Category: Case Study (Page 1 of 2)

How AI Agents Use the News Events Dataset to Power Smarter Sales

September 11, 2025 / Robert Fon

There’s a lot of talk about AI agents right now. Some see AI agents powered by News Events dataset as futuristic assistants, others as overhyped chatbots in disguise. The truth lies somewhere in between: AI agents are becoming practical tools for sales teams, and what makes them useful isn’t just the AI itself — it’s the data feeding them.

AI agents powered by News Events dataset are utilizing the News Events dataset effectively. One dataset that’s proving especially powerful here is the News Events dataset.

Every headline hides an opportunity — the key is knowing which ones matter.

Why AI Agents Need Real-Time Signals

An AI agent without fresh data is basically a parrot. It can mimic patterns, but it won’t know when your prospect just raised a Series B, or when your competitor opened a new office in London. That’s where the PredictLeads News Events dataset steps in.

Since 2016, it has processed millions of blogs, press releases, and articles, surfacing structured signals like:

A company receives financing
A new executive hire or departure
A competitor launches a product
A business expands into a new region

Instead of raw news headlines, the dataset gives AI agents clean, categorized events they can instantly understand and act on. This makes them excellent AI agents powered by News Events dataset.

Turning Events Into Action

Here’s how it looks in practice:

Prospecting agent: While scanning a target account list, the agent notices that “Company X just signed a new client in your industry.” Instead of sending a generic email, it drafts a message that congratulates them and positions your product as the next logical step.
Account monitoring agent: Your AI checks daily for news about top accounts. It flags that a CEO has stepped down at one company, suggesting you re-engage before new leadership sets a different direction.
Competitive intelligence agent: While tracking your market, it picks up that a competitor “is developing” a new feature. That becomes part of your next strategy meeting, long before it makes it into glossy press releases.

The dataset doesn’t just enrich records in your CRM — it gives AI agents powered by News Events dataset the awareness they need to behave less like scripts and more like actual teammates.

Why Structure Matters

The power here isn’t only in freshness, it’s in structure. AI agents thrive on clarity. If a news article says, “Rumors suggest the company might launch a new product later this year,” the dataset captures that nuance as planning = true, rather than treating it as a confirmed launch.

That kind of detail is the difference between an AI agent that spams prospects with irrelevant updates and one that reaches out with credibility.

The Bigger Picture

AI agents powered by News Events dataset are quickly moving from novelty to necessity in sales. But what separates the helpful ones from the noise is data quality. The News Events dataset acts like a stream of real-time situational awareness, allowing AI to spot openings humans might miss — and do it at scale.

In a sense, it gives AI agents something they usually lack: context. And in sales, context is everything.

Final Thought

If the last decade was about building bigger CRMs and larger lead lists, this one will be about equipping AI agents with the right signals. The News Events dataset is one of those signals — turning headlines into structured intelligence that AI can understand, prioritize, and act on. Therefore, AI agents powered by News Events dataset are becoming indispensable tools in modern sales strategies.

Because at the end of the day, the future of sales isn’t just AI for the sake of AI. It’s AI that knows when the moment is right.

Interested in our API Docs? Feel free to find them “here“.

How AI Sales Agents Are Transforming B2B Prospecting and How PredictLeads Steps In

How PredictLeads Company Data powers modern Sales Intelligence & Data Enrichment

Company Intelligence Data in Your Sales Enablement Platform

What Summer BBQs Can Teach Us About Reading B2B Buying Signals

July 15, 2025 / Robert Fon

It’s a Saturday in mid-July and you’ve been invited to four different BBQs.

You’re walking through a quiet suburban neighborhood, sunglasses on, sandals flapping. The sun is relentless, the scent of grilled meat hangs in the air… and you’re on a mission. 🥩🧑‍🍳

The first house?
You catch a whiff of burnt tofu and hear someone ask if the kombucha is homemade.

Hard pass.

You keep moving.

A few steps down, you hear music (real music) and spot a lineup of Ford Raptors and a 96 Chefy parked out front. There’s laughter behind a wooden fence, and you catch sight of a green ceramic grill puffing steady smoke, with a line forming around the buffet table.

You don’t need to ask for a menu.
You already know:

This is the one worth joining.

