From artificial intelligence to product management; Sharara Ezzatnejad’s speech at the Pandora startup meeting

Sharara Ezzatnejad, the CEO and founder of Product Road Company, discussed the effects of artificial intelligence in product management at the second Pandora startup gathering. Emphasizing the challenges and opportunities in this field, he emphasized the importance of proper data and infrastructure for success in the complex world of artificial intelligence.

Referring to her experiences in the field of artificial intelligence and product management, Sharara Ezzatnejad explained: “The world of technology is rapidly evolving, and artificial intelligence has become one of the key tools in product management.” In particular, he pointed to the key role of data in this process, saying, “To be successful in the use of artificial intelligence, businesses need high-quality data and the right infrastructure.”

Data challenges and natural language processing

One of the biggest challenges in the development of artificial intelligence models, especially in the field of natural language processing (NLP), is the lack of access to sufficient and appropriate data in the Persian language. Ezzatnejad noted: “While in other languages, data is easily accessible, in Persian we face problems such as lack of resources and lack of proper structure. These challenges are especially noticeable during the development of NLP algorithms.

He explained: “During his tenure at DigiKala, the management team faced similar challenges. To optimize users’ search and provide relevant results, it was necessary to feed the AI ​​models with the correct data. This required detailed analysis of data and intelligent algorithms that can adapt to Iranian language and culture.

Optimizing the search process with artificial intelligence

Ezzatnejad emphasized this point: “Optimizing the search process in DigiKala was one of the team’s most successful projects. By using artificial intelligence algorithms, the team was able to increase the conversion rate. In this regard, the process of fitting and ranking information was carefully reviewed to ensure that the best products are displayed to users.

For example, by examining search data and analyzing user behavior, the team was able to identify behavioral patterns that enabled more precise optimization. This process not only improved the user experience, but also contributed to a significant growth in sales.

Analyzing customer comments with artificial intelligence

Ezzatnejad expressed the challenges of this field and said: “Another important challenge in product management was the analysis of customers’ opinions and comments. With the increase in the volume of comments, the need for a tool for quick and accurate analysis of this data was felt.” Ezzatnejad talked about the experience of using artificial intelligence models to screen and analyze comments, he said in this regard: “These tools helped the team to quickly identify the problems and strengths of the products.”

He also emphasized: “It is very important to pay attention to cultural and social sensitivities in the analysis of comments. For example, at times, text analysis algorithms failed to identify inappropriate or disrespectful content. This issue requires constant updating of models and attention to social and cultural changes.

Technical infrastructure was also one of the big challenges in implementing artificial intelligence projects. Ezzatnejad mentioned the server failure prediction project in Digikala. He continued: “The team used advanced algorithms to predict critical times and was able to avoid major problems and costs. This experience showed how using artificial intelligence as a preventive tool can help improve the performance of systems.”

Creating a data-based organizational culture

Ezzatnejad emphasized that creating a data-based organizational culture is very important for the success of artificial intelligence implementation. He added: “Management teams should pay special attention to using data as a key decision-making tool. This organizational culture allows teams to effectively use data to optimize processes and decisions.”

In general, data challenges, cultural sensitivities, optimization of processes and technical infrastructure are all things that must be considered for success in this field. Artificial intelligence is not just a tool, but a management solution that can help businesses improve their performance and provide a better experience for their customers.