Category: Company (Page 1 of 3)

The Billion-Dollar Clues Hiding in The Right Blend of Company Data

In 2012, Stripe was just a little payments API that almost nobody outside of Silicon Valley had heard of.
By 2021, it was worth $95 billion.

The uncomfortable truth is the signals that Stripe was going to be huge were visible years before the big headlines hit. Most people just weren’t looking for them (or didn’t know where to look).

That’s the edge today’s smartest investors are chasing: finding billion-dollar companies before they look like billion-dollar companies. And it starts with something almost no one talks about. The right blend of News and Connections data.

The Secret’s in the Signals

At PredictLeads, , we monitor more than 20 million news sources and close to 100 million companies worldwide, capturing key moments in a company’s journey. Spaning from funding rounds and product launches to strategic partnerships, hiring surges, and market expansions.

But we don’t stop at just the news.

Our Connections dataset maps the business relationships that reveal how a company is truly positioning itself in the market – from product integrations and investor ties to vendor agreements and partnerships with industry leaders. This is done by scaning company websites for partner and customer logos, using our image recognition system to match each logo to a verified domain. We also analyze case study pages, testimonials, and “Our Customers” sections to uncover customers, partners, vendors, and investors that often go unreported in press releases or traditional news.

Each connection is a signal of strategic intent: integrations hint at ecosystem alignment, investor relationships point to future funding potential, and vendor or partner deals often precede market entry or expansion. When combined with our other datasets, these connections turn scattered updates into a clear, data-backed narrative of growth — and within that narrative is where the next unicorn often emerges.

The Pattern Every Investor Dreams Of

Picture this:
January > a startup raises a modest $8M Series A.
February > they integrate with Stripe’s API.
March > our company data shows a vendor relationship with Shopify.
April > they expand into London and start hiring engineers at double the previous rate.

If you’re only reading headlines, you’ll miss the story.
If you’re tracking news events and company connections in real time, you’ll see it months before the rest of the market and you’ll be in the room when the deal is still hot.

Why Public Headlines Are Too Late

By the time TechCrunch reports a $100M Series C, the race is already crowded and you’re not ahead of the game, you’re simply keeping pace with everyone else.

To spot opportunities earlier, you need to look where others aren’t. News data reveals unannounced or smaller funding rounds — early signals that a company is gaining momentum. Connections data uncovers the strategic moves behind that momentum, from product integrations and new partnerships to key customer wins and vendor relationships.

Overlay these signals, and you will not wait for the news — you’ll see them coming. The result is an early warning system for hypergrowth, giving you a competitive edge long before the headlines hit.

The Future of Investment Intelligence

In the next five years, the biggest wins in venture won’t go to the investors with the most meetings — they’ll go to the ones who can see conviction in the data before the rest of the market believes it.

The edge won’t come from chasing every funding headline, but from quietly tracking the early indicators of momentum: a new integration with a market leader, a sudden hiring surge in engineering, an unexpected expansion into a high-growth region.

When you can spot these moves as they happen — and connect them into a bigger story — you stop reacting to the market and start anticipating it. Finding the next unicorn isn’t about luck; it’s about reading the signals early enough to act, while the opportunity is still invisible to everyone else.

If you’re ready to see what those whispers sound like, let’s talk.

How Hiring & Tech Insights Help Close More B2B Deals?

When it comes to B2B sales, timing and relevance win deals. But with noisy inboxes and overused tactics, how can sales teams rise above the clutter? The answer lies in real-time signals >> specifically, insights about who companies are hiring and which technologies they use.

In this post, we’ll break down how Jobs and Technologies data can transform your outbound strategy and help you close more deals, faster.

Why Static Lead Lists Fall Short

Most lead lists go stale within weeks. People change jobs. Companies pivot. Tools come and go. If you’re still relying on outdated data, you’re already behind.

That’s why modern sales teams are turning to dynamic lead enrichment — adding fresh, actionable intelligence about a company’s current needs, hiring trends, and technology stack.

The Power of Jobs Data: Catch Companies in Buying Mode

Open job roles are one of the strongest buying signals out there. Why?