You skip the silent lawns and low-energy gatherings and you:
1. Read the signals.
2. Follow the smoke.
3. Choose wisely.

🎯 In B2B Sales and Investing, the Same Rules Apply

Some companies signal quality before you even step in the door.
Their websites, partners, and public presence give off subtle (and measurable) signs:

Logos of well-known brands appear on their sites.
Integrations and partnerships get highlighted.
Case studies and testimonials drop recognizable names.
All of it is smoke – but in this case, smoke that matters.

It’s all smoke! But in this case – it means something.

In B2B such smoke isn’t always obvious. That’s why we built the Connections Dataset at PredictLeads – to read the grill smoke signals at scale.

🔍 Why Logos Matter and Why They’re Hard to Track

To gain credibility, B2B startups often put logos of companies they work with directly on their websites. These show up under sections like:

“Our Customers”
“Trusted by”
“Partners”
“Who we work with”
Testimonials or Case Study pages

The challenge?
Most of these logos are not backlinked. There’s no easy text trail or hyperlink to follow. A Google search won’t help. Scraping doesn’t cut it.

So we built something smarter.

Logo Recognition Meets Entity Mapping

Our system uses image recognition to detect logos on company websites. Then we match those logos to verified domain names and legal entities.

This enables us to connect:

Which company is claiming a relationship
Who the other party is (vendor, partner, customer, etc.)
Where and how that connection is represented

We don’t just scan the homepage. We parse through case study sections, customer lists, footers, header navs, press pages (anywhere companies hint at collaboration).

Each relationship is then categorized:

“vendor” → “Company A is a vendor to Company B”
“partner” → “Company A collaborates with Company B”
“integration” → “Company A integrates with Company B”
“investor”, “published_in”, “parent”, “rebranding” (and more)

We even timestamp when we first and last saw the connection. That means you can prioritize based on recency and relationship type.

🧾 Example: Invoicy → Salesforce

Let’s say a small fintech startup called Invoicy includes a line on their “Customers” page that says:

“Trusted by finance teams at companies like Salesforce, Rippling, and Brex.”

There are no backlinks. Just static logos and a sentence tucked beneath a testimonial.

Our system scans the page, detects the Salesforce logo, maps it to the domain salesforce.com, and parses the surrounding text.

The language >“trusted by finance teams”< suggests that Invoicy is a vendor to Salesforce, likely providing tooling for invoicing, reconciliation, or internal financial workflows.

That gets recorded as:

category: “vendor”
source_url: the exact URL of the “Customers” page
first_seen_at: when the connection was first detected
last_seen_at: when it was last confirmed

For a company like Invoicy, being able to show they’re used by a giant like Salesforce is a huge trust signal and even more so when made searchable and machine-readable.

Now sales teams, investors, and analysts can factor that credibility directly into targeting models, scoring frameworks, or due diligence … without ever scraping a webpage by hand.

🔥 What This Means for You

For GTM teams:
Use vendor and partner relationships to qualify and prioritize leads.
If your ICP already sells to Snowflake, Notion, or Google – that’s your BBQ. Bring your best pitch.

For investors:
Track which startups are gaining traction with known buyers.
Logos and partnerships are sometimes more honest than press releases.

For growth teams:
Score accounts based on who trusts them.
If they’ve passed another company’s procurement process, they’re likely enterprise-ready.

🛠️ The Grill is Hot so Start Reading the Signals!

You wouldn’t walk into a BBQ blind. You look for smoke, listen for music, and trust the signs.

The same goes for B2B:

Who they work with tells you who they are.

And PredictLeads helps you see that across millions of companies in real time.

Want a quick walkthrough or test run of the Connections Dataset?
Explore the PredictLeads API

Use Data Enrichment to Filter and Prioritize Prospects

Overcome Market Challenges by Leveraging Investor Networks 🤔

How PredictLeads Company Data powers modern Sales Intelligence & Data Enrichment

US-China Tariffs and Shopify Adoption: Signals to Watch

April 9, 2025 / Robert Fon

Trade tensions between the US and China are once again front and center — and this time, the numbers are steep, affecting hiring signals in various sectors.

China’s finance ministry has announced an 84% tariff on all goods imported from the US.
In response, the US has implemented a 104% tariff on all Chinese goods, which officially took effect today, Wednesday, April 9.

