Contact Us
No results found.
Sıla Ermut

Sıla Ermut

Industry Analyst
69 Articles
Stay up-to-date on B2B Tech

Sıla is an industry analyst at AIMultiple focused on email marketing and sales videos.

Research interests

Sıla's research areas include email marketing, eCommerce marketing campaigns and marketing automation.

She is also part of AIMultiple's email deliverability benchmark. She is designing and running email deliverability benchmarks while collaborating with the AIMultiple technology team.

Professional experience

Sıla previously worked as a recruiter and worked in project management and consulting firms.

Education

She holds:
  • Bachelor of Arts degree in International Relations from Bilkent University.
  • Master of Science degree in Social Psychology from Başkent University.

Her Master's thesis was focused on ethical and psychological concerns about AI. Her thesis examined the relationship between AI exposure, attitudes towards AI, and existential anxieties across different levels of AI usage.

Latest Articles from Sıla

AIFeb 25

Generative AI for Email Marketing: Applications & Examples

Generative AI has evolved beyond basic email content creation to enable real-time personalization, multimodal interactions, and cross-channel orchestration that responds to customer behavior.

AIFeb 24

Top 20 Predictions from Experts on AI Job Loss

As a McKinsey consultant, I helped enterprises adopt new technology for a decade. My quick answers on AI job loss: AI job loss predictions Note: The size of the plots is correlated with the size of the job loss prediction. The percentages referenced in our analysis are derived from assumptions about overall job displacement.

Enterprise SoftwareFeb 24

Compare Email Marketing Pricing: Top 20 Providers

Choosing an email marketing service that fits your budget is key to effective campaigns. Basic plans often include features such as email design tools, contact management, and limited automation, making them ideal for small businesses. Higher-tier plans offer advanced automation, segmentation, analytics, and integrations, making them suitable for larger enterprises.

Agentic AIFeb 24

15 AI Agents in Marketing Tools & Examples

Research shows that 50% of organizations using generative AI plan to launch agentic AI pilot programs in 2025.AI agents in marketing represent a significant shift in the industry, introducing systems that can reason, make decisions, and act with minimal human oversight.

Enterprise SoftwareFeb 23

Top 20 ITSM Case Studies

Leveraging IT Service Management (ITSM) tools is essential for businesses aiming to increase the efficiency of their IT operations and enhance service delivery.

DataFeb 20

Federated Learning: 7 Use Cases & Examples

According to recent McKinsey analyses, the most pressing risks of AI adoption include model hallucinations, data provenance and authenticity, regulatory non-compliance, and AI supply chain vulnerabilities. Federated learning (FL) has emerged as a foundational technique for organizations seeking to mitigate these risks.

AIFeb 20

20 Strategies for AI Improvement & Examples

AI models require continuous improvement as data, user behavior, and real-world conditions evolve. Even well-performing models can drift over time when the patterns they learned no longer match current inputs, leading to reduced accuracy and unreliable predictions.

Enterprise SoftwareFeb 19

Top 11 AI in ITSM Use Cases & Examples

Leveraging AI for IT service management (ITSM) tools supports organizations in terms of: See the top 11 use cases of AI in ITSM, examples, and benefits of leveraging AI in ITSM.

Enterprise SoftwareFeb 19

Prices of Top 5 IT Service Management (ITSM) Software

IT Service Management (ITSM) tools that support incident, problem, change, and knowledge base management offer diverse pricing models. See IT service management pricing details of the top 5 providers and the feature guide for small businesses and enterprises. ITSM pricing comparison Note: Pricing information is obtained from vendor websites.

AIFeb 18

10+ Large Language Model Examples & Benchmark

We have used open-source benchmarks to compare top proprietary and open-source large language model examples. You can choose your use case to find the right model. Comparison of the most popular large language models We have developed a model scoring system based on three key metrics: user preference, coding, and reliability.