It’s no secret that the rise of alternative data—from employment data to credit‑card receipts, web traffic, and geolocation data—has empowered hedge funds to uncover unique signals beyond traditional financial metrics. 

In fact, a recent research report, “Alternative Data Buyside Insights & Trends 2025” by BattleFin and Exabel, revealed that 98% of investment managers agreed that “traditional data/official figures are becoming too slow in reflecting changes in economic activity” and forecast the demand for alternative data to fuel alpha generation to continue accelerating for years to come.

But how can institutional investors manage multiple data streams at the same time and produce signal efficiently? Below are 11 leading platforms that fuse AI, machine learning, and alternative data to enable quantitative and fundamental investors to generate actionable insights faster and accurately.

1. Exabel

Overview: Exabel is a next‑generation alternative data platform used by asset managers, hedge funds, and pension funds. It provides over 50 pre‑mapped alternative datasets seamlessly integrated with KPI and fundamental data (e.g. via FactSet, Visible Alpha)

Strengths:

• Only onboards alternative data where they can clearly identify a signal. Helps buyside firms focus on Signal generating data vs wasting time.
• Coding‑free interface and Signal Explorer enable investment teams (even non‑data‑scientists) to map data to company KPIs, test signals, and build forecasts almost immediately.
• Flexibility to onboard proprietary datasets (bring your own data) and combine them with vendor data, reducing integration barriers.
• Built for speed: firms can evaluate new datasets “in days, not months”  
• Hierarchical modeling: more accurate, consistent, and insightful predictions using alternative data
• Affordable pricing tiers based on usage
  
  

2. Hebbia

Overview: Hebbia’s flagship platform, Matrix, functions as an AI‑driven analyst designed to ingest vast volumes of unstructured documents (PDFs, filings, transcripts) and produce structured, fully cited outputs that support complex, multi‑step research workflows.

Strengths:

• Scalable cross‑document synthesis: Capable of processing millions of pages across formats to uncover patterns and comparative insights    
• Structured, auditable output: Results are delivered in spreadsheet‑like grids 
• Sophisticated task orchestration (ISD engine): Queries are decomposed into logical subtasks and executed via AI agents in parallel, followed by iterative searching and inference, producing comprehensive answers even for intricate questions  
• Trusted by elite institutions: Used by approximately 30% of the top 50 asset managers, including firms like Centerview Partners, Charlesbank Capital, and broad adoption in hedge funds and private equity—proving its relevance in real‑world finance workflows  
• Crisis‑ready speed: Demonstrated valuable during the SVB regional bank fire‑sale event by mapping exposure across portfolios in minutes instead of days or weeks 

Note: Hebbia does not bundle proprietary datasets—it relies on user‑provided documents and data rooms.

3. AlphaSense

Overview: An intelligent search & market‑intelligence platform that mines investor transcripts, filings, news, and analyst research using AI and NLP.

Strengths:

• Helps uncover sentiment, hidden commentary, and industry trends not captured in spreadsheets.
• Trusted by top-tier asset managers for real-time decision support.
• Powerful document search, trend tracking, and alerting across public and proprietary content.
  
  

4. Koyfin

Overview: A visual analytics platform tailored for hedge funds, combining traditional and macro data into customizable dashboards and charts.

Strengths:

• Intuitive UI for building dashboards on global economic indicators + equity data—useful for macro‑driven quant strategies.
• Low barrier to entry and accessible pricing.
• Supports cross‑asset class comparisons quickly.

5. Qlik (Data Integration & AI)

Overview: Qlik provides end‑to‑end data integration, real‑time analytics, and automated AI/AutoML powered dashboards.

Strengths:

• Robust ingestion & cataloging layer (Replicate, Compose, Catalog) for blending internal and vendor alternative data.
• Natural‑language analytics via Qlik Answers; visual AutoML and low‑latency processing.
• Enables non‑technical users to query unstructured data sets.

6. Claude for Financial Services (by Anthropic)

Overview: Tailored generative‐AI platform designed specifically for financial institutions—bridging internal and external data with privacy safeguards.

Strengths:

• Pre‑built connectors to Databricks, Snowflake, S&P Global, Box—centralizes alternative data ingestion.
• Advanced Claude 4 models achieve high accuracy on complex tasks (83% in Financial Modeling World Cup) and generate qualitative insight efficiently.
• Enterprise‑grade IP protection; no client usage leaks back into training.

7. Aiera

Overview: A generative AI‑driven event intelligence platform focused on delivering real-time context and signals from investor events.

Strengths: 

• Integrates live and historical earnings call transcripts, corporate events, regulatory files, and media sources into a unified interface with search, sentiment, summaries, and topic extraction capabilities  
• Backed by prominent investment banks and research providers, with Microsoft as a strategic partner following a $25 M Series B round in June 2025 
• Trusted by institutional financial professionals to power equity research workflows via dashboards, APIs, and native integrations  
• Designed with focus, speed, and auditability—making event-based alpha accessible in real time.

8. Bigdata.com

Overview: An AI research assistant tailored for finance professionals, built on RavenPack’s decades of alternative‐data expertise.

Strengths: 

• Unified platform combining news, sentiment, earnings calls, filings, and portfolio data into search‑first infrastructure optimized for financial workflows 
• Recent launch of autonomous “AI agents” that monitor portfolios 24/7, issue pre‑market briefs, and automate repeatable research tasks 
• Proven auditability: every insight includes paper‑trail provenance, enabling firm governance and validation  
• Used by top-tier financial institutions—14 hedge funds and 20+ investment banks among them  

9. Wokelo

Overview: A generative AI platform designed to accelerate investment research, diligence, and intelligence synthesis.

Strengths: 

• Automates up to ~40% of due diligence tasks by generating executive‑ready reports, memos, and sector profiles in minutes—saving days or weeks of manual effort  
• Pulls from 500+ premium datasets including FactSet, Cap IQ, LinkedIn, news, filings, patents, and more to produce real‑time, high-fidelity synthesis  
• SOC‑2 compliance and strong data room integration support secure workflows; used by clients including KPMG, Guggenheim, Google, Tata Group, private equity and VC firms  
• Accelerates deal flow: reduces diligence cycles from ~21 to ~10 days and enables screening of 5–10× more deals per month 

10. Carbon Arc

Overview: An AI‑driven marketplace and exchange providing structured, private data as pay‑per‑megabyte insights.

Strengths: 

• Founded by a former Point72 data executive and raised $55–56 M to launch Insights Exchange, a platform that turns siloed private and enterprise data into AI-ready, licensed datasets 
• Unified ontology to standardize diverse datasets (retail, healthcare, industrials, etc.), enabling interoperability and rapid AI integration  
• Consumption-based pricing: users pay per MB of insight consumed—lower cost and flexible access compared to traditional data contracts  
• Democratises access to structured alternative data, enabling even smaller asset managers to leverage signal-rich sources competitively 

11. FactSet

Overview: A legacy data & analytics leader offering both traditional and alternative data coverage, delivering integrated tools for research, portfolio analysis, and risk management.

