Frakture Pitch Deck: 11-Slide Pre-Seed Deck

Frakture’s deck is a classic example of a pre-seed technical pitch, leaning heavily on a macro labor shortage thesis to justify its existence. The company identifies a specific gap in the market: while many tools provide automation or analysis, few successfully turn data into 'timely, contextual, personal' action without heavy human intervention. By citing a projected shortage of 140,000 to 190,000 data analysts by 2018, the deck positions Frakture as a necessary labor-saving technology. However, the deck lacks critical investor information, including a team slide, financial projections, or a…

Key takeaways

• The deck identifies a projected shortage of 140,000-190,000 data analysts in the US by 2018 as a primary market driver (Slide 2).
• Frakture categorizes the competitive landscape into three buckets: Automation, Analysis, and Optimization, claiming no tool does all three well (Slide 3).
• The technology stack is explicitly defined, utilizing Redshift for column store databases and MongoDB for object stores (Slide 4).
• The product is currently in the prototype stage, with the interface layer built on Node.js to deliver results to desktops and tablets (Slide 4).
• The company defines its target market as CMOs and agencies with marketing budgets exceeding $1 million across at least four channels (Slide 5).
• Operational goals for the next 6-12 months include building a team of 5-7 people and working with a 'Gamma' cohort of clients (Slide 5).
• The deck omits a team slide, failing to identify the 'geeks' solving these engagement problems (Slide 5).
• There is no financial data, business model, or specific capital request included in the provided slides.

Frequently asked questions

What is the core problem Frakture is trying to solve?

According to Slide 2, the problem is twofold: good analytics are difficult to obtain due to a massive shortage of skilled data analysts (up to 190,000 by 2018), and turning those insights into action is technically difficult. Frakture argues that existing tools fail to bridge the gap between having data and creating 'relevant, timely, contextual, personal' engagement.

How does Frakture differentiate itself from competitors like Adobe or Marketo?

Slide 3 segments the market into Automation (e.g., Marketo, Eloqua), Analysis (e.g., GoodData, MediaMath), and Optimization (e.g., Optimizely, Hootsuite). Frakture claims that tools doing all three of these things well and simply do not exist, implying their solution is an all-in-one platform that handles the full lifecycle from data ingestion to campaign management.

What is the current state of Frakture's technology?

As of Slide 4, Frakture has a 'working prototype.' This includes ETL libraries for ingesting millions of records, a prediction engine using Redshift and MongoDB, and a Node.js interface layer. The tech is designed to produce interactive timelines and manage full campaigns across multiple channels.

Who is the ideal customer for this platform?

Slide 5 specifies a very narrow target market: CMOs, consultants, and agencies serving companies with at least a $1 million marketing budget. Furthermore, these companies must be active across a minimum of four channels and have 'Smart Analytics/Data folks' who can recognize the ROI of the tool.

What are the company's immediate milestones?

The company aims to expand its headcount to 5-7 employees within 6-12 months (Slide 5). During this same period, they plan to move their prototype into testing with a 'Gamma' cohort of clients to refine the product and build the brand as a 'simple, elegant solution' for marketing problems.

Frakture pitch deck: the facts

Company

Frakture

Stage

Pre-Seed

Slides

11

Sector

Marketing & AdTech

Frakture pitch deck PDF

The full Frakture deck is embedded on this page and can be read slide by slide in the browser — no download or account required. Each slide is covered in the breakdown above.

What the Frakture pitch deck was used for

This deck is a pre-seed / seed fundraising presentation (version 3) for Frakture, a Washington DC–based marketing data and automation company founded in 2013 that builds a predictive analytics and multichannel data engine for marketers. The deck (circa 2013) positions Frakture as a platform to integrate cross-channel marketing data, generate insights via segmentation and modeling, and automate the delivery of timely, personalized messages across channels. The company was seeking approximately $750k in seed capital to fund 6–12 months of work with a small cohort of clients to refine the product and business model.

Business model: Developer of a multichannel data engine and data warehousing service that deploys digital “bots” (automated jobs) to pull, clean, normalize and warehouse marketing and fundraising data from disparate platforms (email CRMs, ad platforms, payment gateways, social, SMS, etc.) for nonprofits and agencies.

Year

2013

Founded

2013

Headquarters

Washington, DC, United States

Round: Pre-Seed/Seed (early-stage round circa 2013 focused on initial team and product-market fit work).

Raising: The 2013-era deck states a goal of raising $750k in seed money to fund 6–12 months of work with a cohort of clients, but publicly available funding databases and profiles do not confirm that this specific round closed or provide details on investors or final amounts.

