Category: Uncategorized (Page 2 of 3)

Why Companies Rely on PredictLeads Data for Accuracy Instead of LLMs

Large Language Models (LLMs) are great at generating text, but when it comes to sourcing accurate, complete, and scalable company data for sales, they fall short. That’s why leading sales teams, investment firms, and go-to-market platforms rely on PredictLeads for reliable company data. When comparing PredictLeads company data vs LLMs, PredictLeads clearly outperforms in accuracy and completeness. Therefore, the debate around PredictLeads company data vs LLMs tends to favor PredictLeads for its precision.

We provide verified, structured, and instantly available datasets that make LLMs more powerful — instead of trying (and often failing) to have them collect the raw data themselves.

Here’s why the choice of PredictLeads company data vs LLMs can impact your workflow’s effectiveness:

1. Accuracy You Can Trust

Companies choose PredictLeads because our data is factual and verified at the source. LLMs, when tasked with crawling and extracting data, can misinterpret, skip over important details, or even hallucinate results. PredictLeads ensures your workflows run on solid, reliable inputs by leveraging detailed PredictLeads company data.

2. Complete Data, Not Just a Subset

LLMs often capture only fragments of information. For example, Tesla is hiring for 4,100+ positions right now. An LLM may return just a few dozen roles — sometimes only 3% of the total. That means missing critical senior or C-level positions that reveal Tesla’s strategy.

With PredictLeads, you get the entire dataset upfront and can filter for the insights that matter most, emphasizing the advantage of company data vs LLMs.

3. Breadth of Sources Beyond the Obvious

LLMs are limited to surface-level results, typically pulling from a company’s own website. PredictLeads scans across 100+ million company websites, surfacing signals like:

  • Case studies companies publish with partners
  • Emerging hiring trends
  • Strategic announcements beyond the press releases

For instance, while an LLM might only capture what NVIDIA says about itself, PredictLeads uncovers what other companies are saying about working with NVIDIA — a much broader and more valuable picture, highlighting the advantage of choosing PredictLeads company data over LLMs.

4. Instant Results, No Waiting Around

When speed matters, PredictLeads delivers. LLMs can take over a minute to fetch and process all open roles or case studies for a company. That’s a non-starter for busy sales reps or analysts.

PredictLeads data is already structured and available via flat file exports or integrations. Queries return results in milliseconds — fueling workflows without delay, proving efficiency in the PredictLeads company data vs LLMs comparison.

5. Built to Fit LLM Workflows

Even the best LLMs struggle with large amounts of raw data. A single case study might run 15,000+ characters. Feeding an LLM dozens at once causes context window overload and hallucinations.

PredictLeads provides concise summaries (~300 characters) of case studies, partnerships, and events. This means your LLM agents can handle more inputs, connect dots faster, and produce more accurate insights, making the company data vs LLMs discussion lean towards PredictLeads.

6. Beyond Enrichment in Clay

Our data is available in Clay if you already know which company domains you want to enrich. But most companies rely on us directly because we provide:

  • The full dataset of some 100M+ companies (including ones you haven’t identified yet)
  • Historical exports to track changes over time
  • Additional fields like timestamps and confidence scores not included in Clay

This makes PredictLeads not just an enrichment tool — but a data foundation for growth and investment strategies, illustrating the importance of selecting PredictLeads company data vs LLMs.

Why Companies Rely on PredictLeads company data

At the end of the day, companies don’t want their LLMs wasting time and compute on incomplete or unreliable data gathering. They want their LLMs focused on analysis, insights, and execution.

That’s why they rely on PredictLeads — to provide structured, factual, and scalable datasets that make LLMs (and the teams using them) perform at their best. Thus, the effectiveness of PredictLeads company data vs LLMs is evident in their performance.

Interested in exploring how PredictLeads can fit your workflow? Let’s set up a quick call.

Interested in our docs? Here they are:)!

Large Language Models (LLMs): Powerful for generating insights, but not built for sourcing accurate and complete company data.

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

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

The First Data-Driven VC Hackathon

Last week, we were proud to sponsor the Data-Driven VC Hackathon, co-organized by Red River West and BivwAk! by BNP Paribas in the heart of Paris 🇫🇷.  Over two action-packed days, 80 participants – including developers, data scientists, and VC professionals – came together to tackle one ambitious goal: revolutionizing how venture capitalists make decisions with the power of data. This foundation in Paris will pave the way for the Data-Driven VC Hackathon Paris 2025 event.

Why This Hackathon Matters

The VC industry has long been due for innovation in how data is leveraged. While traditional methods have their place, the hackathon demonstrated that by combining cutting-edge tools, open-source collaboration, and diverse talent, we can push the boundaries of what’s possible. The event offered participants exclusive access to APIs from tier-one data providers. These included PredictLeads, People Data Labs, Similarweb, and Harmonic. This empowered them to bring their most creative ideas to life. Furthermore, the upcoming 2025 hackathon in Paris is expected to build on these innovations in anticipation of the Data-Driven VC Hackathon Paris.

The Winning Project: Pulse

The first-place project, Pulse, blew the jury away with its dynamic, data-driven approach to market segmentation. Built on enriched textual data from sources like PredictLeads, Pulse uses NLP-powered clustering to segment companies into evolving markets. The tool doesn’t just map existing trends but it also visualizes how markets evolve in real-time, offering an extreme level of granularity. This capability has the potential to change how VCs identify opportunities and allocate resources, a key focus for future Data-Driven VC events including those planned for Paris in 2025.