Strengths:

• Aggregates alternative datasets such as satellite imagery, web scraping, and transactional data into analytics workflows.
• Powerful screening, alerts, and performance attribution modules help quantify alpha from non‑traditional signals.
• Deep user base in global financial institutions and well‑established support infrastructure.
  
  

Comparison Table: Which Tool Best Fits Your Hedge Fund Strategy?

Why Alternative Data Matters in 2025

In 2025, hedge funds are increasingly leveraging alternative data to differentiate strategies. Firms are moving past reliance on traditional fundamentals to incorporate geolocation data, web traffic, consumer receipts, and sentiment analytics to uncover early trends and hidden alpha signals.

• As one fund manager put it, Exabel “propelled us ahead of our peers” by accelerating alternative data evaluation cycles 
  
  
• Simultaneously, platforms like Claude for Financial Services now offer unified interfaces that combine internal datasets (e.g. CRM, proprietary research) with external market and alternative datasets via secure enterprise connectors  

Implementing the Right Toolset

When evaluating AI and analytics platforms for alternative data strategies, hedge funds should consider:

1. Data sourcing & onboarding speed: Can your team test new datasets rapidly (like Exabel or Quandl) without long integration cycles?
   
   
2. Signal-building capabilities: Do tools support script‑free modeling (Exabel, Qlik) or require coding (Quandl, SAS)?
   
   
3. Governance & audit: Platforms like SAS Viya or Quantexa offer strong bias checks and compliance controls.
   
   
4. Integration with existing infrastructure: Does the tool plug into Snowflake, Databricks, FactSet, Excel workflows, etc.?
   
   
5. Strategic focus: Quant‐heavy firms may prefer Quantexa graph analytics or Quandl data; fundamental shops might lean toward Daloopa or Exabel.
   
   

The convergence of AI, machine learning, and alternative data is reshaping how hedge funds uncover alpha. From structured financial extraction, NLP sentiment mining, network intelligence, to built‑in signal-testing platforms, the tools above represent the top tier of capability in 2025.

• Exabel stands out for its speed and ease in mapping alternative data to company KPIs—allowing firms to test datasets and build predictive signals in days.
  
  
• Tools like FactSet, AlphaSense, and Claude for Financial Services support broader enterprise workflows combining traditional and alternative data.
  
  
• Platforms including Koyfin, SAS Viya, Qlik, and Quantexa each deliver unique strengths depending on whether your strategy is quantitative, fundamental, graph‑based, or model—focused.

By selecting the right platform mix, investment teams can gain robust, differentiated access to alternative data insights, accelerate research workflows, and systematically generate repeatable alpha.

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Focus on compliance, proof of value, and educational content to set your brand apart.

As a modern data provider, you know firsthand that while alternative data is booming, so is competition. With data budgets expected to grow in 2025, data buyers are flooded with options. 

In fact, according to a recent 2025 alternative data focused research study by BattleFin and Exabel, over 86% of investment managers said that their use of alternative data would increase overall in the next two years, with different data categories expected to experience varying levels of growth. 

When asked which sources of alternative data they anticipate using more in the next three years, geolocation data emerged as the category with the highest expected growth, with over 52% of respondents indicating a dramatic increase in usage. Consumer spending data closely followed, with around 51% of investment managers expecting to expand their use.

But despite having a vast menu of datasets to choose from, data buyers will only buy what stands out in generating signal for finding alpha or actionable insights for driving better business outcomes. In McKinsey’s recent report about scaling data products, the global consulting firm advises, “It’s about more value, not better data. The goal of developing data products isn’t to generate better data; it’s to generate value.”

So how do you get noticed? To help shed light on the subject, the alternative data experts at BattleFin offer the below three strategic ways to package your alternative data, reduce buyer hesitation, win their trust—and their business.

3 Powerful Ways to Package Alternative Data to Attract More Buyers

1. Front‑Load Compliance & Legal Assurance: Eliminate Risk for Buyers

One of the biggest friction points for data buyers—especially institutional ones—is risk. They must ensure your data is legally obtained, ethically sourced, and defensible against regulatory scrutiny. That’s why you should lead with compliance as a core feature of your offering.

Buyers in financial services require strict compliance documents like DDQs, formal policies governing PII/MNPI, and evidence of GDPR, CCPA or ISO 27001 alignment. Leading risk management firm Deloitte emphasizes the need for due diligence, vendor risk monitoring, and documentation around personally identifiable data. 

Reputation matters. That’s why it’s important to verify your certifications, collect data legally, and provide sample datasets to demonstrate credibility.

• Prepare a robust Due Diligence Questionnaire (DDQ) and make it front and center in your marketing materials.
• Highlight certifications and compliance frameworks like FISD standards, GDPR/CCPA alignment, and any ISO or audit credentials—this signals credibility. 
• Include metadata and data provenance documentation, clearly explaining where your data came from, how it's collected, and its legal basis.
  If possible, include a back‑test summary showing consistent quality and reliability over time. 

By starting here, you reduce barriers early, prove you’ve done your legal homework, and position yourself as a safe, trustworthy alternative data source.

2. Offer Validation: Live Trials and Real Proof of Value

Once compliance is established, buyers want to know: “Does this data actually offer value when used?” Proving your dataset’s effectiveness with concrete evidence is essential.

Trials and back‑testing build trust and let buyers analyze real results before committing. Alternative data buyers rely heavily on trial periods to assess performance. Alternative data analytics platforms like Exabel can help expedite this process with their highly efficient data evaluation offering and alternative data vendor value summaries. 

Flexible trial structures—including extensions—and transparent communication throughout trials improve engagement and conversion rates. 

• Structure live trials—either free (time-limited) or paid, but with enough scope (e.g., a 3‑month window) to let buyers integrate and test your data. 
• Provide sample data, data dictionaries, methodology documentation, and even backtested results as part of the trial—building confidence and speeding the evaluation. 
• Offer post-trial collaboration—let buyers retain access if they ask to extend or keep data past expiration. This flexibility can transform trials into conversions. 
• Track usage, performance accuracy, integration ease—and share insights—so buyers can see proof that your data “gets it right.”

Showing you can deliver reliable insights, and proving it live, makes decision-makers comfortable investing in your Alternative Data—even at premium pricing.

3. Use Whitepapers to Educate and Position Your Brand as a Thought Partner

For data consumers—especially those on data or research teams—whitepapers pack an intellectual punch. They demonstrate thought leadership, showcase real use cases, and create top‑of‑funnel interest in your data.