Industry: Marketing analytics, data warehousing and automation for communications and fundraising (Marketing & AdTech with nonprofit focus).

Use of funds as presented: According to the deck’s SlideShare description, the company aimed to use the seed funds to build an elite team, work intensively with a small cohort of clients for 6–12 months, and refine both the product and business model to ensure relevance.

What happened after the Frakture deck

Frakture appears to have remained a relatively lean, revenue-focused company rather than a heavily venture-funded startup: the 2013 deck sought a $750k seed round, but public datasets report no traditional primary funding, while later records highlight ongoing operations, partnerships with platforms like Mobile Commons, case-study clients, and a modest valuation associated with an M&A offer and a

• Frakture evolved from its early predictive analytics pitch into a specialized provider of data warehousing, bots-based a
• The company secured real-world adoption, including case studies such as the ONE Campaign and agency Mothership Strategie
• Frakture formed partnerships such as powering donation attribution analytics inside the Mobile Commons/Upland platform,
• Corporate databases list Frakture as founded in 2013, headquartered in Washington, DC, and operating with revenue, inclu

What the Frakture deck got right

• Strong timing thesis around big data, analytics maturity and marketing complexity. The deck clearly articulates a timely 2013 insight: digital advertising and social media had moved beyond hype, analytics and big data were becoming accepted, and professional experimentation techniques had matured, making automated cross-channel modeling and action both necessary and feasible. This framing ties the product tightly to macro trends in marketing and big data.
• Clear, differentiated technical approach using bots and a data warehouse. Frakture’s concept of using automated “bots” to continuously pull, clean, and normalize data from multiple marketing and fundraising systems into a data warehouse, then generating cross-channel reports and models, is a distinctive and concrete technical approach that differentiates from generic dashboards.
• Founders with relevant SaaS and nonprofit tech track record. The founders’ slide emphasizes prior experience founding and running a $9M SaaS CRM and a nonprofit SaaS communications platform, alongside social entrepreneurship and organizing experience, which signals strong domain knowledge in both SaaS and nonprofit/advocacy technology.
• Compelling linkage from analytics insight to automated marketing action. The deck connects big data “insight” directly to “action,” emphasizing that the company is “all about the Action,” which aligns with investors’ preference for products that not only analyze but also drive automated, revenue-impacting workflows.
• Disciplined, clearly articulated seed ask and milestone plan. The fundraising ask is tightly scoped—$750k for 6–12 months with a specified small client cohort to refine product and business model—showing discipline in capital needs and a focus on iterative learning rather than over-raising at a very early stage.
• Later case studies and partnerships validate the deck’s original thesis. Subsequent public case studies and partnerships, while post-dating the deck, retroactively validate the core thesis presented: organizations like ONE Campaign and Mothership Strategies use Frakture to centralize data and automate reporting, demonstrating that the initial vision had real market demand.

What could have been stronger

• Limited visibility into financial projections and long-term capital needs. The deck specifies a $750k seed target and a 6–12 month runway with a small cohort of clients but, based on the OCR excerpt and the publicly visible summary, does not provide detailed financial projections, unit economics, or a clear long-term capital plan beyond this initial period, making it harder for investors to assess scalability and capital efficiency.
• Scarce evidence of early traction in the deck. The narrative emphasizes big data, analytics maturity and cross-channel marketing but the OCR snippet and public summary do not show concrete traction metrics (e.g., existing paying customers, pilots, case studies, or revenue) at the time of the deck, which weakens proof of market validation for a 2013 pre-seed/seed raise.
• Target market definition in the deck may be broad. Although the company clearly targets organizations with large marketing budgets and multi-channel programs, the deck text available via OCR and description does not spell out a focused initial vertical (e.g., explicitly nonprofits vs. broader B2B marketers), potentially blurring the go-to-market story in early-stage fundraising.
• Competitive landscape and differentiation not clearly documented in the deck. The deck’s framing around big data, predictive analytics, and cross-channel modeling was differentiated in 2013, but the materials visible do not directly benchmark against existing marketing automation or analytics platforms (e.g., by naming competitors or showing feature comparisons), which investors often expect to understand the defensibility of the approach.
• Go-to-market team and hiring plan appear high level. From the OCR and description, the deck emphasizes the founders’ prior SaaS and nonprofit platform experience but does not obviously highlight any dedicated commercial leadership (sales, customer success) or specific hiring plan beyond “elite team,” leaving some ambiguity about go-to-market execution capacity.