What Made This Event Unique

  • Diverse Participation: Teams were composed of coders, data scientists, and VCs from across Europe, creating an ecosystem of expertise and perspectives.
  • Real-World Impact: The projects weren’t just ideas but functional prototypes published under an open-source MIT license. This ensures the broader VC community can build on the innovations from the event. 🛜
  • VC-Specific Tools: From automated market trend analysis to productivity-enhancing tools for VC workflows, the projects tackled real challenges faced by investors every day. The aim is for Data-Driven VC Hackathon Paris 2025 to further this mission.

PredictLeads’ Role

As a sponsor, PredictLeads provided participants with access to our comprehensive company intelligence datasets, enabling them to work with real-world data. The winners used our insights to identify market shifts, analyze startup activities, and create actionable intelligence. Our mission has always been to make it easier for decision-makers to stay ahead of the curve. This event was a perfect opportunity to showcase how our data can empower innovation, especially looking towards 2025’s Data-Driven VC Hackathon in Paris.

Looking Ahead

The energy at BivwAk! was contagious, and it’s clear that this hackathon is just the beginning. As projects like Pulse continue to evolve, they could become the foundation for new startups. They may transform tools for VCs. The open-source nature of the event ensures that these innovations are accessible to all, fostering collaboration across the industry. This is crucial for future Data-Driven VC events in Paris, especially as we approach 2025.

To the organizers, mentors, and sponsors: thank you for making this event a resounding success. And to the participants: your creativity and dedication were inspiring. We can’t wait to see where this journey leads.

Stay tuned for updates and feel free to explore the winning projects on GitHub. Let’s keep innovating together!

Overcome Market Challenges by Leveraging Investor Networks 🤔

In today’s highly competitive market, leveraging investor networks for business growth can be a key strategy for companies offering innovative solutions that often face significant challenges in scaling their businesses. Despite having a great product or service, many companies struggle to:

  • Break into new markets: Identifying and engaging with potential customers in new sectors or geographies can be daunting.
  • Build trust quickly: Establishing credibility with prospects, especially in B2B markets, can take considerable time and effort.
  • Stand out among competitors: Differentiating from competitors in crowded markets is increasingly difficult.
  • Access the right networks: Many companies lack the connections necessary to open doors to high-value prospects or strategic partners.

These challenges can slow down growth and make it harder for companies to reach their full potential, even when they have strong products and a clear value proposition.

How Investors Can Step In: Leveraging Investment Networks

This is where your investors can play a pivotal role. Many venture capital firms, such as Sequoia Capital, Andreessen, and Insight Partners, have extensive networks that go beyond mere financial backing. These investors have invested in a diverse portfolio of companies, creating a network of businesses that can be leveraged to accelerate your growth. Here’s how:

Leveraging Investor Introductions

Your investors can facilitate introductions to other companies within their portfolio. These introductions can be invaluable, providing you with direct access to potential customers, partners, or even key industry influencers.

  • Example: If your company is backed by Sequoia Capital, they can introduce you to other companies in their portfolio that could benefit from your product. This not only opens the door to new business opportunities but also provides a trusted endorsement that can significantly shorten the sales cycle.

Proactive Outreach Using Shared Investment as a Connection Point

Rather than relying solely on investor introductions, you can take a proactive approach. While a shared investor relationship helps establish credibility, it’s important to highlight why your outreach makes sense for the recipient. A tailored message that emphasizes a logical fit between your offering and their current needs will go much further.

  • Example: If GV (formerly Google Ventures) has invested in both your company and Verve Therapeutics, you could reach out to Verve Therapeutics with a message like:

“Hi Mike,Saw we’re both fellow GV portfolio companies and that you’re hiring heavily for your Marketing department. We provide [x marketing software], and thought we should chat to see if we can support your efforts.”

The focus here isn’t just on the shared investor, but on how your product could address their specific needs – in this case, scaling their marketing team. This not only builds instant credibility but also offers a clear, relevant reason for them to engage in a conversation.

Additional Use Cases: Uncovering Broader Business Relationships

The value of your investor’s network extends beyond just portfolio companies. The dataset also uncovers other crucial business relationships such as partners, vendors, sponsors, and more. These connections can be leveraged in various ways:

  • Identifying Strategic Partners: Discover companies that share common partners with your business, opening up possibilities for joint ventures, collaborations, or technology integrations.
  • Vendor Optimization: Uncover potential vendors within your investor’s portfolio or those of their partners, enabling you to streamline your supply chain or access better resources.
  • Sponsorship Opportunities: If your investor has connections with companies that are looking for sponsorship opportunities, this data can help you identify potential sponsors who align with your brand.

Mentioned Companies

The investment companies and some of their notable recent investments include:

Conclusion: The Power of Strategic Network Utilization

By strategically utilizing the investment network data, your company can overcome the common challenges of breaking into new markets, building trust, and accessing the right networks. Whether through facilitated introductions by your investors or proactive outreach, the shared investment relationship serves as a powerful tool for building trust and opening doors. Additionally, by exploring connections such as partners, vendors, and sponsors, you can further optimize your business operations and discover new growth opportunities.

Would you be interested in utilizing this data in platforms to supercharge your sales outreach and lead generation strategies? You can find the full report and more details here.

Introducing PredictLeads’ New Technology Detection API Endpoint

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:

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:

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!

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