Buyers in the B2B world often engage with multiple content pieces—3 to 7 or more—before contacting a provider. Whitepapers are a top performer in building trust and awareness. Whitepapers that include case studies, visual insights, and quantifiable results can highlight your value without overt selling. 

Create research-driven whitepapers, for example:

• “How Alternative Data Predicted Q2 Retail Spend Trends”
• “Using Geolocation Data to Forecast Real‑Time Store Traffic”
• Or even an annual “Alternative Data Insights Report in [Your Vertical]”
  
  

Use real anonymized examples, charts, and narrative to explain the impact—not just technical specs. Keep it analytical and educational. Gate these content assets behind a simple form to capture leads, then nurture them via follow-up email content marketing. Repurpose whitepaper content into blog posts, Infographics, or executive summaries—extend reach and reinforce SEO value around the term Alternative Data.

Well-crafted whitepapers say, “We’re not just selling data—we enable better, data-driven decisions.” That differentiates you, especially among research-savvy data buyers.

In 2025, the alternative data market is booming—with buyers spending millions and loyalty running high. To stand out, packaging your data isn’t just about features—it’s about trust, proof, and partnership.

By leading with compliance, proving your data works, and educating the market through whitepapers, you craft a compelling narrative that your alternative data isn’t just available—it’s credible, valuable, and investment-worthy.

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The Recipe for Success You Should Be Following Before, During, and After Events

If you’re an alternative data provider, you know firsthand that getting the most return on investment from industry events to showcase your data isn’t as easy as just showing up–that’s only the first step. There’s quite a bit of homework and preparation necessary to ensure your data solution is demonstrated effectively to your target customers. 

According to recent research from The Tradeshow Network, as much as 70% of industry event attendees said they benefited from lead generation and brand awareness after attending in person industry tradeshow events. When it comes to ROI from attending BattleFin Discovery Day–the proof is also shown by data providers directly. 

“BattleFin events are always well planned and flawlessly executed. The core value for us as a data vendor is the 1-1 meetings with buyers. In terms of ROl, generally one good deal pays for the time and expense invested, and we have usually experienced that. We are repeat event customers, so that is always the true test,” said Michael Sapienza, Business Development at DataPulse, an alternative data provider that previously attended BattleFin Discovery Day. 

Are you ready to attend BattleFin Discovery Day or your other next industry event and get the most value from it? To make sure you don’t miss out on any opportunities to market your brand and generate leads, the BattleFin team has developed an in-depth overview of the top three ways to extract value from attending our alternative data events, segmented by time leading up to, during, and after the event. 

1. Pre-Conference Preparation

Research and Targeting

• Make sure that you have built out a concise company and product profile in the app or directory.  Before BattleFin events we set up a call review your profiles.  Adding Marketing Attachments, Coverage Lists and Real World Examples help you stand out.  

• Leverage the bi-directional meeting scheduler: Review the buyer list to identify prospects, especially decision-makers or stakeholders from target companies.

• Speakers and Exhibitors: Note relevant sessions and key speakers where potential customers might be.  Reach out to speakers to connect over LinkedIn before the event.

Set Goals

• Define clear objectives, such as the number of leads to capture, meetings to schedule, or partnerships to explore.  Create an ROI model and hit it.  

Schedule Meetings in Advance

• Reach out to prospects before the conference through email or LinkedIn to schedule time to meet at your booth or during breaks.

Optimize Collateral

• Create compelling materials like brochures, whitepapers, or case studies showcasing how your data solutions have delivered value.  

• Prepare tailored presentations or demos highlighting the pain points of target customers.  Leverage the BattleFin Ensemble platform to see the 13F filings of the funds your meeting with.   See which top holdings they may have that your data covers.  Come prepared with some interesting insights on those companies.

Social Media Buzz

• Announce your attendance and booth details on LinkedIn and Twitter(X).  

2. Networking At the Conference 

Booth Strategy

• Eye-Catching Setup: Use visuals, interactive demos, or giveaways to draw attendees to your booth.

• Engaging Staff: Train your team to approach attendees proactively and ask open-ended questions to understand their needs.  Don’t be a wallflower.  

Network Effectively

• Attend sessions and social events to engage with attendees in a less formal setting.

• Engage with prospects over coffee and during meals.

Offer Value

• Position yourself as a thought leader by offering advice, sharing insights, or discussing trends during conversations.

• Mention unique aspects of your data solutions, such as breadth, depth, or integration capabilities.

3. Post-Conference Follow-Up

Personalized Outreach

• Send tailored follow-up emails or LinkedIn messages within 1-2 days. Reference specific conversations or sessions to make it personal.  Short concise subject lines get the most email opens.

Provide Additional Value

• Share relevant resources, like a whitepaper or case study related to their industry, along with your message.

Nurture Leads

• Segment your leads by interest or readiness to buy and add them to appropriate nurture campaigns.  Give 3 to get 1.  Give 3 pieces of useful information before asking them for anything or to get on a call.

Stay Connected

• Follow up periodically to provide insights or updates that might interest them, even if they’re not ready to buy immediately.

In conclusion, alternative data providers attending BattleFin Discovery Day–and any other industry events– will find that the most ROI comes from leveraging the above checklist and being prepared with a strategic approach to capturing attention from the data buyer prospects you want to engage with when the time comes. 

Need more inspiration? Check out our previous BattleFin event data spotlights, sponsors, speakers, and panel discussions for ideas of how to set your data product apart. 

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The month of July saw an explosion of activity across the alternative data industry--particularly with many new data product launches and lots of buyside momentum. Here's an in-depth recap of everything you need to know.  

News You Can Use

Prada missed the street’s consensus estimates. With all the information out there, is there a way to do better at forecasting a firm’s performance rather than just relying on consensus and sell side research? Alt data is proving its worth by delivering more accuracy. Exabel, the analytics platform consolidating alt data and building insights and models on it, got this one right across 4 different KPIs. Check out their post for more details. Makes us think, can investment professionals afford to ignore alt data signals? 

Exabel recently added pass_by to their offerings - a footfall dataset enhanced by hardware sensors - with a strong signal in retail, hospitality and restaurant sector. Check out their detailed report on it.

What’s happening in the LLM world?? We came across this leaderboard that tracks metrics from a user’s standpoint and not just performance. Interesting to see Grok 4 on the top… but for how long?

The Data Corner

Advan put out their monthly insights report in early July with coverage on SFM, AMZN, TSLA, CHWY, SBUX, DVA, PII, GWW, HRL, WYNN/Mgm, PRKS, CMCSA/DIS, and PSA. It was nice to see a healthcare name on it - Davita (DVA) - showing visitation as a good predictor of treatments. What was cool was to see weather, flu seasons and a cyber attack having a negative impact on visitations/treatments. 