  • New hires need tools. A company hiring for “Sales Enablement Manager” or “Revenue Operations Analyst” might be evaluating CRM tools or sales engagement platforms.
  • Growing teams have growing pains. An influx of job ads often means upcoming budget changes or workflow challenges you can help solve.
  • Titles reveal intent. Hiring for “Security Engineers”? Pitch your cybersecurity solution. Looking for “Customer Success Managers”? Perfect time to introduce your onboarding software.

By tracking job openings, you’re not guessing what a company needs but seeing it in plain sight.

Technology Insights: Your Shortcut to Relevance

Now pair that with technology usage data. Knowing a company’s tech stack gives you an unfair advantage:

  • Tailor your pitch. If a prospect uses HubSpot, don’t waste time explaining integrations — highlight how your tool plugs in seamlessly.
  • Find competitors. Selling a project management tool? Filter for companies using Jira or Asana.
  • Segment smarter. Break down your outreach by industry, company size, and the specific tools they already use.

Understanding the tech landscape means you’re not sending generic outreach but you’re showing up with context.

NOW! Let’s combine the Two: Jobs + Tech = Smart Targeting

Here’s where things get powerful: combining Jobs and Tech data.

Imagine this:

You identify a company hiring a “Growth Marketing Lead” and see they use Segment, HubSpot, and Webflow.

You’re selling a data activation tool that plugs right into that stack.

Now you’re not just a cold email — you’re an answer to their current problem.

This type of targeting:

  • Increases reply rates
  • Shortens deal cycles
  • Positions you as a strategic partner, not a vendor

How to Start

You don’t need a platform — just the data. At PredictLeads, we help GTM teams enrich their lead lists with:

  • Job Openings (titles, departments, descriptions)
  • Technology Detections (tools in use, timing, frequency)

You can export enriched lists, plug them into your CRM or outreach tool, and let your sales team do what they do best — close.

It’s Not About More Leads

Outreach isn’t a numbers game anymore. It’s a relevance game. By combining hiring signals with tech stack insights, you’re building the foundation for conversations that convert.

Because the best sales pitch? It’s the one that feels like perfect timing.

What Summer BBQs Can Teach Us About Reading B2B Buying Signals

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.
You read the signals.
You follow the smoke.
You 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:

  • They showcase logos of brands they serve.
  • They mention integrations and partnerships.
  • They drop names in case studies and testimonials.

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

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

In the last 18 months, AI agents have gone from novel prototypes to embedded tools reshaping how teams operate. From automating lead qualification to writing personalized outreach and prioritizing accounts. So we entered an era where AI-powered workflows are no longer futuristic but they’re being built every day by forward-thinking teams.

But there’s a catch: even the smartest agents are only as effective as the data you feed them… and this is where PredictLeads comes in. 💪

What Is PredictLeads?

PredictLeads is a data provider that helps go-to-market (GTM), sales, marketing, and investment teams detect buying signals, technographic data, and growth indicators across 92M+ companies globally.

Unlike traditional data vendors that rely on static firmographics, PredictLeads provides real-time events. Our infrastructure captures:

  •  📌 Job openings (e.g., a company hiring 8+ marketers)
  • 📈 Funding rounds (e.g., $15M Series A just announced)
  • 🤝 Partnership announcements from news sources
  • 🧠 Technology adoption (e.g., company started using HubSpot, Intercom, or Snowflake)
  • 🔄 Website evolution (tracking when companies update key web pages or product language)
  • And more 🤯

Rather than manually building lists, users plug into our API and webhook system to enrich, monitor, and score leads based on real-world behavior.

Why AI Agents Need Event-Based Company Data

Here’s a truth few people mention: most AI agents today are bottlenecked by poor context.

Whether you’re using LangChain, OpenAgents, AutoGPT, or custom tools in Pipedream, n8n or Zapier, these agents often rely on CSV files, firmographic filters, or outdated CRMs.

But what if you could give your AI agent real-time awareness of companies across the globe? With PredictLeads, you can.

