Since we’re a default remote first company majority of us work most of the time from home, embracing a remote-first company culture. This commitment to a remote-first company culture ensures flexibility and efficiency in our work environment.
That is why we have monthly informal “meetups” as we call them so that we get some much needed face time đ .
This month we’ve visited local brevery that gets its name from Slovenia’s capital Ljubljana, pronounced “Loo-Blah-Nah” đ.
We’ve learned how the beer gets made and a fact or two.
One of the two facts we’ve learned: India Pale Ale beer (IPA) got its name from the British colonial era. When Brits were taking their Pale Ale beer to India it very often turned bad due to long travels. So they’ve learned to add more hops and alcohol to it to last the long journey on the ships. And that is why it’s called IPA.
How the beer gets made:
1. Malting: Barley is soaked, germinated, and dried to produce malt. Slovenia does not produce it locally so the visited brevery imports it from Germany.
Barley (slo: jeÄmen)
2. Mashing: Malt is mixed with hot water, converting starches to sugars, forming wort. It was explained to us this is basically “sweet water”.
3. Boiling: Wort is boiled, and hops are added for bitterness and aroma.
Hops (slo: hmelj)
4. Fermentation: Yeast is added to the cooled wort, converting sugars to alcohol and COâ. Each of the steps till now takes place in a different stainless steel barrels. No air should get in these barrels otherwise the beer gets bad.
Interesting fact #2: Per the 500 galons (2000 liters) of beer being made some 1,000 pounds (500kg) of Barley is needed and only some 10 pounds (5kg) of hops.
5. Conditioning: Beer is aged to develop that flavor that we all love. In our case the guy said it takes some 3-4 weeks for the beer to develop.Â
As the beer develops our evening also developed quite nicely with every new type of beer we tried along the evening đ . Cheers! đ»
As PredictLeads partnered up with clay.com, it seemed only natural to then go work with clay in the literal sense. This new phase marks the exciting PredictLeads Clay partnership, further enhancing collaboration.
As much as we try it’s really challenging for all of us to look at the camera at the same time đ
Jokes aside, it was an interesting coincidence though not planned to happen :). Eva booked us for a nice evening of working with clay (literally). Through this collaboration with clay, the PredictLeads Clay partnership certainly extended beyond just business.
Screenshot
When working with clay to create a finished ceramic product, two primary steps are needed when heating / firing the clay:
There were also two types of “tables” we were working at. This was the “Pottery Mill”.
Bisque Firing (First Firing): The purpose is to transform the raw clay into a hard ceramic state. This firing removes moisture from the clay and drives out organic materials. The temperature for bisque firing in our case was 950°C (1,750°F).
Glaze Firing (Second Firing): After bisque firing, the piece is coated with glaze, a glass-like coating that provides a smooth, glossy finish. The glazed piece is then subjected to a second firing, known as glaze firing. This firing melts the glaze and forms a glassy, non-porous surface on the ceramic piece. In our case Glaze firing temperature was 1,250°C (2,345°F).
Till the next team meetup! đ
We’re still waiting for the clay shop to go through these two steps and we can’t wait to see what we produced :). Ultimately, this hands-on experience is all part of what makes the PredictLeads Clay partnership such an enriching experience.
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:
Additional information can be found in our docs âhereâ.
Interested in Trying It Out?
Weâre 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!
Hey everyone! Today, let’s dive into how personalized sales outreach with data can revolutionize your approach and make connections more meaningful.
In sales, finding and engaging the right prospects can feel like searching for a needle in a haystack. Sending non personalized emails is just a thing of the past and companies offering sales solutions are looking into data to add that personalized touch that increases those reply rates that we all like.
Job Openings Dataset as well as the News Events Dataset are incredibly useful and widely adopted for uncovering new leads and improving sales outreach. However, there is a unique dataset that is gaining significant attention. This dataset, which is not yet widely used due to its limited availability, holds great potential for transforming sales strategies. Here is why:
We all know that companies like to put logos of other companies they work with, on their website to gain credibility. Since those logos are often not backlinked, PredictLeads has built an image recognition system that connects these logos with company domain names. By checking the companyâs Case studies pages, testimonials, “Our customers” sections and more allows PredictLeads systems to identify them as customers, partners, vendors, sponsors and more.
Hereâs a quick rundown of how the Connections Dataset can revolutionize your sales efforts and how itâs used to target High-Value Prospects.
Identifying and Prioritizing Key Prospects
First up, letâs talk about finding those high-value prospects. With the Connections Dataset, you can pinpoint companies that already have significant relationships with your existing clients or partners. This means theyâre more likely to convert because thereâs already some trust and relevance built in.