How an investor would read this deck

What draws attention

• The deck’s ask is **$750k in seed funding** for 6–12 months of work with a small cohort of clients, which is a modest round size aligned with early iterative product-market fit work.
• Frakture’s focus on **automated data integration and warehousing for nonprofits and agencies** is a niche with demonstrable pain around siloed data, offering a potentially sticky B2B SaaS/service hybrid.
• The founders’ background includes **building prior SaaS CRM and nonprofit communications platforms**, suggesting domain expertise and familiarity with both commercial and nonprofit tech markets, as highlighted on the “Why we’re the ones to solve it” slide.
• The deck’s early emphasis on **bots-based automation and cross-channel attribution** anticipated later trends in marketing ops and fundraising analytics, which may appeal to investors who value early thematic insight.
• Later evidence of adoption by organizations like **ONE Campaign** and partnerships such as with Mobile Commons/Upland demonstrates that this product category can secure credible nonprofit and political clients, validating the general thesis of the deck even if not contemporaneous with the raise.

Risks that stand out

• Third-party funding datasets indicate little or no traditional venture funding, suggesting that either the 2013 seed round did not close as envisioned or capital remained limited, which can constrain product development and go-to-market capacity.
• The company operates in a market with many generic marketing automation, analytics and CDP platforms; without clear differentiation or proprietary technology, Frakture could face intense competition from larger vendors offering overlapping capabilities.
• Frakture’s core customer base appears heavily concentrated in nonprofits and political/digital agencies, which may expose the company to budget cyclicality (e.g., election cycles, fundraising climates) and sector-specific purchasing dynamics.
• If the business model involves significant services alongside software (custom warehouses, bespoke reports), scalability and margins may be lower than pure-play SaaS, potentially limiting venture-scale outcomes.
• Dependence on integrations with third-party platforms (CRMs, ad networks, SMS tools) creates platform risk; API changes or vendor consolidation could require ongoing engineering investment to maintain compatibility.

Questions this deck invites

• What, if any, primary capital did Frakture ultimately raise around or after this deck, and on what terms, given that some secondary datasets list $0 in traditional funding despite a stated $750k seed target?
• What were the founders’ prior SaaS CRM and nonprofit communications platforms (mentioned in the deck), and what were their outcomes (exits, scale, revenue), to better assess founder-market fit and execution track record?
• At the time of the deck, how many customers or pilots were in place, in which verticals, and on what pricing model (SaaS subscription vs. services-heavy), and how did this evolve over subsequent years?
• How does Frakture’s platform technically integrate with major CRMs, ad platforms and SMS tools (APIs, connectors, warehouse schema), and what are the switching costs and retention metrics for current clients?
• What is the competitive landscape for nonprofit-focused data warehousing and marketing analytics (including general CDPs and marketing automation suites), and where does Frakture sit on pricing, features, and support relative to horizontal

What founders can take from the Frakture deck

• A clear, concrete funding ask—such as Frakture’s $750k seed target tied to a 6–12 month runway and a specific plan to work with a cohort of clients—helps investors quickly understand scope and intended milestones for a pre-seed/seed round.
• Positioning around a specific pain point (siloed marketing and fundraising data across many tools) and a distinctive mechanism (bots feeding a data warehouse plus cross-channel reporting) can make a complex technical product more tangible for investors and customers.
• Highlighting founders’ prior domain experience—in this case, leading SaaS CRM and nonprofit communications platforms—can strengthen credibility when entering a nuanced vertical like nonprofit marketing analytics.
• Early decks that emphasize big-picture vision (predictive analytics, cross-channel modeling) benefit from pairing that vision with concrete early traction or pilots; later case studies and partnerships demonstrate how valuable such validation becomes.
• Focusing on a specific customer segment (nonprofits and digital agencies) can yield strong product-market fit, but pitch materials should still articulate how this niche can support a sustainable and scalable business over time.
• Building a data infrastructure product (warehouse, bots, cross-channel reporting) often leads to blended software-and-services offerings; decks should clarify how much is standardized SaaS versus custom work to address investor concerns about scalability and margins.

Frakture pitch deck: common questions

What does Frakture do?

Frakture is a multichannel data engine and data warehouse platform that uses automated “bots” to pull together data from disparate systems—such as CRM, email, social media, ad platforms, SMS and payment processors—into a unified warehouse, then provides cross-channel reporting and analytics for marketing and fundraising programs. It primarily serves nonprofits and digital agencies that need to coordinate and evaluate complex digital outreach and fundraising efforts.

Who is Frakture’s target customer?

Frakture focuses on nonprofits and digital agencies that run multi-channel programs with significant marketing or fundraising budgets and multiple platforms—for example, organizations using email CRMs, Facebook, Google Ads, SMS tools, and payment processors who need integrated reporting and attribution.