Aura Intel published a study to surface business trends in the Private Equity space from its workforce analytics platform. A couple of takeaways:

• Private equity hiring surged nearly 5× year-over-year in April 2025, with dramatic spikes closely tied to fund deployment and portfolio milestones—unlike the steady growth seen in the broader market. Top firms like BlackRock, General Catalyst, and TCI drove activity primarily in key financial hubs, but there’s also rising regional activity in states such as Massachusetts and Texas.
• There is a pronounced shift from just hiring investment roles to boosting operational and technical talent. Demand is rapidly growing for Data Scientists, Customer Success Specialists, and operational leaders—highlighting a move toward analytics-driven decision-making and embedded value-creation within portfolio companies, making hiring trends a real-time strategic signal for the industry’s next moves. 

SensorTower did a study on growth and customer traction of different LLM chatbots - it was nice to see demographic variations and cross platform usage of users of these different platforms. A more detailed study of the AI apps landscape is also available highlighting how apps are adapting to opportunities and potential threats from AI in their space.

Placer.ai did a study on consumer behavior patterns 5 years from COVID-19 pandemic, focusing on retail, dining entertainment, and office spaces during the first half of 2025 compared to pre-pandemic (2019) and 2024 levels. Key Takeaways:

• Retail and Dining Visits Exceed Pre-Pandemic Levels: Both retail and dining segments saw higher visits in H1 2025 compared to 2019, driven by major expansions from top chains and a consumer emphasis on value-driven and premium options. Consumers increasingly visit multiple chains to find the perfect product rather than relying on one-stop-shops.

• Bifurcation in Consumer Behavior Toward Value and Premium:

  There is a distinct split where value-focused retailers like dollar stores and off-price apparel chains have seen significant traffic growth, while mid-market apparel and casual dining suffer declines. Luxury apparel and fine dining segments, however, remain strong or have improved since 2019.

• Office Space Utilization Remains Low Despite Recovery Efforts:

  Visits to office buildings nationwide are still 33.3% below 2019 levels, indicating that hybrid and remote work models have permanently reshaped office usage. Although some cities show modest improvements thanks to Return to Office initiatives, the overall recovery in office attendance remains incomplete.

Is there alpha in forward looking statements on earnings calls? Check out Alexandria tech’s research and back test on it - a sharpe of 1.72!!

Lexis Nexus published a report on “GenAI Success in Financial Services”. Firms looking to adopt AI tech in their business will find this report very useful.

Is there a signal, an insight that can be extracted from code repositories? Saw an interesting piece from AnteData showing software security and infrastructure firms, like Akamai, benefitting from the AI boom as reflected in strong developer activity showing demand for fast and secure content delivery. There’s also a significant uptrend in activity for Autodesk and Dassault Systemes driven by changes to trade flows, reshoring, defense manufacturing demand, new types of simulation facilitated by AI productivity improvements.

Wondering what’s happening in the Yogurt category in China? Check out Win Win Networks Hot Topic Analysis for July, 2025.

Interested in the business of Music? Clearscore put out a report on the “Oasis” tour which shows TicketMaster spend index spiking, average transaction value peaking at GBP250, total spend index for food and drink service provider at Wembley is beating Taylor Swift’s Era’s tour. They also published a white paper on ExactOne - a consumer spend dataset,by analysing YoY revenue trends across 3 UK listed firms - a use case that quants might find very interesting.

Data Product Launches

Hatched Analytics: Launches Hatched-IQ - indices based on 70+ prop data feeds and designed for systematic strategies.

Aura Intel launches a conversational AI assistant for its workforce analytics platform making workflows more efficient and accurate for its clients.

Apptopia announces its new Mobile Performance Indices. MPIs are a proprietary blend of deep consumer signals for growth, engagement, and user segmentation, into a single index. A stock's MPI is the only metric you truly need to understand mobile data impact for any public company. Check out these indices in action for UBER, MELI, PTON and WISE.LN.

SensorTower: Analyze gaming performance across mobile, PC and console for a complete cross platform view using Video Game Insights.

BCMstrategy launched a data feed that firms can use to train their AI models on public policy issues and their impact. It’s one of kind feeds that has applications across the financial landscape.

Oxford Data Plan launched 4 new tickers - Dollar General, CVS Group, Cloudfare, JetBlue, Natural Grocers - and added new KPIs for Netflix - Paid Subs (UCAN) - and Roku - Global Platform Revenue.

Finster.AI launched an AI powered screener that removes the constraints of predefined filters and categories. You can use natural language to define your interest list and ideas.

Guideline launched a higher frequency version of its ad spend data. The product reduces lag and provides an early read on shifts in the ad market. 

Big Data Federation announces the launch of its “The Financial AI” platform that enables portfolio construction, backtesting and optimization of strategies through an intuitive chat based AI agent.

Repvue announced its Cloud Sales Index which is made up of 246 companies with 47K sales professionals ratings and over 2M data points.provides a pic of sales professionals succeeding and organizations outperforming their peers.

Buy Side News

Equity L/S hedge funds are experiencing significant growth - drawing $10B in first half of 2025 according to a note from HFR. According to data from PivotalPath, Equity L/S delivered 9.2% returns in the same period.

Man Group is reporting a record AUM of $193B at the end of June driven by strong quarterly inflows.

QRT, the Paris based quant fund, is continuing its diversification beyond quant by hiring equity researchers from the sell side.

According to a note from GS, hedge funds reduced their exposure to tech stocks in late July and, according to US government data, increased their bullish positions in gold to the highest level since April.

AQR Capital Management, led by billionaire investor Cliff Asness, has delivered double-digit returns across multiple strategies in the first half of 2025, including an 11.4% gain at the firm's flagship Apex multi-strategy hedge fund. ➜

Ken Griffin’s $66bn multi-strategy hedge fund major Citadel posted a modest 2.5% gain in the first half of 2025, falling behind smaller multi-manager rivals Balyasny and ExodusPoint, which returned 7.3% and 9.3%, respectively. ➜

Whetstone Capital, the $250m hedge fund known for its contrarian deep-value approach, posted a 21% return in May – its best monthly performance since inception – by doubling down on bets on unloved and mispriced tech stocks.

Bridgewater Associates’ flagship Pure Alpha fund gained 17% in the first half of 2025, outperforming the broader hedge fund industry amid a volatile macro backdrop, according to an unnamed source familiar with the fund's performance.

Walleye Capital is not accepting new investor capital as the $8B firm focuses on maintaining performance according to a report from Bloomberg.

Merger Arbs (Adage, Citadel, HBK) cashed in on the lucrative event driven play - the closing of Chevron’s acquisition of Hess.

New Silk Road Investment - a long standing Singapore hedge fund - is winding down due to withdrawal of capital by US institutions from Asian markets and declining performance.

University of California’s $190B investment arm has exited hedge funds investments - a move that started in the 2020 crisis.

