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Sıla Ermut

Sıla Ermut

Branchenanalyst
74 Artikel
Bleiben Sie über B2B-Technologie auf dem Laufenden

Sıla ist Branchenanalystin bei AIMultiple und spezialisiert auf E-Mail-Marketing und Vertriebsvideos.

Forschungsschwerpunkte

Sılas Forschungsschwerpunkte umfassen E-Mail-Marketing, E-Commerce-Marketingkampagnen und Marketingautomatisierung. Sie ist außerdem Teil des AIMultiple-Projekts zur E-Mail-Zustellbarkeits-Benchmark-Analyse. In Zusammenarbeit mit dem Technologie-Team von AIMultiple entwickelt und implementiert sie Benchmarks zur E-Mail-Zustellbarkeit.

Berufserfahrung

Sıla arbeitete zuvor als Personalvermittlerin und war in Projektmanagement- und Beratungsunternehmen tätig.

Ausbildung

Sie hält:
  • Bachelor of Arts-Abschluss in Internationalen Beziehungen von der Bilkent-Universität.
  • Master of Science-Abschluss in Sozialpsychologie von der Başkent-Universität.
Ihre Masterarbeit befasste sich mit ethischen und psychologischen Bedenken im Zusammenhang mit KI. Sie untersuchte den Zusammenhang zwischen KI-Nutzung, Einstellungen zu KI und existenziellen Ängsten bei unterschiedlichen Nutzungsintensitäten von KI.

Neueste Artikel von Sıla

UnternehmenssoftwareMai 18

IT-Asset-Management (ITAM) Preisvergleich

Finding the right IT Asset Management (ITAM) solution is key to controlling costs, reducing risks, and gaining full visibility into your IT infrastructure. Designed for IT managers, procurement teams, and SMEs, this comparison highlights how different pricing models and feature sets align with varying business needs.

UnternehmenssoftwareMai 18

E-Commerce-Technologie-Anwendungsfälle & Beispiele

The eCommerce sector continues to expand by ~10% each year as more consumers shift their purchasing habits online and seek faster and more convenient digital experiences.This growth is also accompanied by increasing competition, making it essential for businesses to understand how technology is shaping customer expectations.

KIMai 18

Top 9 AI-Anbieter im Vergleich

The AI infrastructure ecosystem is growing rapidly, with providers offering diverse approaches to building, hosting, and accelerating models. While they all aim to power AI applications, each focuses on a different layer of the stack.

UnternehmenssoftwareMai 18

AI Energy Consumption Statistics

A recent forecast predicts AI will use over half of data center electricity by 2028.As compute-intensive workloads such as generative AI expand, total electricity demand is also expected to rise. We covered data from the IEA, MIT, and major cloud providers to identify AI energy consumption efficiency trends and policy responses and best practices.

KIMai 15

17 Anwendungsfälle für generative KI im Gesundheitswesen

Healthcare systems are facing increased data volumes, staff shortages, and rising expectations for personalized care. Generative AI is emerging as a key solution by synthesizing unstructured medical data, such as clinical notes, imaging reports, and patient histories, into insights for clinicians and administrators.

KIMai 15

Welt-Grundmodelle: 10 Anwendungsfälle

Training robots and autonomous vehicles (AVs) in the physical world can be costly, time-consuming and risky. World Foundation Models offer a scalable alternative by enabling realistic simulations of real-world environments. These models accelerate development and deployment in robotics, AVs, and other domains by reducing reliance on physical testing.

UnternehmenssoftwareMai 14

Top 20 ITSM-Fallstudien

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

KIMai 14

AI-Bild-Erkennungs-Benchmark

As these synthetic visuals grow more realistic and accessible, the ability to detect them has become a critical concern for upholding generative AI ethics, combating misinformation, and ensuring image authenticity. We compared the top 7 AI image detectors across 5 dimensions and found that most perform no better than a coin toss.

KIMai 14

Top 12 SEO AI-Anwendungsfälle mit Fallstudien

As algorithms change and consumer expectations rise, it has become more challenging to compete for accessibility in search results. Conventional SEO techniques, which depend on manual research and minor updates, frequently fall behind these developments. AI-powered SEO tools address this challenge by automating complex tasks and aligning content more precisely with user intent.

KIMai 14

KI im Vertrieb: 15 Anwendungsfälle & Beispiele

Artificial intelligence can enhance sales processes from lead generation to sales forecasting, helping businesses overcome low conversion rates and long sales cycles.