Sıla Ermut
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
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.
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.
Top 11 AI in Fashion Use Cases & Examples
Faced with creative bottlenecks, inefficient supply chains, and rising consumer expectations, fashion brands are seeking smarter solutions. McKinsey estimates that generative AI could boost operating profits in the fashion, apparel, and luxury sectors by up to $275 billion by 2028.
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.
eCommerce AI Image Editing: GPT Images & Nano Banana
AI image editing tools analyze and automatically adjust product photos, allowing eCommerce businesses to enhance quality, remove backgrounds, or modify details with minimal effort. We tested the top 7 AI image editing tools on 20 images and 20 prompts across five dimensions, including prompt adaptability, realism, shadows, color rendering, and image quality.
Top 10 AI Avatar Generation Tools
When choosing the right AI avatar generation tool, businesses can take into account the following components: We tested 6 AI avatar generation tools and compared their visual (resolution and export capabilities) and voice (number of languages supported and voice cloning availability) features, as well as their pricing plans.
Top 20 Supply Chain AI Tools with Examples
From demand forecasting and inventory optimization to last-mile delivery and supplier negotiations, AI enables supply chain companies to process complex data, respond to disruptions more quickly, and make more informed decisions across global networks.
Top 8 Drug Discovery Software
The drug discovery software market divides into three categories: computational chemistry suites for structure-based design, AI-native platforms for generative chemistry and target identification, and R&D data management systems for ELN, LIMS, synthesis tracking, data analysis, and compound registration. We compared the top 8 drug discovery platforms across features, pricing, and deployment models.
Top 10 Voice Bots: Bland AI, ElevenLabs & PolyAI
A voice bot or voice AI agent listens to the caller, uses speech recognition to convert spoken words into text, applies natural language processing and natural language understanding to identify customer intent, and then returns an answer via text-to-speech.
Compare Multimodal AI Models on Visual Reasoning
We benchmarked 15 leading multimodal AI models on visual reasoning using 200 visual-based questions. The evaluation consisted of two tracks: 100 chart understanding questions testing data visualization interpretation, and 100 visual logic questions assessing pattern recognition and spatial reasoning. Each question was run 5 times to ensure consistent and reliable results.
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