Jain Global, launched last year with $5.3B in commitments, has lagged other established multi-strats with a 12 month return of just over 2.7% according to a report in the Financial Times.

According to a note from GS, hedge funds are rotating out of financial stocks and into consumer staples.

Quants - Marshall Wace’s TOPS, AQR’s Delphi L/S, Renaissance Institutional Equities each posted approx 11% in H1 2025 capitalizing on the move away from Mag 7 and return to fundamentals.

New Fund Launches

Carrhae Capital - A London based EM hedge fund is preparing to launch with a strategy that excludes China completely - in response to demand from investors from US to cut their exposure - with an expected AUM of $700M.

KR Capital, founded by Ravi Naresh, ex Marshall Wace Partner, is being seeded approx $3B by Millenium to run an equity L/S strategy.

Agave Capital Management Limited, a macro hedge fund, founded by former Citadel PM, is expected to launch with $1B in AUM this year.

Autonomy Capital launches Autonomy Stellar, a L/S fund designed to capitalize on global systemic shifts and price based tech disruption.

Saber Capital - a Zurich based Energy focused firm launched by Steve Barclay with backing from New Holland Capital.

Upcoming Events

BattleFin Data Discovery Day: October 9th, New York, NY; returning this fall! Reserve your spot early and save more. 

COLLIDE Data & AI Conference: September 30th - October 1st, Atlanta; data + AI focused. 

International Conference on Big Data and Smart Computing: October 30th, New York; big data.

BattleFin Discovery Day London: November 20th, London; alternative data focused.

At BattleFin Miami, BattleFin CEO Tim Harrington, Nimble Way CEO Uriel Knorovich and Tiny Fish CTO Mark Peng sat down to discuss what advances in AI technology means for financial alt data and what to expect in 2025.

Here are our top takeaways:  

Two Paths to AI-Driven Advantages in Alt Data 

1. Truly Alternative Data with AI

What’s truly alternative data in 2025? Increasingly syndicated data brings greater access to data than ever but also raises the question: is your alternative data truly alternative, or available to most players in the field and thus mainstream? Meanwhile, AI is enabling data consumption and parsing at unprecedented speed and scale, redefining “the art of the possible” in alternative data. 

The key question – what datasets, previously thought inaccessible, can now be brought into the fold? And is your team the one capable of sourcing these insights first? 

2. Extracting Greater Insights Faster from Alternative Data

Cleaning and Structuring Data: Turning complex, messy sources into ready-to-use data is often costly and slow. AI enables this process at a new speed and scale. For example, Tiny Fish uses AI to both extract and transform data from complex websites and files into data tables in one step. Nimble uses AI Agents to support Enterprise needs, from governance & compliance in the data gathering phase, to structuring, cleaning and validation in the processing phase.

Advanced Analytics and Specialized Tools: Tools like the Exabel platform exemplify the new paradigm of alt data analytics and consumption. Such specialized platforms consolidate datasets, map and tag these datasets to KPIs and leverage AI to produce insights and signals. Whereas the alpha generation process at each firm can be unique, having a platform like Exabel to get you 80% there seems to be the proven choice.  

The Specialization of AI and Enterprise Use Cases

The era of generalized AI training is nearing its peak. In 2025, we expect a significant shift toward post-training specialization, where AI systems are adapted to address the unique requirements of specific domains, such as finance, supply chain, or healthcare.

For instance, in finance, entity resolution is key—whether it’s resolving tickers or mapping relationships in corporate hierarchies. Contrast this with a supply chain scenario, where the focus might be on parsing multilingual procurement data. AI’s ability to specialize enables it to deliver contextually relevant insights across industries.

Small, hard-to-maintain automation scripts are increasingly being relegated in favor of solutions that offer Enterprises the customization, scale, compliance, and reliability they require. Nimble is building solutions towards rising Enterprise needs. For instance, Coca Cola faced a data interpretation challenge on whether to process multiple online storefronts of a business as unified or fragmented entities. Nimble’s AI-driven interpretation is tailored to use case needs.

The Biggest Challenges Ahead

Accuracy and Reliability 

Across sectors, delivering accurate and reliable datasets remains a foundational challenge. Consistency across every run is not just a preference—it’s a necessity for any viable enterprise solution.

Open AI Operator and Google Project Mariner provide a glimpse into the future of agentic automation. In 2025, computer-using-agents face a similar challenge to build the framework and infrastructure to be enterprise ready.

Trust and Adoption: Bridging the Gap

The AI industry still faces significant cultural and technical hurdles in building trust. Panelists drew parallels with self-driving cars: no matter how reliable the numbers suggest these systems are, public and institutional trust takes time to establish.

AI systems must incorporate intelligent fact-checking and validation to enhance reliability. Yet, the human-in-the-loop model remains essential. As AI rapidly evolves, its adoption will continue to require robust guardrails, transparent annotations of data processing, and the assurance of human verification.

Enterprise Requirements

Enterprises have unique working requirements, from stringent regulation and data accountability to high working volumes and unique use cases. Scaling up AI while maintaining performance, cost-effectiveness, and compliance is a substantial challenge facing the industry.

At BattleFin Miami, BattleFin CEO Tim Harrington, Nimble Way CEO Uriel Knorovich and Tiny Fish CTO Mark Peng sat down to discuss what advances in AI technology means for financial alt data and what to expect in 2025.

Here are our top takeaways:  

Two Paths to AI-Driven Advantages in Alt Data 

1. Truly Alternative Data with AI

What’s truly alternative data in 2025? Increasingly syndicated data brings greater access to data than ever but also raises the question: is your alternative data truly alternative, or available to most players in the field and thus mainstream? Meanwhile, AI is enabling data consumption and parsing at unprecedented speed and scale, redefining “the art of the possible” in alternative data. 

The key question – what datasets, previously thought inaccessible, can now be brought into the fold? And is your team the one capable of sourcing these insights first? 

2. Extracting Greater Insights Faster from Alternative Data

Cleaning and Structuring Data: Turning complex, messy sources into ready-to-use data is often costly and slow. AI enables this process at a new speed and scale. For example, Tiny Fish uses AI to both extract and transform data from complex websites and files into data tables in one step. Nimble uses AI Agents to support Enterprise needs, from governance & compliance in the data gathering phase, to structuring, cleaning and validation in the processing phase.

Advanced Analytics and Specialized Tools: Tools like the Exabel platform exemplify the new paradigm of alt data analytics and consumption. Such specialized platforms consolidate datasets, map and tag these datasets to KPIs and leverage AI to produce insights and signals. Whereas the alpha generation process at each firm can be unique, having a platform like Exabel to get you 80% there seems to be the proven choice.  

