What is the core value proposition of Datelytics?

Datelytics aims to move dating away from 'shallow' swiping by focusing on shared activities. By integrating third-party events and using social media data to analyze interests, the app facilitates real-world meetings centered around specific plans, such as salsa lessons or tech meetups, rather than just digital conversation.

How does Datelytics plan to make money?

The business model is commission-based. According to slide 11, the company intends to 'pay their bills' by taking a cut of every transaction or booking made through the app. This suggests an affiliate or marketplace model where users buy tickets to events or dinners directly within the Datelytics interface.

What technical components power the app?

The deck highlights a 'Facebook Analyzer' as the primary technical driver. This tool is intended to scrape or analyze a user's social data to understand their interests, which then informs the selection of people or events the app recommends to the user.

Who are the founders of Datelytics?

The team consists of Brandon T. Luong, serving as CEO, and Phaka Dludla, serving as COO. The slides include photos of the founders—one featuring a Google Glass wearable—but do not list any prior professional achievements, education, or industry expertise.

What is missing from the Datelytics pitch deck?

The deck is missing several standard venture components: a market size analysis (TAM), a competitive matrix, a financial forecast, and a clear funding ask. It also lacks a 'Why Now' slide and any evidence of traction, such as beta user feedback or partnership agreements with event providers.

Datelytics Pitch Deck: 12-Slide Breakdown

See all 12 slides of the Datelytics pitch deck, with a slide-by-slide teardown of what the deck does well and where it falls short.

Datelytics presents a 12-slide pitch deck focused on solving the 'shallow' nature of modern dating apps by integrating third-party activities and events. The company identifies core problems such as spam bots, awkward dates, and superficiality, proposing a solution that uses a 'Facebook Analyzer' to match users based on interests and then suggests specific activities to attend together. The business model is purely commission-based, earning revenue from transactions made through the app. While the deck is visually simple and uses meme-style imagery to convey pain points, it lacks critical inv…

Key takeaways

The company identifies three primary pain points in dating: spam bots/weirdos, awkward dates, and superficiality (Slides 3-5).
The solution is an app that aggregates activities from third-party programs for singles to meet (Slide 6).
Product functionality allows users to toggle between finding a specific date or finding an event to attend (Slide 8).
The 'magic' behind the platform involves a Facebook Analyzer to determine user interests (Slide 9).
Revenue is generated through commissions earned on transactions made within the app (Slide 11).
The deck contains no mention of current traction, user numbers, or growth metrics.
There is no competitive landscape slide to address how Datelytics differs from incumbents like Tinder or Meetup.
The team slide introduces the CEO and COO but provides no bios, past experience, or credentials (Slide 12).

The Datelytics Pitch Deck: A Narrative-Heavy Approach to Dating

Datelytics enters the crowded dating app market with a specific thesis: the current experience is broken because it is superficial and leads to awkward real-world interactions. Their deck is structured as a narrative of pain and relief, using large-scale imagery and minimal text to drive home the emotional frustration of modern dating. However, as a fundraising tool, it leaves many quantitative questions unanswered.

Slide 1: Title Slide

The deck opens with the Datelytics logo and the tagline: "Find activities for singles to meet." The visual includes a smartphone mockup showing a feed that includes a tech meetup, a dinner for two at a restaurant called 'Vinny's' with a 'BUY' button, and a new match notification. This immediately establishes the product's hybrid nature as both a dating tool and an event marketplace.

Slides 2-5: The Problem Statement

Datelytics uses a four-slide sequence to define the problem. Slide 2 asks, "What's the problem with dating apps?" overlaid on a black-and-white image of Jay-Z. Slide 3 claims apps are "Full of weirdoes, creeps or spam bots," using a comedic image of three men with binoculars. Slide 4 addresses the user experience, stating they "Don't solve awkward dates," while Slide 5 characterizes the entire industry as "Completely Shallow." This section is effective at identifying common grievances, but it lacks data or research to quantify the scale of these issues.

Slide 6: The Solution

The solution is stated plainly: "Our solution is to create a dating app that finds activities from third party programs for singles to meet." The slide features a binocular icon, reinforcing the idea of 'finding' or 'scouting' opportunities rather than just passive swiping. It positions the company as an aggregator of third-party content.