How to Do It:
Analyze Data: Dive into the Connections Dataset to find companies that share multiple connections with your current network.
Prioritize Prospects: Rank these companies based on the number and quality of shared connections.
Sales Outreach: Focus your efforts on these high-value prospects. Make sure to highlight the mutual connections and the benefits of joining an established network.
Example: A SaaS company finds that several of its clients are partners with a leading industry player. By targeting this player and emphasizing the mutual benefits, they can craft a top notch outreach thatâs hard to ignore.
Next, letâs make your emails shine.
Personalized outreach campaigns are the way to go because they address the specific needs of each recipient. By referencing the target companyâs partnerships or integrations, your emails can be way more relevant and engaging.
How to Do It:
Gather Insights: Use the Connections Dataset to get detailed insights into the target companyâs partnerships and integrations.
Personalize Emails: Craft email content that references these relationships, making it super relevant.
Automate Personalization: Use AI tools to scale this personalization process, ensuring each email is tailored to the recipientâs context.
Example: An AI-powered email platform identifies a potential clientâs recent partnership with an e-commerce platform like Shopify. They send a personalized email campaign highlighting success stories of similar clients who benefited from this integration. Boom -> relevance and appeal.
Warm Introductions through Mutual Connections
Finally, letâs talk about using mutual connections for warm introductions. These can significantly boost your chances of successful engagement. The Connections Dataset can help you leverage existing relationships to approach leads with more trust and credibility.
How to Do It:
Map Networks: Use the ConnectionsDataset to map out mutual connections between your company and target leads.
Request Introductions: Reach out to these mutual connections for warm introductions, explaining the mutual benefits.
Follow-Up Strategy: Develop a follow-up strategy that leverages the credibility of the mutual connection.
Example: A lead generation company finds that one of its key clients is also a partner of a high-value prospect. They request an introduction from the key client, who provides a warm referral, significantly improving engagement chances and improves their data-driven sales outreach.
Utilizing AI for Enhanced Personalization & amplify the Impact with automation
AI can take your use of the ConnectionsDataset to the next level by automating the analysis and personalization processes. Here are some tips:
Automated Analysis: AI analyzes the dataset to identify patterns and insights, like high-value prospects and mutual connections.
Scale Personalization: AI personalizes email content at scale by incorporating insights from the dataset into email templates.
Predictive Analytics: AI uses historical data to predict which prospects are most likely to convert, helping prioritize efforts.
Continuous Learning: AI systems learn from campaign outcomes, refining algorithms to improve future personalization and targeting.
Example Implementation:
An AI-powered email platform integrates with the Connections Dataset, analyzing the dataset to identify key relationships and generating personalized email content. It predicts which prospects will respond positively and continuously refines its personalization algorithms.
Conclusion
Since 2019, over 170 million business connections have been detected, with business connections data available for 38,5 million websites. Last month alone, there were approximately 12 million business connections, and around 57 million over the past year. The Connections Dataset is a goldmine for lead generation companies and those using AI for personalized emails. By providing detailed insights into company relationships, it helps you target high-value prospects, create relevant and engaging email campaigns, and leverage mutual connections for credible engagements. Combined with AI, it automates these processes and achieves personalization at scale, leading to higher engagement rates and better sales outcomes.
Feel free to let us know if you or if you’d like to learn more. Weâre here to help:)!
PredictLeads has been selected as one of the top 10 teams to participate in the 2018 Startupbootcamp Commerce program in Amsterdam!
Out of more than 600 applicants worldwide, we were chosen among the top twenty companies and invited to Final Selection Days on January 16â17. After an intense evaluation process in front of over 100 mentors and partners, we were honored to be picked as one of the top 10 startups for this yearâs program.
What This Means for PredictLeads
Starting on February 19, weâll join an intensive 3-month acceleration program packed with workshops, one-on-one mentoring sessions, and networking events. The program concludes on May 17, 2018, with Demo Day – where weâll present our progress in front of hundreds of investors, partners, and industry leaders.
During this time, weâll be mentored by a world-class network of entrepreneurs, executives, and VCs. Weâll also gain access to leading commerce companies in the Netherlands to validate and scale our solutions.
PredictLeads will benefit from:
âŹ15K in seed funding
Free office space in Amsterdam
âŹ500K+ in partner services
Access to partners including Amazon, Cisco, Ahold Delhaize, PwC, America Today, and Rabobank
A global network of angels and venture capital investors
Our Goal During Startupbootcamp
Weâre excited to use the immense SBC business network to grow our client base. Our focus will be on B2B companies leveraging company intelligence data in their products or services. Our vision is to establish PredictLeads as the market leader in actionable company intelligence for vendors worldwide.