🧠 Example: An AI Agent for SDR Teams

Imagine an AI agent that:

  1. Monitors a list of 10,000 target accounts.
  2. Detects when any of them hire a “Sales Enablement Manager” or start using “Outreach.io”.
  3. Automatically generates a personalized intro email (mentioning the hiring signal and tech stack).
  4. Pushes the draft to your SDR’s inbox or LinkedIn queue.

This isn’t a vision but something that is already being built using PredictLeads + AI.

Top Use Cases for PredictLeads in AI WorkflowsHow Developers Are Plugging Into PredictLeads

Use CaseDatasetAI Output
Outbound AutomationJob Openings + TechnologiesPersonalized emails or LinkedIn messages
Account ScoringNews Events + FundingDynamic ICP fit scoring
CRM EnrichmentCompanies + Website EvolutionAuto-filled account descriptions & tags
Market MappingConnections + Tech DetectionsRelationship graphs and industry maps
Timing SignalsJob ads + Product LaunchesPredictive lead routing and prioritization

Our API-first architecture is designed for speed and scale:

  • JSON responses, simple endpoints
  • Daily updated datasets
  • Filter by job title, tech tag, domain, industry, revenue, geography, and more
  • Works inside Pipedream, n8n, Make.com, Zapier, Retool, Hex, or any data warehouse

With no login UI or bloated dashboards, you get direct access to raw signals – the way AI agents expect it.

Why This Matters in 2025

As AI agents become more autonomous, they need ongoing context. You wouldn’t send an SDR to a meeting blind. Why would your AI be any different?

Feeding agents with PredictLeads’ dynamic company signals ensures your GTM systems stay ahead of the curve –  proactively identifying shifts in buyer behavior before competitors do.

This will help you change the future from automating more tasks to making smarter decisions in real-time. And so that we are on the same page > that starts with better data.<

Final Thoughts

At PredictLeads, we believe the next wave of GTM efficiency will come from pairing autonomous agents with live market signals.

If you’re building AI tools that need to understand what companies are doing (not just who they are) we should talk.Get started with a free trial or speak with our team about your use case: https://predictleads.com

How 🟣PredictLeads + Pipedream🟢 Help Founders Score and Reach Out to Leads with Relevant, Timely Signals

Most companies already have a massive list of leads covering some tens of thousands of domains, contacts, or accounts collected from various sources. So sometimes – the problem isn’t finding leads – isknowing when and why to reach out. 

That’s where PredictLeads comes in 🥳

Our API lets you ping domains in your lead list and enrich each company with fresh, real-time signals like hiring activity, new partnership, funding rounds, or changes in their tech stack. These signals help you score leads and create meaningful, personalized outreach triggers so your sales team can contact prospects at the exact right moment. 

By integrating PredictLeads data with Pipedream, your engineering team can now build fully automated workflows that: 

  • Enrich leads as they come in
  • Automatically score and prioritize based on recent business events 
  • Trigger personalized email sequences or alerts to sales reps 
  • Do all this without costly manual data processing or building complex pipelines
PredictLeads logo above a headline asking 'What do you want to automate with PredictLeads?' followed by a subtext describing AI agent deployment with over 2,500 connected apps

Why This Matters 🤔

Many founders tell us: “We have a huge lead list, but our outreach is not working. We don t know who to call first or what message to send.” 

The truth is that generic outreach is too old or irrelevant and doing that leads to wasted time and budget. But if you can layer in contextual, timely data like “This company just raised $5M“, or “They started hiring SDRs last week” suddenly your outreach becomes relevant, compelling and timely.

How the PredictLeads + Pipedream Workflow Works

  1. Upload or connect your lead list of thousands of company domain names. 
  2. Use PredictLeads API via Pipedream to ping each domain and enrich it with signals such as recent funding, hiring, new partnerhips or tech adoption.
  3. Pipedream picks up this data and runs workflows to:
    • Score each lead based on your criteria
    • Create or update records in your CRM 
    • Send tailored outreach messages via email or LinkedIn 
    • Alert sales reps in Slack or other tools 
  4. Sales teams receive prioritized leads with a strong reason to reach out making outreach timely, efficient, and high impact.