Slides 7-8: Product Functionality

Slide 7 shows the dual-path nature of the app. Users can find "a date" (viewing individual profiles like 'Carla') or "an event" (viewing listings like 'Salsa lessons' or '2014 Year End Awards'). Slide 8 provides a three-step process for the 'magic' of the platform: 1) Facebook Analyzer, 2) Select a person or an event/daily deal, and 3) Find something to do with the new match. This confirms that the app relies on the Facebook API for interest-based matching.

Slide 9: Target Audience

Slide 9 features a group photo of diverse individuals with the caption: "We're here for single folks who enjoy their lives, but looking to share it with someone." This slide attempts to define the brand identity—social, active, and grounded—but it does not provide demographic data or a specific target persona (e.g., urban professionals aged 25-35).

Slide 10: Business Model

The monetization strategy is presented on Slide 10: "We will be paying our bills by every commission earned through our app." The background is a pile of hundred-dollar bills. While the revenue stream is clear (transactional commissions), the deck does not explain the expected take rate, the cost of customer acquisition (CAC), or the lifetime value (LTV) of a user.

Slide 11: The Team

The team slide introduces Brandon T. Luong (CEO) and Phaka Dludla (COO) . The photos are informal. Crucially, there is no text describing their backgrounds, previous startups, or technical skills. In a seed-stage pitch, the team's ability to execute is often the most important factor for investors, making this omission significant.

Slide 12: Conclusion

The deck ends with a "Thank You" slide, repeating the logo, Twitter handle (@Datelytics), and website (www.datelytics.co). There is no call to action or specific request for capital.

What Works in the Datelytics Deck

Clear Problem Identification: The deck does a good job of tapping into the emotional frustrations of dating app users. By focusing on 'awkwardness' and 'shallowness,' they create a clear 'enemy' for their solution to fight. · Simple UI Presentation: The mockups on Slides 1 and 7 clearly show how the product works. The 'BUY' button next to events immediately explains the transactional nature of the platform without needing a long explanation. · Focused Value Prop: The deck doesn't try to be everything to everyone. It is strictly about activity-based dating, which differentiates it from general-purpose apps like Tinder.

What is Missing from the Datelytics Deck

Market Size: There is no mention of the Total Addressable Market (TAM). Investors need to know if this is a billion-dollar opportunity or a niche hobbyist app. · Traction: The deck contains zero metrics. Even if the app is in pre-launch, data on waitlist signups, pilot partnerships with event venues, or user interview insights would provide much-needed validation. · Competitive Analysis: The dating space is incredibly crowded. Datelytics fails to mention how it will compete with incumbents who are also moving into 'experiences' (like Bumble's 'Bumble Bizz' or 'Bumble BFF' features). · Financial Ask: A pitch deck is a tool for a transaction. By omitting the amount of money they are looking to raise and what they plan to do with it, the founders miss the opportunity to set the stage for a deal. · Founder Credentials: The team slide is purely visual. Without knowing if the founders have experience in software development, marketing, or the hospitality industry, it is difficult for an investor to assess execution risk.

What Founders Should Copy

The 'Problem-Solution' Bridge: The transition from Slide 5 (Shallow) to Slide 6 (Activity-based solution) is a textbook example of how to frame a solution as the direct antidote to a specific pain point. · Visual Simplicity: The deck avoids 'wall of text' syndrome. It uses large fonts and clear headers, ensuring that even a quick skim allows the reader to understand the core concept. · Direct Revenue Model: Many early-stage apps are vague about how they will eventually make money. Datelytics is refreshingly honest about its commission-based model, even if it lacks the supporting unit economics.

Frequently asked questions

What is the core value proposition of Datelytics?: Datelytics aims to move dating away from 'shallow' swiping by focusing on shared activities. By integrating third-party events and using social media data to analyze interests, the app facilitates real-world meetings centered around specific plans, such as salsa lessons or tech meetups, rather than just digital conversation.
How does Datelytics plan to make money?: The business model is commission-based. According to slide 11, the company intends to 'pay their bills' by taking a cut of every transaction or booking made through the app. This suggests an affiliate or marketplace model where users buy tickets to events or dinners directly within the Datelytics interface.
What technical components power the app?: The deck highlights a 'Facebook Analyzer' as the primary technical driver. This tool is intended to scrape or analyze a user's social data to understand their interests, which then informs the selection of people or events the app recommends to the user.
Who are the founders of Datelytics?: The team consists of Brandon T. Luong, serving as CEO, and Phaka Dludla, serving as COO. The slides include photos of the founders—one featuring a Google Glass wearable—but do not list any prior professional achievements, education, or industry expertise.
What is missing from the Datelytics pitch deck?: The deck is missing several standard venture components: a market size analysis (TAM), a competitive matrix, a financial forecast, and a clear funding ask. It also lacks a 'Why Now' slide and any evidence of traction, such as beta user feedback or partnership agreements with event providers.