The Specialization of AI and Enterprise Use Cases

The era of generalized AI training is nearing its peak. In 2025, we expect a significant shift toward post-training specialization, where AI systems are adapted to address the unique requirements of specific domains, such as finance, supply chain, or healthcare.

For instance, in finance, entity resolution is key—whether it’s resolving tickers or mapping relationships in corporate hierarchies. Contrast this with a supply chain scenario, where the focus might be on parsing multilingual procurement data. AI’s ability to specialize enables it to deliver contextually relevant insights across industries.

Small, hard-to-maintain automation scripts are increasingly being relegated in favor of solutions that offer Enterprises the customization, scale, compliance, and reliability they require. Nimble is building solutions towards rising Enterprise needs. For instance, Coca Cola faced a data interpretation challenge on whether to process multiple online storefronts of a business as unified or fragmented entities. Nimble’s AI-driven interpretation is tailored to use case needs.

The Biggest Challenges Ahead

Accuracy and Reliability 

Across sectors, delivering accurate and reliable datasets remains a foundational challenge. Consistency across every run is not just a preference—it’s a necessity for any viable enterprise solution.

Open AI Operator and Google Project Mariner provide a glimpse into the future of agentic automation. In 2025, computer-using-agents face a similar challenge to build the framework and infrastructure to be enterprise ready.

Trust and Adoption: Bridging the Gap

The AI industry still faces significant cultural and technical hurdles in building trust. Panelists drew parallels with self-driving cars: no matter how reliable the numbers suggest these systems are, public and institutional trust takes time to establish.

AI systems must incorporate intelligent fact-checking and validation to enhance reliability. Yet, the human-in-the-loop model remains essential. As AI rapidly evolves, its adoption will continue to require robust guardrails, transparent annotations of data processing, and the assurance of human verification.

Enterprise Requirements

Enterprises have unique working requirements, from stringent regulation and data accountability to high working volumes and unique use cases. Scaling up AI while maintaining performance, cost-effectiveness, and compliance is a substantial challenge facing the industry.

Unveiling the BattleFin Alternative Data Challenge for Corporate Users – A Gateway to Innovation and Recognition

Welcome to the BattleFin Alternative Data Challenge – Corporate 2024 Edition, a competition designed to spotlight the most innovative and unique alternative data providers catering to corporate markets. As the world of data continues to expand, the demand for high-quality, actionable insights has never been greater. This competition offers a platform for data providers to showcase their products and potentially transform their market presence.

Learn More: https://www.battlefin.com/data-challenge-2024-corporate-chicago

How It Works

Apply: Data providers are invited to apply for free to this prestigious competition. The application process involves a simple sign-up where you submit basic information about your firm and update your product details on BattleFin’s alternative data platform, Ensemble. Each firm can enter up to three products into the competition. Detailed instructions will be provided after your initial submission.

Ready to Apply: https://web.battlefin.com/competition-corporate-2024

Evaluation: A distinguished panel of judges from prestigious firms will review the applications by October 1, 2024. Submissions are evaluated on a rolling basis, so applying early enhances your chances of selection. Judges will score each product based on novelty, application use cases, and completeness. The top-scoring product from each firm will move on to the next stage of the competition, with further rankings and selections made per category.

Selections: Up to five finalists will be chosen to present their data solutions at BattleFin Discovery Day in Chicago. Finalists enjoy numerous benefits, including stage presentations, tables in the innovation zone at the event, and a Gold sponsorship at a future Discovery Day event in London or Miami.

Competition Rounds and Scoring

• Initial Qualification: Based on the information submitted for each product.
• First Round: Scoring is based on documentation of the product’s novelty, application use cases, and completeness. Products that effectively demonstrate how their data can enhance operational efficiencies and open up new opportunities will receive higher scores.
• Second Round: Finalists will deliver a brief 5-minute presentation and demonstrate any analytics dashboards or insights at the Chicago event. This presentation is crucial in demonstrating the real-world application and value of the data.

Discovery Day – A Haven for Data Providers

Discovery Day isn’t just about competition; it's a valuable networking opportunity. As a participant, you will:

• Create a profile on the BattleFin Ensemble platform, making your data accessible to thousands of potential buyers.
• Gain tailored meeting schedules with data buyers, enhancing your visibility and business opportunities.
• Increase brand awareness and establish thought leadership within the alternative data community.
• Calculate the tangible ROI from event participation.

For newcomers to BattleFin, the New Data Provider Spotlight offers a chance to be featured on stage, presenting your data products to a vast audience of data buyers and industry leaders.

This competition is more than just a challenge; it's a spotlight on the future of alternative data in corporate decision-making. Join us to demonstrate how your data can shape the future of industries and elevate market standards. Don’t miss this chance to be recognized as a leader in the transformative world of alternative data.

Insights and Innovations: Recap of BattleFin's Corporate Discovery Day Event

November 2nd, 2023 – Lavan Midtown, NYC

In the heart of New York City, at the technologically infused venue of Lavan Midtown, with its impressive floor-to-ceiling projections, industry leaders gathered for BattleFin's first-ever Corporate Discovery Day Event. On November 2nd, 2023, an assembly of experts from renowned companies came together to discuss the ever-evolving role of data in shaping business strategies.

The Power of Data Analytics and Governance

Henry Schein: The day kicked off with insights from Daniel Entrup of Henry Schein, who brought to the forefront the critical need for data-driven ROI before investments. A proactive approach to budgeting that echoes the broader company goals was underscored, along with an unwavering commitment to data governance and privacy.

Vertical Knowledge:Rayne Gaisford of Vertical Knowledge carried the torch, presenting their adept skills in harnessing data from the retail and used car markets. The emphasis was on the merger of company-internal data with extensive pre-processed web-scraped data, painting a fuller picture for strategic decision-making.

Human Capital and Environmental Data

Revelio Labs: Ben Zweig from Revelio Labs steered the conversation towards the human element within corporations. By dissecting employment analytics, Revelio Labs posited a firm's human capital costs and provided deeper understanding through advanced analytics.

Weather Source: Weather patterns and their influence on business operations were artistically outlined by Craig Stelmach from Weather Source. Their predictions offer a granular view at the SKU/Store level, furnishing businesses with actionable data to tune their AI/ML algorithms for improved customer product recommendations.

Economic Indicators and Digital Customer Journey

Institute for Supply Management: Representing the Institute for Supply Management, Denis Wolowieckiturned the audience's attention to the macroeconomic indicators reflected in their data, forecasting the health and trends of markets.

CyberSyn: Alexander Izydorczyk from CyberSyn delved into the intricacies of the digital customer journey, demonstrating the importance of synthesizing diverse data streams into cohesive insights, with a nod to Snowflake for its data management capabilities.

Focusing on ROI and Real-Time Data

Domo: Mohammed Aaser of Domo illuminated the session with discussions on ROI-driven strategies, spanning forecasting to risk management, and the critical understanding of decision-makers' psychological profiles.

