Tag: track companies (Page 3 of 3)

US-China Tariffs and Shopify Adoption: Signals to Watch

April 9, 2025 /

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.

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

January 6, 2025 /

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

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

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

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

The Shifting Landscape of Supply Chains

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

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

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

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

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

The crisis highlights broader challenges:

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

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

Supply Chain Insights with Job Data

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

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

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

Example: Semiconductor Shortages

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

The Advantage

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

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

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

Conclusion: Turning Job Data into Strategy

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

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

Questions? PredictLeads is here to help! 🙂

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

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Introducing PredictLeads’ New Technology Detection API Endpoint

August 21, 2024 /

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

How It Works

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

Example API Endpoint

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

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

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

What You Get

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

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

Sample cURL Request

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

curl –request GET \

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

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

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

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

Interested in Trying It Out?

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

Note on Development

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

Technology Data Snapshot

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

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

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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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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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