While it remains to be seen whether a last-minute deal will be struck, if these tariffs go into effect as planned, they are expected to introduce significant friction into global ecommerce, logistics, and retail operations, influencing hiring signals in these industries.

At PredictLeads, we’re looking into how this situation might influence two key areas where strategic shifts often show up first:

Hiring signals across ecommerce and logistics
Technology adoption patterns, particularly around Shopify

Shopify: A platform exposed to global flows

Shopify plays a central role in enabling international ecommerce expansion. It’s widely used by brands that rely on cross-border fulfillment and Chinese manufacturing, making it particularly exposed to the effects of rising tariffs, which also affects hiring signals for roles related to Shopify and ecommerce.

If the new trade restrictions take hold:

Some sellers may pause or delay global expansion efforts.
Others might shift their infrastructure strategy toward more localized platforms or hybrid solutions.
We may see slowed adoption of Shopify among brands operating from or targeting heavily affected markets.

Together with our partners in the market intelligence space, we’re keeping a close eye on the data — particularly around Shopify adoption trends and ecommerce tech stack changes — to better understand how and where these shifts might emerge.

It’s still early, but this is the moment to start watching for new hiring signals.

Hiring signals: A directional early warning

Job data has historically been one of the earliest and most reliable indicators of how companies react to market disruption, often seen in hiring signals.

Over the next several weeks, we’ll be tracking:

New job postings that mention Shopify, global logistics, or cross-border ecommerce
Changes in hiring behavior tied to international expansion roles
Increased focus on domestic operations, regional warehousing and job creations, and supply chain resilience

These subtle shifts in hiring priorities can offer a first glimpse into how companies are adjusting their ecommerce strategies in response to the tariffs.

For market intelligence teams: where to focus

Whether you’re analyzing ecommerce growth, tracking tech adoption, or assessing exposure to global supply chain risk, now is the time to monitor alternative data sources more closely for new signals related to hiring.

We recommend focusing on:

Tech stack detections — to identify the adoption slowdown at platforms like Shopify
Hiring data — to spot where expansion plans are being paused or redirected due to new hiring signals
Regional trends — to see whether companies begin shifting focus toward LATAM, Southeast Asia, or domestic-only models

These early indicators can inform broader trend analysis well before public earnings or analyst reports reveal the full picture.

Stay ahead of the shift

As of April 9, the tariffs are now in effect — and unless there’s a breakthrough soon, the ripple effects across global trade could intensify, signaling new hiring patterns.

If you’re preparing internal research, building trend reports, or want a deeper look into Shopify adoption and ecommerce hiring trends in this context, feel free to reach out. We’re happy to share additional cuts of the data or collaborate on deeper analysis.

This is a developing story, and the signals are just starting to surface.

How Hiring & Tech B2B Sales Signals Help Close More B2B Deals?

AI Adoption and Sector Shifts Through Job Openings Data

Leveraging Hiring Intent

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

February 21, 2025 / Robert Fon

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

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

How Experts Are Using PredictLeads data for sales outreach

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

📌 Job Openings as a Sales Trigger

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

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

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

📌 Technographic Data for Smarter Targeting

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

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

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

📌 Combining Multiple Signals for High-Intent Outreach

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

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

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

📊 Why PredictLeads Data Gives You an Edge

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

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

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

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

THANK YOU! 🙏 💜

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

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

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

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

January 6, 2025 / Robert Fon

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

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

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

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

The Shifting Landscape of Supply Chains

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

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

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

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

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

The crisis highlights broader challenges:

Labor Shifts
VW subsidiary Audi plans to halt EV production at its Belgium plant, affecting 3,000 jobs. German automakers have collectively shed 46,000 jobs since 2019, with more to come.
Technology Gaps
As competitors like Tesla dominate EV sales globally, VW’s slower adoption of cutting-edge EV technologies has been costly.
- Worthy mention is also BYD… But lets stick for cars that can actually steer 😬.

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.

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). 🌮
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.
Evaluate Supplier Resilience
Job postings reveal supplier priorities. Companies hiring sustainability officers likely align with green initiatives, while those focused on automation are investing in efficiency.

Example: Semiconductor Shortages

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

The Advantage

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

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

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

Conclusion: Turning Job Data into Strategy

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

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

Questions? PredictLeads is here to help! 🙂

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