BIScience: A video presentation from BIScience expanded on the digital intelligence realm, offering a window into consumer behaviors and transactions across the digital sphere, bolstered by their comprehensive ad intelligence tools and real-time eCommerce data.

Broadening the Data Conversation

The event further expanded with discussions from John Edge of Broadhaven, John Harmon of Coresight Research, and Anduril Partners, where the utility of first-party data, alternative data use cases, and the importance of such data in the corporate sector were thoroughly explored.

This Corporate Discovery Day was more than a confluence of minds; it was a blueprint for the future of data in business. Each presentation was not only a lesson in the current state of data analytics but also a forecast of where data is steering the ship of corporate decision-making.

For attendees seeking to deepen their engagement or to participate in upcoming events, BattleFin remains an open door at events@battlefin.com. And as we anticipate next year's happenings, BattleFin's 2024 event lineup promises to bring even more to the table, forging paths for the future of corporate data usage.

Stay tuned for more updates and make sure you're a part of the next wave of data-driven transformation!

Unveiling the Future of Business: Battlefin's Corporate Discovery Day

In the realm of business innovation, staying ahead requires more than just adapting to change – it's about embracing the future with open arms. Enter Battlefin's Corporate Discovery Day, an event poised to revolutionize the way companies explore new horizons, forge partnerships, and unlock untapped opportunities. In this blog post, we dive into the significance of Battlefin's Corporate Discovery Day and the transformative impact it promises to deliver.

Catalyzing Connections: The Essence of Corporate Discovery Day

Corporate Discovery Day isn't just an event; it's a platform where innovation meets collaboration. It's where industry leaders, visionaries, and disruptors converge to share insights, forge alliances, and unearth the potential of tomorrow. The event serves as a bridge between established corporations and emerging startups, creating an ecosystem where fresh ideas can flourish and established players can leverage new technologies to thrive.

A Glimpse into the Future: What to Expect

Engaging Conversations:Corporate Discovery Day offers a rich tapestry of discussions, panels, and keynote speeches that dive into the latest trends, challenges, and breakthroughs across industries. Attendees can expect thought-provoking insights from luminaries who are shaping the future of business.

Startups Unveiled: One of the highlights of the event is the exposure it provides to innovative startups. Emerging companies get the chance to present their disruptive solutions, allowing established corporations to explore potential partnerships and investments that can drive mutual growth.

Networking Opportunities:The event's collaborative atmosphere encourages networking and relationship-building among attendees. From industry peers to potential investors, Corporate Discovery Day provides a fertile ground for meaningful connections.

Innovation Showcase: Attendees can explore an innovation showcase where groundbreaking technologies, products, and services are unveiled. This interactive exhibition space brings together cutting-edge solutions that have the potential to reshape industries.

Unlocking Synergies: Why Corporate Discovery Day Matters

Open Innovation: Traditional business models are evolving, and open innovation is becoming a cornerstone of success. Corporate Discovery Day embodies this philosophy by encouraging established companies to tap into the creativity and ingenuity of startups, fostering a culture of innovation.

Accelerating Growth: For startups, the event provides a unique chance to gain exposure, validate their concepts, and secure potential partnerships or investments that can accelerate their growth trajectory.

Evolving Industries: Industries are in a constant state of transformation. Corporate Discovery Day propels this evolution by showcasing disruptive technologies and novel approaches that challenge the status quo and spark new waves of change.

Knowledge Exchange: The event fosters a space where knowledge is freely exchanged. Attendees can gain fresh insights, learn about emerging trends, and discover best practices from industry experts.

Join the Journey: A Call to Action

As Battlefin's Corporate Discovery Day unfolds, it beckons companies to step into the realm of possibility, embracing collaboration, innovation, and the spirit of exploration. It's an invitation to be part of a movement that redefines the way businesses evolve, setting the stage for a future where alliances between giants and startups become a driving force of progress.

Are you ready to embark on a journey of discovery? Prepare to immerse yourself in a world where the unknown is embraced, boundaries are shattered, and the future of business is shaped by the collective power of innovation. Join Battlefin's Corporate Discovery Day and be a catalyst for transformation.

In an age where data reigns supreme, the concept of a "Data Map" has emerged as a valuable tool for organizations to navigate the vast landscape of information they collect, store, and utilize. As businesses expand globally, launching Data Maps becomes an intricate dance, especially when rolling out such initiatives in the complex and diverse regulatory environment of the European Union (EU). In this blog post, we will delve into the intricacies of launching Data Maps and explore the challenges and strategies associated with EU rollouts.

Understanding Data Maps: A Brief Overview

In an era characterized by an overwhelming deluge of data, businesses are grappling with the challenge of managing, protecting, and leveraging their information effectively. Enter the concept of Data Maps – a strategic tool that has emerged as a guiding star for organizations navigating the complex universe of data. In this blog post, we will delve into the significance of Data Maps and how they are shaping the way businesses operate in the digital age.

At its core, a Data Map is a visual representation that charts the intricate pathways of data within an organization. Much like a map guides travelers through uncharted territories, a Data Map guides businesses through their data ecosystem, illuminating the sources, flows, destinations, and interactions of data. This comprehensive view offers several invaluable benefits:

The EU Landscape: A Regulatory Mosaic

The European Union is renowned for its robust data protection regulations, with the General Data Protection Regulation (GDPR) leading the charge. Launching a Data Map within the EU requires a deep understanding of these regulations, as well as the various national adaptations and industry-specific rules. Failing to comply can result in hefty fines and reputational damage.

Challenges of EU Data Map Rollouts

Complexity of Regulations: The EU's regulatory framework is intricate, with nuances that vary between member states. Navigating the intricacies of GDPR, along with other regulations, demands a tailored approach for each rollout.

Cross-Border Data Flows: Many organizations operate across EU borders, necessitating careful consideration of how data moves between countries while adhering to the GDPR's stringent requirements.

Consent Management: Obtaining and managing user consent for data processing is a critical aspect of GDPR compliance. Ensuring clear and explicit consent mechanisms in various languages can be a logistical challenge.

Data Subject Rights: EU citizens' rights to access, rectify, and erase their personal data add layers of complexity to Data Map rollouts. Organizations must establish streamlined processes to address these rights promptly.

Strategies for Successful EU Data Map Rollouts

Thorough Assessment: Conduct a comprehensive assessment of your data landscape, identifying all data sources, flows, and potential risks. This forms the foundation of your Data Map.

Legal Expertise: Engage legal professionals with expertise in EU data protection laws. They can provide guidance on regulatory nuances and help ensure compliance.

Localization: Customize your Data Map rollout strategy for each EU member state, taking into account local regulations and language requirements.

