Tag: PredictLeads

💜How Blueprint Supercharges Sales with PredictLeads Data💜

Navigating the sales landscape with data isn’t just about collecting information – It’s about turning it into actionable insights. This is exactly what Blueprint has mastered using PredictLeads.

🤘Let’s dive into how they do it. 🤘

Data at Work: Real Insights, Real Growth

Blueprint uses PredictLeads to perform deep technographic scoring, analyzing data on 500 new technologies each week. This isn’t just about knowing what’s out there -> it’s about predicting market trends and identifying emerging competitors, providing a clear advantage in crafting timely and relevant sales pitches.

Jordan Crawford, the founder of Blueprint, puts it simply: “It’s not about having more data, but about having the right data that you can actually use.” This is where PredictLeads shines, offering depth with actionable insights.

Key Stats and Strategic Decisions

With PredictLeads, Blueprint isn’t just collecting data -they’re strategically deploying it.

Here’s how:

  • Job Openings Data: By analyzing the hiring trends of potential clients, Blueprint can pinpoint when companies are expanding and tailor their pitches to meet these growth phases.
  • Technology Adoptions: Tracking 636 million technology adoptions helps Blueprint stay ahead, suggesting when companies are likely to need their cutting-edge solutions.

A Relationship Built on Success

Blueprint’s partnership with PredictLeads goes beyond data. It’s about continuous support and collaboration, which Crawford describes as unparalleled. “PredictLeads always finds a way to make it happen,” he says, emphasizing the personalized support that helps Blueprint leverage data effectively.

For those eager to dive deeper into this use-case, you can check it out here.

If you have any questions, please don’t hesitate to reach out to us at: info@predictleads.com

We are here to help:)!

💜Stay Awesome💜
PredictLeads team

Understanding Pension Funds’ Strategic Shift to Private Markets with PredictLeads’ Data

As global pension funds like CalPERS increasingly redirect investments from public equities to private markets, the demand for precise, actionable insights grows significantly. This strategic transition, aimed at securing higher yields and reducing market volatility, is particularly highlighted by pension funds’ systematic moves towards assets like private equity and private debt.

The Role of PredictLeads’ Data in Navigating Private Markets

Job Openings Data:

PredictLeads’ Job Openings Data provides real-time insights into hiring trends directly from company websites, reflecting growth and expansion activities within specific sectors. An increase in recruitment, especially within sectors like private equity and private debt, often suggests robust sector health and promising profitability prospects. For pension funds diversifying their portfolios into these private markets, such insights are critical. They help align investment strategies with sectors that demonstrate strong growth potential, making this data invaluable for funds adjusting to the dynamic conditions of private markets. Additionally, pension funds can use this data to identify emerging industries or regions where new skills are in demand, providing an early indicator of economic shifts that could influence long-term investment decisions.

Business Connections dataset:

The Business Connections dataset from PredictLeads employs advanced image recognition to scan and categorize logos on company websites, unveiling key customer relationships often obscured in conventional financial reports. This dataset is especially valuable for pension funds engaging in scoring potential (startup) investments. Identifying major clients, particularly public companies, allows funds to assess a startup’s credibility and market traction. Companies with esteemed, stable clients can be scored higher, indicating lower risk and potentially higher reliability as investment opportunities. This insight is crucial for informed decision-making in public market investments.

Pension funds can leverage this data to assess the market reach and network strength of potential investments, ensuring a more comprehensive risk assessment and decision-making process. Furthermore, this dataset allows pension funds to monitor the customer base stability of current investments, providing ongoing risk management and insight into market position changes.

Broader Market Implications:

The shift of pension funds toward private markets not only reshapes their investment strategies but also influences broader market dynamics. By utilizing PredictLeads’ alternative data, such as Job Openings and Business Connections, pension funds can gain deeper insights into the risk and potential of their private market investments, which are crucial for informed decision-making in an environment where traditional metrics fall short. 

Moreover, this strategic use of alternative data helps pension funds anticipate market trends, adapt to economic changes, and identify investment opportunities early, maintaining a competitive edge in an increasingly complex financial landscape. Whether through pinpointing emerging sectors with job openings data or evaluating the robustness of potential investments with key customer analysis, these datasets provide critical insights that enhance and refine investment strategies.

Conclusion:

As the trend of pension funds moving towards private markets continues to grow, the importance of alternative data becomes increasingly central. Datasets like PredictLeads’ Job Openings and Business Connections dataset provide essential tools that enable large institutional investors to execute their strategies with greater precision and confidence. By leveraging these alternative data sources, pension funds can more effectively navigate the complexities of private markets, aligning their investment approaches with the most promising opportunities for sustainable returns.

Got questions? Don’t hesitate to reach out at info@predictleads.com!

Case Study: InReach Ventures & PredictLeads

InReach Ventures uses technology to help scale venture capital and make
investments in early stage startups throughout Europe. They built their own
proprietary software and developed a new model of investing to discover and invest in the most promising startups.

There’s a few major data challenges VC’s often face including 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 and how PredictLeads company intelligence data helps InReach Ventures discover new companies and track 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, which helps us to find startups from all over Europe. This data, along with other types, allows us to look at how companies are growing, whether they’re growing their team, if they’re getting new customers or new business connections or partnering with different companies. “

PredictLeads

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. Having the InReach team focus on what we’re good at and working with partners that are better than us in areas 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 but never been able to prioritise. Finding news events around a particular company and identifying company customers through logos/connections is really interesting for us and also 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 and how much innovation is happening in venture capital in the past 10 years is very limited. I think there is a change now where data and software is being seen as a way for venture firms to innovate their model. The issue that traditional VC firms first face is that culturally at their core, they are not a technology firm but a professional services organisation. Where we think we have an advantage is that we started as a technology, product and engineering organisation, taking a very data driven approach to venture capital. That’s where we think we will long term hold the advantage because we started doing this earlier. Traditional venture capital will start to utilise data over time, but at their core they are not tech or engineering organisations. Short term, data and tech will play a broader role in terms of the whole industry using it as it’s becoming more and more of a buzz and as data is becoming more demanded.”

What are some of the trends in Venture Capital?

“My co-founder and Investment Partner Roberto layed out the 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 that it helps us discover that a startup exists in the first place and then tells us whether there’s something interesting happening that we might want to talk to them about.”

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