About Startupbootcamp
Founded in 2010, Startupbootcamp is a leading global accelerator with 20+ programs across Europe, Asia, the Americas, MENA, and Africa. Selected startups receive hands-on mentorship, industry connections, and access to a powerful investor network to accelerate growth.
Weâre thrilled to join this program and canât wait to share the journey ahead. đ
We started PredictLeads with the mission to find actionable business data in public documents. One of our innovations includes the Job Openings Dataset, which provides valuable insights for businesses.
HISTORY
Job postings were always among the most valuable business signals we tracked. Early on, our clients asked not just for news and funding events, but for insights into who companies were hiring, for what roles, and in which locations.
The challenge was that job data scattered across thousands of careers pages was unstructured, messy, and difficult to normalize. For example, one company may post âSoftware Developerâ while another writes âBackend Engineerâ â but both describe similar roles. Without standardization, insights were limited.
After months of developing crawling systems, mapping roles to O*NET occupation codes, and building quality checks, weâre proud to launch the Job Openings Dataset.
FUTURE
At its core, the Job Openings Dataset performs three key steps:
Scan millions of company websites and career pages daily. Public source examples: job boards, ATS systems, company career portals.
Map jobs to standardized frameworks. Using O*NET codes and predictive tagging, postings are classified into consistent roles and families.
And just like with our other datasets, we apply a human supervision layer â ensuring the highest possible quality in classification and normalization.
EXAMPLES
To better picture the type of data, here are two JSON examples:
These are just 2 of 30+ categories supported (engineering, marketing, sales, finance, HR, and more). Full schema is available here: https://predictleads.com/docs/#job_openings
APPLICATIONS
The types of applications are (almost) endless, but here are a few we see most often:
Sales Enablement Solutions: identify prospects investing in teams relevant to your product.
Predictive Lead Scoring: hiring signals are some of the strongest intent indicators for buying readiness.
Account Based Marketing or Sales: personalize outreach with context such as âjust hired a new Marketing Managerâ or âexpanding their engineering team in London.â
Recruiting & Talent Intelligence: map hiring velocity across roles, salaries, and geographies.
Market Analysis: spot industry-wide demand trends and role scarcity early.
CONTACT
Get access to the Job Openings Dataset or request your API key:
At PredictLeads, we go through millions of company websites and public sources to uncover signals that matter most for your business. These sales trigger events highlight when a prospect is more likely to buy or upgrade your service.
Examples of such events include:
Leadership changes
New funding rounds
Technology installations
New product launches
Notable PR mentions
Expansion into new markets
Job openings at key departments
 Why Sales Triggers Matter
With this information at hand, you can quickly filter the best 50â100 prospects out of thousands and contact them at exactly the right moment. No more guessingâjust timely, relevant, and personalized outreach.
 The Technology Behind It
We combine the power of:
Machine learning
Information extraction
Natural language processing (NLP)
Text analysis
Stream mining
This enables us to detect buying signals with precision and deliver them to you in real time.
Join Our Early Customers
Weâre currently working closely with our first customers to build a product that delivers true value. Want a test drive?
Shoot us an email at sales@predictleads.com and weâll help you reach the right prospects, at the right time.
At PredictLeads, our mission is simple but powerful: help companies grow smarter with better data.
In todayâs competitive world, information is everywhere. But not all information is useful. Businesses often waste time on outdated or irrelevant signals, chasing leads that never convert. PredictLeads exists to change that.
Why We Exist
We believe that sales and investment teams deserve access to real-time, actionable insights. Our mission is to make company intelligence accessible, reliable, and easy to use. By transforming millions of raw signals into clean datasets, we help teams cut through the noise and focus on opportunities that truly matter.
What We Do
PredictLeads scans the web to detect:
Job Openings â showing when companies are hiring, growing, or shifting focus.
News Events â revealing funding rounds, partnerships, acquisitions, and more.
Technology Detections â mapping which tools and platforms companies adopt.
Connections Data â uncovering real business relationships hidden in plain sight.
Website Evolution â tracking changes that indicate new strategies or launches.
With these datasets, sales teams book more meetings, investors spot market shifts, and businesses make faster, more confident decisions.
How We See the Future
Data isnât just numbers on a screen. Itâs the backbone of strategy, creativity, and growth. Our mission is to be the partner that empowers businesses to transform data into action. With the right insights, we believe companies can build stronger connections, scale faster, and unlock opportunities they might have missed.
At PredictLeads, we see data as the fuel for growth. And our mission is to make sure you never run out of it.