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
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. While 60% of CMOs plan to prioritize AI adoption by 2026,current implementations often miss critical capabilities like dynamic content adaptation and voice-integrated workflows that are reshaping email effectiveness.
Top 12 Transactional Email Services
We analyzed over 30 transactional email services based on their features & dimensions to identify the following providers.
Top 10 Email Server Software: Features & Pricing
There are two main use cases for email servers. If you are looking for: Top 5 transactional email providers Sorting: The list ranks providers, with sponsored entries shown first along with their respective links. All non-sponsored providers are listed in order of the total number of B2B user reviews collected from G2 and Capterra.
AutoSys Key Features & User Insights
Interest in Broadcom’s AutoSys is declining (See: Google Trends graph), and it has a lower average rating on review platforms compared to most other workload automation tools.
AI Presentation Maker: Gamma vs. Canva, vs. SlidesGO
We evaluated the top 5 AI presentation makers by examining their capabilities across 9 dimensions with 4 different prompts to assess how well they handle various scenarios: AI presentation maker benchmark results Review the methodology and evaluation criteria to understand how we determined these results.
Top 8 Large Vision Models: Use Cases and Challenges
Large vision models (LVMs) can automate and improve visual tasks such as defect detection, medical diagnosis, and environmental monitoring. Before comparing the top 8 large vision models, it’s important to note that in specialized tasks like object detection, LVMs still lag behind domain-specific models.
Top 5 RLHF Platforms: Guide & Features Comparison
As AI adoption grows, with 65% of organizations now regularly using generative AI, selecting the right tools for optimizing AI models has become more crucial than ever. Reinforcement learning from human feedback (RLHF) platforms have emerged as key players in this process.
AI Data Collection: Risks, Challenges & Tools
AI builders need fresh, high quality data: However, data collection comes with its risks. For example, enterprises need to avoid unethical data collection practices and ensure that data is collected ethically to minimize reputational risk.
10 Steps to Developing AI Systems
IBM identifies the top AI adoption challenges as concerns over data bias (45%), lack of proprietary data (42%), insufficient generative AI expertise (42%), unclear business value (42%), and data privacy risks (40%).These obstacles can hinder AI implementation, slow innovation, and reduce the return on investment for organizations adopting AI technologies.
Control-M for Enterprise Workload Automation
Control-M is BMC Software’s workload automation solution that orchestrates application and data workflows across mainframe, cloud, and hybrid environments through a centralized interface. The platform manages complex workflow dependencies, provides end-to-end visibility into production processes, and integrates with major cloud services, data platforms, and DevOps tools.
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