Cover slide of the Datelytics pitch deck — Datelytics pitch deck, slide 1

Datelytics pitch deck: the facts

Company: Datelytics
Slides: 12

Datelytics pitch deck PDF

The full Datelytics 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 Datelytics pitch deck was used for

This deck is a revitalized version of the original Datelytics pitch deck published on SlideShare in October 2013 by founder Brandon T. Luong, describing a new dating app that analyzes users’ social media data to match compatible candidates and suggest date activities. It positions Datelytics as an alternative to existing dating apps that are criticized for superficial swiping and awkward, poorly planned dates. The deck outlines a freemium business model with affiliate and advertising revenue and presents survey data claiming strong user interest and a projection that Datelytics could become a $600 million business within five years. There is no externally verified information tying this deck to a specific announced funding round or investors.

Business model: Freemium dating application that analyzes users’ social network data to match compatible candidates and recommend date activities, with planned revenue from affiliate programs and advertising.

Founders: Brandon T. Luong
Industry: Online dating / consumer internet,

What the Datelytics deck got right

Distinct positioning around activity-centric dating. The deck articulates a clear differentiation from traditional dating apps by emphasizing **shared activities** and personalized date suggestions based on social data, not just matching profiles. This positions Datelytics as offering a more complete “digital dating agency” experience.
Compelling use of social data for matching and recommendations. By integrating social network sign-in and leveraging likes, check-ins, and interests, the concept promises more contextually relevant matches and date ideas than basic profile fields alone. This social-data-driven angle taps into a rich, underutilized signal set for dating at the time.
Recognizable and scalable monetization model. The deck presents a clear freemium model with affiliate and advertising revenue as initial monetization channels, aligning with proven approaches in online dating and consumer apps. This offers investors a familiar and potentially scalable path to revenue if user engagement is strong.
Early indication of user interest via survey data. Including survey results that reportedly show over 90% of respondents interested in trying the app provides at least some validation of the concept and suggests the team made an effort to test initial interest.
Strong articulation of problem-solution fit. The narrative explicitly identifies pain points with existing dating apps (e.g., awkward dates, low-quality matches), then proposes a concrete solution integrating matching and activity planning. This problem-solution clarity enhances the deck’s persuasiveness.
Evidence of iteration and refinement of the pitch deck itself. The revitalized pitch deck indicates iterative refinement of the story and visuals, which can signal persistence and learning in how the founder presents the opportunity to investors and partners.

What could have been stronger

Limited external validation of user demand. Beyond internal survey results claiming that over 90% of respondents would try the app, the deck does not provide external validation (such as market pilots, waitlist size, or partnerships) to support demand for a social-data-driven dating app. This makes it hard for investors to assess whether interest extends beyond a small sample controlled by the team.
No discussion of privacy, data rights, or platform risk. The deck references using users’ social networks to extract detailed information on likes, locations, and activities, but it does not address data privacy, consent mechanisms, API dependency risks, or compliance with platform policies (e.g., Facebook’s terms). For a product built on social data, investors would likely expect a clear strategy for handling privacy and platform risk.
High-level monetization narrative without financial underpinnings. While the deck mentions a freemium model with affiliate programs and advertising, it does not quantify key economic assumptions such as expected take rates, ARPU, customer acquisition costs, or the timing and sources of revenue growth. The projection that the business could reach $600 million within five years is not linked to a concrete financial model.
Unclear technical depth and defensibility. The deck describes analyzing users’ social networks and recommending personalized date activities, but it does not outline the underlying technology stack, algorithms, or defensibility beyond access to social data. Without a clear technical roadmap or IP angle, investors may question how easily competitors could replicate the concept.
Limited visibility into the broader team. Publicly available materials do not identify a broader founding team, advisors, or key hires beyond Brandon T. Luong’s name and contact information. For investors, the absence of a clearly presented team can raise concerns about execution capacity in product, engineering, and growth.

