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Sıla Ermut

Sıla Ermut

Industry Analyst
118 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

AINov 28

Top 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.

AINov 27

23 Healthcare AI Use Cases with Examples

Healthcare systems are under growing pressure from rising patient data volumes and increasing demand for personalized care.  Healthcare AI applications have emerged as a powerful solution to these problems by optimizing processes, enhancing diagnostic accuracy, and improving patient outcomes.

AINov 26

LLM Scaling Laws: Analysis from AI Researchers

Large language models are usually trained as neural language models that predict the next token in natural language. The term LLM scaling laws refers to empirical regularities that link model performance to the amount of compute, training data, and model parameters used when training models.

AINov 26

Top 15 Logistics AI Use Cases & Examples

Persistent inefficiencies, rising operational costs, and ongoing supply chain disruptions continue to challenge logistics functions globally. These pressures are straining traditional systems, reducing service reliability, and limiting organizations’ ability to scale. In response, companies are increasingly turning to artificial intelligence to enhance end-to-end visibility, strengthen resilience, and optimize core functions.

AINov 25

AI Agent Productivity: Maximize Business Gains

AI agent productivity is emerging as a measurable driver of business output. Studies report up to 30% productivity gains, indicating that agents can handle procedural steps, retrieve information, and interact with enterprise systems with consistent accuracy.

Enterprise SoftwareNov 25

Top 10 IT Service Management Tools: Features & Pricing

We evaluated the top 10 IT service management tools based on user experience, performance, and feature set. Explore our findings to see how these leading solutions differ in areas including AI features, communication integrations, DevOps, monitoring & security connections, and deployment options.

Enterprise SoftwareNov 25

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.

Enterprise SoftwareNov 25

Top 18 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.

Enterprise SoftwareNov 25

Top 10 AI in ITSM Use Cases & Examples

Leveraging AI for IT service management (ITSM) tools supports organizations in terms of: See the top 10 use cases of AI in ITSM, examples, and benefits of leveraging AI in ITSM.

AINov 25

Audience Simulation: Can LLMs Predict Human Behavior?

In marketing, evaluating how accurately LLMs predict human behavior is crucial for assessing their effectiveness in anticipating audience needs and recognizing the risks of misalignment, ineffective communication, or unintended influence.