slowdown

The Industrials sector, encompassing companies producing finished goods for construction and manufacturing, also saw sharp drops in job listings.

Factory closures, supply chain disruptions, and uncertainty around demand caused many businesses to reduce or suspend hiring, further compounding economic strain.

Why Hiring Intent Data Matters

The pandemic highlighted just how valuable hiring intent data can be in understanding broader market shifts:

  • Leading indicator of economic health: Job postings often decline before official unemployment numbers rise.
  • Sector-specific insights: Not all industries react equally—tracking hiring intent helps pinpoint where growth or contraction is happening first.
  • Strategic decisions: For sales, recruiting, and investment teams, knowing where companies are still hiring versus cutting back provides a competitive advantage.

Conclusion

Covid-19 created one of the fastest and deepest shocks to hiring intent data in modern history. IT, Consumer Discretionary, and Industrials all saw major declines as businesses adapted to uncertainty and lockdown measures.

For companies, analysts, and investors, monitoring hiring intent signals provides a forward-looking view into market resilience—or vulnerability.

👉 If you’d like to explore more detailed hiring datasets, check out our PredictLeads APIs or reach out at sales@predictleads.com

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Introducing Key Customer Data

April 16, 2020 /

Introducing PredictLeads’ Key Customer Data API

PredictLeads is excited to announce the launch of Key Customer Data, our newest dataset designed to give sales, marketing, and investment teams unprecedented insight into a company’s ecosystem of relationships.

With this addition, PredictLeads now offers four core datasets:

  • News Events – real-time monitoring of company activity and mentions
  • Hiring Intent – job postings and recruitment signals to reveal growth plans
  • Technologies – up-to-date technology stacks powering companies
  • Key Customer Data – detailed insights into customers, partners, sponsors, vendors, investors, and more

What Is Key Customer Data?

As the name suggests, Key Customer Data identifies who a company is doing business with. This includes:

  • Customers and clients
  • Strategic partners and sponsors
  • Vendors and suppliers
  • Investors and portfolio companies

We extract this information from multiple trusted sources, such as:

  • Case study pages and client success stories
  • Testimonial and “Our Customers” sections on websites

To go even further, we use image recognition technology to connect logos found on websites to the correct company domain. This ensures accuracy and enables you to quickly map out real customer relationships.

Why Company Data Such As Key Customers Matters

Key Customer Data helps answer questions like:

  • Which companies are using my competitor’s product?
  • Who are the top sponsors or partners of a given business?
  • What vendors or suppliers does a target company rely on?
  • Which portfolio companies does a VC firm back?

With this intelligence, teams can:

  • Generate higher-quality leads by targeting companies with proven buying signals
  • Refine account-based marketing (ABM) strategies with more context on relationships
  • Support competitive intelligence by tracking who is working with whom
  • Accelerate partnership development by identifying relevant ecosystems

Clean, Developer-Friendly APIs

Like our other endpoints, Key Customer Data is delivered through clean, modern APIs following the JSON:API specification.

You can also access the data via:

  • Flat Files – ideal for bulk delivery
  • Webhooks – for real-time updates and integrations

Our APIs are designed for easy integration into CRMs, sales intelligence platforms, and data workflows, making it simple to enrich company profiles and enhance decision-making.

Getting Started

Ready to explore the new dataset? Getting started is simple:

  1. Sign up here: https://predictleads.com/sign_up
  2. Access your API key directly in your account settings
  3. Explore the documentation for Key Customer Data here: https://predictleads.com/docs/#connections

For further details or custom requirements, contact us at sales@predictleads.com and our team will be happy to help.

Final Thoughts

At PredictLeads, we believe the future of B2B sales and marketing lies in data-driven decision-making. With the addition of Key Customer Data to our product suite, companies can now unlock a clearer, more accurate picture of business relationships worldwide.

Start enriching your workflows today and discover how Key Customer Data can give your team the competitive edge.

Cheers,
PredictLeads Team

Finding Top-Performing Companies with PredictLeads

October 1, 2018 /

At PredictLeads, we work with some of the most data-driven teams — from venture capitalists (VCs) and corporate VCs to sales professionals and innovation departments.

Our mission is clear: provide company intelligence data that helps teams both enrich known companies and discover up-and-coming challengers so they never miss a market shift.

Enrich Known Companies to Score and Prioritize

For established companies in your pipeline, the goal is to access data that reveals true company performance.

PredictLeads currently tracks and provides:

  • Hiring Intent – uncover which companies are actively expanding.
  • News Events – funding rounds, partnerships, acquisitions, and more.
  • Business Connections – hidden customer, partner, and vendor relationships.
  • Technographics – technology adoption and usage signals.

👉 All datasets are available via clean APIs: PredictLeads Enrich API.

By enriching known companies, VCs and sales teams can score prospects, prioritize effectively, and focus resources where they matter most.

Discover Challengers Before Competitors Do

The second goal is to spot new and fast-growing challengers. These are companies that are just starting to show expansion signals.

Examples include:

  • Hiring via platforms like Hacker News.
  • Expanding offices into new geographies.
  • Receiving industry awards.
  • Signing new high-value clients.

👉 Explore these through our Discover Endpoints.

By identifying these companies early, you can get ahead of competitors, build relationships sooner, and align with future winners.

The Challenge of Predicting Performance

Clients often want to predict how well a company will perform in the future. This is no easy task. To get there, you need:

  1. Accurate and complete data.
  2. Enough historical data points to train reliable models.

PredictLeads tracks over 17 million companies and offers performance data from 2015 onwards. Still, the journey requires patience:

  • Startups often need 5+ years to succeed or exit.
  • VCs and CVCs must validate their models over these long timeframes.
  • Training models on past company trajectories is possible, but missing data points often limit accuracy.

It’s a long-haul game. But history shows that teams with more knowledge, more data, and deeper insights consistently outperform those without. That’s why we’re confident our efforts — and the data we provide — will deliver results for our partners

Conclusion: Patience + Data = Performance

At PredictLeads, we know predicting company success takes time. But with the right data, enriched insights, and early discovery of challengers, you can make smarter bets and stay ahead of market shifts.

📩 Interested in learning how PredictLeads can help your organization find top-performing companies?
Get in touch via our contact form.

Looking forward,
Roq

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