Example Use Case: Outreach After Funding or Partnership & Hiring Events

Your company has a list of 30,000 leads collected from marketing and old data vendors but it’s unclear which leads are hot right now.

You set up PredictLeads API to check these domains daily and flag those who: 

  • Raised a funding round in the past month 
  • Recently hired sales or marketing roles 
  • Started using new technologies relevant to your product 
  • Formed a partnership with a F500 company (signaling buying power)

Whenever a lead matches your triggers, Pipedream runs your workflow scoring that lead higher, sending a personalized email sequence referencing their recent event, and notifying your sales team to act fast.

List of popular PredictLeads API actions with options to get technologies, look up companies by domain, retrieve companies by technology, and access news events by domain each with links to documentation and a 'Try It' button

Why Use PredictLeads + Pipedream Together?

  • Low cost & no heavy engineering to get automated
  • Real-time enrichment without building your own data pipelines. 
  • Personalize outreach at scale to reach to the right people with the right message at the right time. 
  • Create flexible workflows integrated with any CRM, marketing platform, or communication tool via Pipedream extensive connectors.

If you already have a lead database stop wondering who to call next, know when to call & get started with PredictLeads + Pipedream now, and unlock 100 free API credits to experiment.

PredictLeads and Pipedream logos above an illustration of two stylized hands forming a handshake, symbolizing integration and partnership between the platforms

The Great Gatsby Mystery: A 1920s-Inspired Team Building Experience

Last week, the PredictLeads changed Google chats and company data to glamour, secrets, and suspense. Our destination? A one-of-a-kind immersive mystery game set in the roaring 1920s.

Four PredictLeads team members dressed in 1920s Gatsby-themed attire smiling and posing after completing a mystery escape game at Enigmarium. They wear vintage-style hats and accessories, standing against a rustic, dimly lit background.

Dressed in our finest vintage attire, we joined forces (and in some cases, formed rivalries) to solve a high-stakes Gatsby-themed that brought out the detective (and the actor) in all of us.

Reimagining Team Bonding in the Style of The Great Gatsby

As part of our ongoing commitment to fostering strong team culture, we wanted to do something more and were looking for an experience that was collaborative, interactive, and completely unexpected.

Each of us was assigned a character – from wealthy elites and ambitious entrepreneurs to struggling artists, cunning politicians, and even a few shady underworld figures. With roles in hand and costumes to match, we were immersed in a glamorous, high-stakes environment filled with intrigue, hidden agendas, and unexpected twists.

A Night of Suspicion, Alliances, and Twists

The game kicked off with whispered theories and hushed conversations. Who could we trust? Who had something to hide? Working in small groups, we pieced together clues, questioned timelines, and uncovered motives.

And just when we thought we had it figured out – boom. A final twist turned everything upside down. We won’t spoil the ending, but let’s just say that more than one person is still debating whether the artist was secretly behind it all.

Dressing the Part: Vintage Glam Meets Office Culture

What made the evening even more memorable was the team’s commitment to the theme. Feathers, fedoras, flapper dresses, suspenders, red lips, and sparkling accessories transformed our crew into characters straight out of a F. Scott Fitzgerald novel.

Three PredictLeads team members in elegant 1920s Gatsby-style costumes clinking champagne glasses during a themed mystery event. They are wearing vintage dresses, pearls, feathers, and headpieces, smiling and engaged in lively conversation.

For many of us, it was the first time we’d seen each other outside our usual roles. People embraced their alter egos, delivered dramatic monologues, and even discovered unexpected talents for improvisation and persuasion.

Unique Team Events Matter

At PredictLeads, we know that team-building activities aren’t just about having fun, but they’re about building trust, encouraging creative thinking, and strengthening our collaboration across roles and departments.

This 1920s mystery night reminded us that behind every line of code and every data insight is a team of curious, resourceful, and creative people. When we step outside our usual routines (even just for a night) we return more connected, more energized, and more in sync.

Planning a Team Building Event? Try a Mystery Game

If your company is looking for a unique corporate event idea, we can’t recommend immersive mystery games highly enough. They combine teamwork, communication, and problem-solving > all wrapped in an experience that people won’t forget.

