product overview
Edkwery is a B2B2C education intelligence platform built to help institutions discover, evaluate, and attract high-potential students. On the B2B side, it offers a powerful sourcing engine that enables schools, universities and training providers to identify ideal candidates using behavior, academic history, and intent signals. The platform includes a smart ad engine for targeted outreach and lead acquisition.
On the B2C side, Edkwery acts as a “LinkedIn for education,” letting students explore programs, compare institutions, and apply with one click—streamlining long, repetitive application processes across universities.
ownership
Led 0→1 development of Edkwery’s core platform, driving data automation, enrichment, and growth tooling.
- Built and scaled a SpaCy-based enrichment engine with autonomous scraping bots to keep institute and course data continuously updated across thousands of sources
- Designed a smart outreach engine to automate student matching and lead generation across institutions
- Launched a microtransaction-powered ad engine, optimizing cost-per-student-acquisition by segment and behavior
- Defined platform structure for dual B2B/B2C use, supporting growth across institutions and learners
- Enabled real-time profile enrichment, auto-tagging, and lead scoring to improve match quality and conversion efficiency
Market Sizing & Opportunity
The global EdTech market is projected to reach $348B by 2030 (13.3% CAGR), with online education alone expected to grow from $83B to $185B by 2029. Yet, institutions struggle to efficiently source qualified students, while applicants face fragmented, repetitive processes. Edkwery addresses both gaps—offering a B2B engine for data-driven student targeting and a B2C platform for one-click applications—streamlining recruitment and discovery in a fast-growing market.
Personas, Use Cases & Solution footprint
Institutions & Universities (B2B)
Use Case: Identify and acquire qualified students through enriched data and precision outreach
Challenges:
- Traditional student recruitment spends $2,000+ per enrollment, often wasted on unqualified leads
- CRMs lack real-time enrichment, forcing teams to manually vet leads and manage fragmented channels
- No visibility into student behavior, engagement signals, or program-level attribution
Solution Footprint:
- Spacy-based enrichment engine auto-tags academic interests, behavior, and location intent from multiple sources
- Microtransaction-powered ad engine triggers smart outreach based on match score, cutting CAC by up to 45%
- Institution dashboard with filters, lead scoring, and conversion analytics—enabling segment-level targeting and campaign ROI tracking
Students & Applicants (B2C)
Use Case: Discover and apply to matched programs instantly, without repeating the same form multiple times
Challenges:
- Average student completes 6–10 separate applications, each with redundant forms and limited feedback
- Poor fit leads to high churn—over 30% of students change or drop out due to misaligned choices (Inside Higher Ed)
- Most platforms offer search, not guided decision-making or personalized recommendations
Solution Footprint:
- One-click apply engine using pre-filled verified profiles and smart eligibility checks
- Course comparator with structured data on outcomes, fees, and rankings
- AI-driven match engine combining behavioral signals, academic history, and stated preferences
Together, these systems enable a real-time, intelligent bridge between student intent and institutional targeting—improving match quality, lowering acquisition cost, and compressing time to apply.
Impact & Reach
- 35% lower CAC for institutions using smart outreach and microtransaction ad engine
- 4x faster application cycles enabled by one-click apply and pre-filled student profiles
- 28% increase in lead-to-admit conversion from improved match scoring and targeting
- Launched in 3 GCC countries, supporting multilingual content and regional compliance
- 60% higher engagement on institutions using personalized course recommendations and tracking
- 1.2M+ student profiles enriched using automated scraping and NLP-based classification
Strategic Initiatives & Learnings
- Built a SpaCy-powered enrichment engine to auto-classify and update 1M+ education records
- Introduced microtransaction-based ad model, reducing acquisition cost and enabling precision targeting
- Shifted to a modular data pipeline to scale scraping, validation, and enrichment in real time
- Prioritized one-click apply workflows, cutting friction and increasing application completion rates
- Validated that personalized student matching + real-time data significantly improves lead-to-enroll conversion
- Learned that institutions value predictive signals over volume, driving our shift toward scoring-based outreach and match quality metrics