How much money was Frakture trying to raise with this deck, and did they close the round?

According to the original Frakture deck hosted on SlideShare, the company sought to raise approximately $750k in seed funding to build an elite team and work for 6–12 months with a small cohort of clients to refine the product and business model. Public secondary sources focused on the company’s funding and valuation history do not list any completed primary equity funding rounds and in some cases explicitly show $0 of traditional funding, so there is no clear evidence that this specific $750k seed round closed.

What problem does Frakture solve and how?

Frakture’s deck and subsequent positioning emphasize that they deploy “bots” to automate data ingestion and transformation from multiple platforms, centralize this data into a warehouse, and then provide cross-channel reporting and attribution capabilities. This allows organizations to analyze campaign performance across email, social, ads, SMS and donations, attribute revenue to specific messages or campaigns, and reduce manual data wrangling workloads.

What happened to Frakture after this deck—did the company succeed?

Frakture’s deck describes itself as a predictive analysis and cross-channel automation platform seeking seed capital around 2013. Subsequent public information shows Frakture operating as a Washington DC–based provider of data warehousing and automation for nonprofit and fundraising-focused organizations, with long-term partnerships (e.g., with Mobile Commons/Upland) and case studies like ONE Campaign and Mothership Strategies using its bots and warehouse for cross-channel analytics and attribution. However, available third-party datasets suggest the company did not raise traditional venture rounds and instead appears to have grown via revenue and partnerships.

Sources

Funding and outcome facts on this page were researched on 2026-08-22 from the pages below.

• Frakture - Data Warehousing - Do More With Robots.
• What is Frakture?
• Frakture, Inc - LinkedIn
• Frakture Data Solutions
• ONE Campaign
• Data Powered by Frakture: An Agency Case Study on Mothership Strategies
• Trusted ROI at your fingertips
• Frakture Deck

Frakture pitch deck slides

What each slide of the Frakture pitch deck says

Slide 2

Data Sources: A Marketing is being transformed due to the f| flood of data. Harnessing that power is still a [4 problem. Aggregating data ACROSS channels and technologies is hard. 6 5 % of Organizations say that integrating (1] multiple data sources is a challenge TOO many channels, Ti 2 Net too many data sources C] ® ©

Slide 3

#2 Good analytics are difficult to get > Lack of Human Resources 2018 Data Analyst Shortage > 140,000-190,000: Shortage by 2018 of people with deep analytical skills among US Companies FrirTYrTr —— IN > Benefits are tangible, but not always obvious HHH k giv > Lack of good, easy cross-channel modeling tools wire Re IIe RETIY =190,000 teeteeeeeateeeeaee” #3 Turning insight i ! AeseprtretanTeeg” urning insight into action a 4 o t > Turn data into something: Relevant, Timely, Contextual, Personal - A fancy dashboard is insufficient > Being an expert in each of these channels is impossible Tools that do all three of these things well and make it simple do not exist Source: http://blog.neolane.c…

Slide 4

Why it's solvable NOW > > B 2 B . Digital Advertising and Social Media have moved beyond hype Public acceptance of Analytics and Big Data Professional data analysis techniques and controlled experimentation have matured \Y

Slide 5

\ ~~ SN | 1 extreme Tin | \ ro | A \ IR pin 24 optimal LEB @ GRAPHEFFECT ff SW i P | =" collective d UNIFIED __ SAILTHRU K| suite | Marketo | \ radian Rappnexus \ 4 Adobe. MarketShare 4» GoodData Automation companies are focused Optimization companies improve the on making work easier for marketers. impact of marketing, generally in a This includes dashboards, process Ana lysi S small number of channels. Speeding automation, action triggers, up web page delivery, targeting ads, integration with CRM, etc. Analysis companies make marketers testing infrastructures, etc. all fall better by delivering new or better under Optimization. statistics for them to make decisions on. Predictive analytic…

Slide 6

Why we're the ones to solve it > Chris Lundberg Co-Founder, CEO Geek with People Skills. I build highly scalable technology that people actually need to do their jobs better and scalable companies to support them. April Pedersen Co-Founder Social Entrepreneur addicted to helping people figure out how to use technology for meaningful engagement. Leader, organizer, marketer, rabble rouser. We are : Experienced Tech & Social Entrepreneurs who enjoy major disruption in industries & helping groups grow and better engage with their audiences. We're all about the Action. Together we have: ACTION Founded and ran $9M SaaS CRM and Founded and ran nonprofit SaaS to Communications Platform with 2000 ma…

Slide text above is read directly from the Frakture deck PDF embedded on this page.

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