Smiling man and woman in vintage 1920s-style attire at a themed event, posing confidently in front of a gold column. The woman wears a flapper-style dress with pearls and a headband, while the man is dressed in a grey blazer, light blue shirt, and flat cap.

We came for the mystery. We left with stronger connections, unforgettable memories, and a renewed appreciation for the people behind the PredictLeads brand.

Until next time,
The PredictLeads Team 💜

Using PredictLeads + Polytomic to Power GTM Execution (in HubSpot and Salesforce)

Modern go-to-market teams rely on timely data to prioritize accounts, launch targeted campaigns, and coordinate sales and marketing outreach. Yet too often, valuable buying signals get buried in spreadsheets or trapped in data warehouses out of reach for the teams who need them most.

That’s why we’re excited to share how teams can now use Polytomic to ingest PredictLeads data and sync it directly into CRMs like HubSpot and Salesforce which enables faster, more data-driven GTM execution.

Why is this worth checking out? 

PredictLeads provides structured datasets that reveal what companies are doing today and not just who they are. One of the most actionable sources is the Jobs dataset, which includes job openings published by companies across regions, industries, and roles.

This data becomes even more valuable when combined with Polytomic’s no-code integration and sync capabilities. Companies can now ingest and filter PredictLeads datasets inside Polytomic and push enriched company profiles directly into downstream systems such as Salesforce or HubSpot.

The result? GTM teams can identify the right accounts earlier and take action faster + without waiting for engineering teams to build pipelines or sync logic (read – lower cost overall).

Some Examples

Below are specific ways companies are already leveraging PredictLeads + Polytomic to accelerate sales and marketing efforts:

1. Identify Companies Expanding Their Marketing Teams

A B2B marketing automation company can use PredictLeads to track companies hiring for roles like “Head of Demand Generation” or “Growth Marketing Manager” across North America.

Using Polytomic, they can filter the dataset to include only companies hiring in target regions or industries and sync those records to Salesforce with enriched fields like job title, location, and department.

This gives SDRs a live list of companies expanding marketing efforts which often leads to indicators of new technology investment.

2. Prioritize Sales Outreach Based on Engineering Hires

A DevOps platform provider can monitor companies hiring for “DevOps Engineers” or “Platform Engineers.”

When PredictLeads detects these job openings, Polytomic can automatically add these companies to a HubSpot static list, assign them to specific reps, or trigger sequences.

This ensures the sales team is focusing on companies building out the exact functions their product supports.

3. Regional Expansion Tracking

A SaaS company entering the DACH market can use PredictLeads to identify existing accounts or net-new prospects that are hiring in Germany, Austria, or Switzerland & even if the companies are headquartered elsewhere.

Polytomic enables dynamic filtering by job location and continuous syncing of these expansion signals into the CRM.

This allows the GTM team to prioritize outreach to accounts actively expanding into target regions.

4. Surface High-Intent Accounts in Product Categories

A cybersecurity firm can monitor job descriptions for keywords like “SOC2,” “Zero Trust,” or “compliance.”

With PredictLeads, these keyword-based filters can be applied at the job posting level. Polytomic can then transform this insight into CRM data fields and automatically assign these companies to tailored marketing or outbound workflows.

How It Works

  1. Ingest PredictLeads data into Polytomic: Use Polytomic’s UI or API to import PredictLeads datasets, including Jobs, Technologies, News Events, or other signals.
  2. Filter and enrich: Apply filters based on department, location, job title, or keywords. Combine with internal firmographic or historical data.
  3. Sync to your CRM or tool stack: Polytomic allows you to push data to HubSpot, Salesforce, Google Sheets, and many other tools (no code required.)
  4. Activate GTM workflows: Enable automated lead scoring, list assignment, alerts, or outbound triggers based on fresh buying signals.

Bottom Line?

This integration bridges the gap between rich external data and actionable CRM workflows. With PredictLeads and Polytomic, go-to-market teams can:

  • Shorten the time from signal to action
  • Prioritize accounts based on real-time hiring intent
  • Reduce reliance on internal engineering resources
  • Improve campaign targeting and SDR productivity

If your team is already using PredictLeads (or considering it) and wants to enable more automated, intelligent GTM workflows, integrating via Polytomic is a fast and scalable option.