Consent Mechanisms: Implement user-friendly and transparent consent mechanisms, ensuring individuals understand how their data will be used.

Training: Educate employees about GDPR requirements and the importance of adhering to the Data Map. A culture of data privacy and protection is vital.

Data Management Tools: Leverage data management tools and software to automate and streamline the Data Map process, making compliance easier to maintain.

In Conclusion

Launching a Data Map within the EU requires a meticulous approach, combining a deep understanding of regulations with proactive strategies for compliance. By navigating the complexities of the EU's data protection landscape, organizations can unlock the benefits of streamlined data management, enhanced customer trust, and minimized regulatory risks. As the EU continues to evolve its data protection framework, organizations must stay agile, adaptive, and committed to upholding the highest standards of data privacy and security.

In the ever-evolving landscape of artificial intelligence, where innovation knows no bounds, Intrepid Corporation is set to redefine the future with a groundbreaking revelation – the launch of Ensemble AI. This game-changing technology promises to reshape industries, empower decision-makers, and catalyze a new era of intelligence-driven solutions. In this blog post, we journey through the exciting introduction of Ensemble AI at Intrepid and explore the potential it holds for businesses and beyond.

A Symphony of Intelligence: Introducing Ensemble AI

Ensemble AI isn't just another addition to the AI toolkit; it's a symphony of intelligence that harmonizes various AI algorithms to create a single, dynamic solution. By leveraging the strengths of multiple algorithms, Ensemble AI produces more accurate, robust, and reliable outcomes than any individual algorithm could achieve alone. This approach revolutionizes the AI landscape, ensuring that businesses can make decisions with unparalleled confidence.

The Intrepid Approach: Pioneering Excellence

At Intrepid, innovation isn't just a buzzword; it's a way of life. The launch of Ensemble AI is a testament to the organization's commitment to pushing the boundaries of possibility. By merging diverse AI models and methodologies, Intrepid is setting a new standard for AI-powered solutions, fueling intelligent decision-making and driving transformative results for clients across industries.

Unleashing the Potential: Applications of Ensemble AI

Ensemble AI's impact stretches across sectors and domains:

Financial Predictions: Ensemble AI's predictive capabilities can empower financial institutions to make more accurate predictions regarding stock prices, market trends, and economic indicators, thereby guiding better investment strategies.

Healthcare Diagnostics: In healthcare, Ensemble AI can enhance diagnostic accuracy by combining various medical imaging analysis techniques, aiding doctors in making more informed and timely diagnoses.

Manufacturing Optimization: By analyzing data from sensors and machinery, Ensemble AI can optimize manufacturing processes, reduce downtime, and enhance overall production efficiency.

Customer Experience Enhancement: Businesses can leverage Ensemble AI to create personalized customer experiences by combining sentiment analysis, behavior prediction, and recommendation systems.

Bridging the Gap: Overcoming AI Challenges

Ensemble AI also addresses some of the challenges associated with single-model AI approaches:

Bias Mitigation: Combining multiple algorithms can mitigate bias inherent in any single model, leading to more fair and unbiased predictions.

Robustness: Ensemble AI's diversity makes it more resistant to adversarial attacks and anomalies, ensuring stability and reliability.

Generalization: By blending different AI models, Ensemble AI excels at generalizing insights across different datasets and scenarios.

Your Journey with Ensemble AI: Making Waves in Innovation

As businesses strive to make informed decisions in a world driven by data, Ensemble AI emerges as a beacon of promise. At Intrepid, the launch of this transformative technology signifies not just an innovation, but a commitment to driving excellence, fostering innovation, and redefining the possibilities of AI.

Intrigued by the possibilities? Get ready to embark on a journey with Ensemble AI at Intrepid. Whether you're seeking to optimize operations, enhance customer experiences, or elevate decision-making, Ensemble AI promises to be your ultimate ally, guiding you toward intelligence-driven success. Stay tuned as Intrepid paves the way for a future where AI's harmonious symphony creates waves of positive change across industries.

Top 5 Things That Drive Buyers Crazy - A Data Dictionary

In the fast-paced world of consumerism, buyers are constantly on the lookout for the best deals, seamless shopping experiences, and exceptional customer service. However, there are certain aspects of the buying process that can drive even the most patient customers to the brink of frustration. In this blog post, we'll explore the top five things that drive buyers crazy and delve into why these factors can make or break a purchasing decision. Welcome to the data dictionary of buyer exasperation.

1. Hidden Costs:

There's nothing worse for a buyer than thinking they've found a fantastic deal, only to discover unexpected charges at the checkout. Hidden costs such as shipping fees, taxes, handling charges, and add-ons can quickly turn a seemingly affordable purchase into an expensive ordeal. Buyers crave transparency; they want to know the total cost upfront, enabling them to make informed decisions without feeling deceived.

2. Complicated Checkout Processes:

The checkout process should be a breeze, yet many buyers find themselves tangled in a web of forms, account creations, and unnecessary steps. Lengthy and convoluted checkout processes can lead to cart abandonment as frustration mounts. A smooth and user-friendly checkout experience is paramount; buyers want their journey from cart to completion to be efficient, intuitive, and hassle-free.

3. Inaccurate Product Information:

Product descriptions that don't match the actual item can be a major source of aggravation for buyers. Whether it's mismatched colors, incorrect dimensions, or misleading features, inaccurate product information erodes trust and can lead to returns, negative reviews, and damaged brand reputation. Buyers expect accurate and detailed information to make informed choices, and any deviations can lead to disappointment.

4. Poor Customer Service:

When buyers encounter issues with their purchases, they rely on customer service to provide prompt and effective solutions. However, poor customer service, such as unresponsive support, lack of knowledge, or dismissive attitudes, can leave buyers feeling frustrated and undervalued. Exceptional customer service can turn a negative experience into a positive one, while subpar service can drive buyers away for good.

5. Out-of-Stock Nightmares:

Nothing is more vexing than finding the perfect product, only to discover it's out of stock. Whether it's due to inaccurate inventory tracking, poor restocking strategies, or high demand catching sellers off guard, out-of-stock items can lead to missed opportunities and leave buyers feeling disappointed. Buyers want reliability and accessibility; if a product is advertised, they expect it to be available.

In conclusion, the modern buyer is empowered, informed, and demanding. They seek seamless experiences, clear communication, and trustworthy interactions. Frustration can arise from hidden costs, complex checkouts, inaccurate information, poor customer service, and out-of-stock disappointments. To succeed in today's competitive marketplace, businesses must prioritize these pain points and proactively address them to create a shopping journey that delights rather than infuriates.

Remember, every interaction a buyer has with a brand shapes their perception and influences their future decisions. By addressing these top frustrations and catering to the needs of buyers, businesses can establish long-lasting relationships, foster loyalty, and set themselves apart in a crowded marketplace.