How an investor would read this deck

What draws attention

The deck’s core hook is leveraging **social network data** (likes, check-ins, activities) to create both better matches and personalized date activities, positioning Datelytics as more than a simple matching app.
The problem framing focuses on pain points with existing dating apps, such as encounters with “creeps” and poor-quality dates, which helps explain why an activity-centric approach might resonate.
The inclusion of survey data claiming over 90% of respondents would try the app serves as an early signal of interest, even if the methodology is not detailed.
The freemium plus affiliate and advertising model fits established online dating monetization patterns and suggests multiple revenue streams if user engagement is strong.
The revitalized deck indicates ongoing iteration on the story, suggesting the founder continued refining the pitch and possibly testing positioning with different audiences.

Risks that stand out

Reliance on third-party social networks for key data introduces platform risk—changes to API access or terms could significantly degrade the product or shut off critical signals.
The business model depends on both user scale and engagement to unlock affiliate and advertising revenue, yet the deck does not provide evidence of traction or detailed unit economics.
Online dating is a highly competitive space with large incumbents and numerous niche players, so standing out and achieving efficient user acquisition could be difficult without a clear, defensible edge.
Using detailed social data for dating recommendations may raise user trust and privacy concerns, and missteps here could damage brand reputation and limit adoption.
The lack of publicly documented funding, product launch, or later milestones suggests that execution or market fit challenges may have prevented Datelytics from scaling after this pitch, increasing perceived risk for investors looking back at the deck.

Questions this deck invites

What concrete evidence exists beyond the cited survey (e.g., landing page conversions, beta signups, or pilot cohorts) to demonstrate demand for an activity-centric dating app?
How would Datelytics manage user privacy, data permissions, and compliance with changing social network APIs, particularly if platforms restrict access to the detailed behavioral data the app depends on?
What technical approach and recommendation algorithms underpin the matching and activity suggestions, and how do they perform compared to existing dating products or event discovery services?
How does the team plan to acquire users efficiently in an already crowded dating market, and what early traction (installs, active users, retention) did they achieve, if any, after this deck?
Are there any strategic partnerships with event platforms, affiliate networks, or venues that validate the affiliate revenue thesis and provide preferred economics?

What founders can take from the Datelytics deck

A clear narrative that connects **problem**, **solution**, and **differentiation**—here, moving from shallow profile swiping to social-data-driven activity planning—helps a dating startup stand out in a crowded market.
Grounding the pitch in concrete user workflows (signing in, seeing candidates based on shared pages and check-ins, then selecting date activities) can make an abstract data-driven product more tangible to investors.
Including even basic survey data on user interest can strengthen the story, but its impact depends on explaining methodology and connecting it to actual product tests or funnels.
Projecting large market outcomes (such as becoming a $600 million business within five years) must be supported by explicit assumptions and financial logic to be credible with investors.
A product that relies heavily on third-party data and APIs needs to proactively address platform risk, privacy, and regulatory considerations in the deck, not just in diligence conversations.
Revitalizing an older pitch deck with updated framing and design, as seen with the revitalized Datelytics deck, can extend the life of existing content and refine messaging, but investors will still look for fresh traction and concrete milestones beyond the narrative.

Datelytics pitch deck: common questions

What is Datelytics?

Datelytics is a proposed **dating app** that analyzes users’ social network data (such as pages liked, check-ins, and activities) to match compatible people and recommend suitable date activities. The concept is to provide not just matches, but also curated date ideas based on social data.

How does Datelytics work?

According to the pitch deck, Datelytics signs users in with their social networks, extracts information about likes, check-ins, and activities, then surfaces candidates who share overlapping interests and locations. After a user chooses a candidate, the app recommends specific date activities that align with that person’s preferences, aiming to create better offline dating experiences.

What is Datelytics’ business model?

The deck states that Datelytics will use a **freemium** model and generate initial revenue from affiliate programs and advertising. For example, it implies earning referral or affiliate fees when users book activities or make purchases related to suggested dates, as well as displaying carefully selected ads intended not to damage the user experience.

Who is behind Datelytics?

The SlideShare deck credits **Brandon T. Luong** and lists contact details including a phone number and email, along with the Twitter handle @Datelytics and an AngelList URL (angel.co/datelytics), indicating he is the founder or primary presenter. No additional verified co-founders or team members are identified in external sources.

Did Datelytics ever raise funding or launch as a product?

There are no credible external records of Datelytics completing a funding round or reaching a specific outcome such as acquisition or shutdown. The available information is primarily the 2013 pitch deck and a later revitalized version on SlideShare, plus references in another deck. Based on current research, Datelytics does not appear in major funding databases or press announcements, so its later trajectory is undocumented in public sources.