To learn more about setting up the integration, reach out to our team at PredictLeads or visit polytomic.com.

PredictLeads Hackathon: Creating Space for Innovation

At PredictLeads, we spend most of our days helping others find the right companies to connect with through data, signals, and integrations. But last week, we took a break from business as usual to focus on something a little different.

We packed our laptops (and swimsuits) and headed to Rezidenca Ortus in Ankaran, Slovenia for a 3-day offsite. The agenda? A mix of team building and a focused hackathon – designed not just to build features, but to challenge how we think, collaborate, and create.

Why a Hackathon?

The goal wasn’t just to ship code. It was to pause, zoom out, and give space to ideas that don’t fit into normal sprint cycles. Some projects were technical experiments, others aimed to improve our workflows, and many explored new ways we could bring more value to customers.

But beneath it all, there was a shared purpose:

  • To ask ourselves: What could PredictLeads look like in 6–12 months if we reimagined parts of our product, infrastructure, and sales approach from scratch?
  • To surface real problems – whether hidden in data pipelines, user flows, or feedback loops and prototype better ways forward.
  • To give every team member the freedom to explore, pitch, and test ideas, regardless of their role or domain.

🌿Nature, Focus & Team🌿

We started with a team day at Škocjanski Zatok, a peaceful nature reserve not far from the hotel. It gave us the mental reset we needed to approach the next two days with intention and clarity.

From Thursday morning onward, the rooms filled with quiet intensity – whiteboards scribbled with flowcharts, spontaneous stand-ups with a sea view, design mockups being debated over coffee, and engineers debugging in pairs. In between: football matches, sauna sessions, late-night brainstorms, and lots of laughter.

Building Together

Not every project will be production-ready tomorrow. But that wasn’t the point. The point was to tap into the full potential of our team and to explore directions that could shape PredictLeads in the quarters ahead.

We’re already taking some of these explorations further, integrating them into our roadmap. Others are helping us rethink how we prioritize, design, and ship.

Above all, the hackathon reminded us that growth isn’t just about velocity but about creating space for good thinking to happen. And sometimes, the best way to do that… is to leave the office, go offline, and just build together.

If you’re curious about where we’re headed next, check out our datasets, reach out, or simply stay tuned – we’re just getting started.

US-China Tariffs and Shopify Adoption: Signals to Watch 👀

Trade tensions between the US and China are once again front and center — and this time, the numbers are steep.

  • 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.

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

  • Job openings 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.

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.

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.

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.

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
  • 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.

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.

Sweet Moments with PredictLeads: A Teambuilding Day at Radolška Čokolada 🍫💜🍫

Working remotely has its perks – flexibility, focus time, and the ability to work from just about anywhere. But every now and then, it’s refreshing to step away from screens and come together in person. That’s exactly what we did this last Thursday at PredictLeads.

For our monthly team meetup, we traded keyboards for cocoa beans and visited Radolška Čokolada, a charming, family-run chocolate shop nestled in the heart of Radovljica. Surrounded by the rich aroma of chocolate and the buzz of creativity, we dove into the delicious world of sweets.

Our hosts welcomed us with a behind-the-scenes look at how their handcrafted creations are made—from tempering and molding to the final artistic touches.

Along the way, we picked up some surprising trivia (did you know that properly tempered chocolate makes a satisfying snap when broken🫰? If it crumbles or bends, something’s gone awry!).

But the real fun began when it was our turn to get hands-on. Aprons on, gloves ready—we rolled up our sleeves and created our own chocolate masterpieces. There were laughs, a bit of friendly competition, and plenty of taste-testing along the way.

Aside from the chocolate, this was a chance to reconnect, recharge, and strengthen the bonds that make our team tick. Whether we were decorating pralines or just sharing a laugh, the day reminded us how important it is to take time to celebrate the people behind the work.

Until the next meetup – sweet memories like this one will keep us smiling. 💜🍫

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