Sharara Ezzatnejad, the CEO and founder of Product Road Company, discussed the effects of artificial ielligence in product manageme 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 ielligence.
Referring to her experiences in the field of artificial ielligence and product manageme, Sharara Ezzatnejad explained: “The world of technology is rapidly evolving, and artificial ielligence has become one of the key tools in product manageme.” In particular, he poied to the key role of data in this process, saying, “To be successful in the use of artificial ielligence, businesses need high-quality data and the right infrastructure.”
Data challenges and natural language processing
One of the biggest challenges in the developme of artificial ielligence models, especially in the field of natural language processing (NLP), is the lack of access to sufficie 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 developme of NLP algorithms.
He explained: “During his tenure at DigiKala, the manageme team faced similar challenges. To optimize users’ search and provide releva results, it was necessary to feed the AI models with the correct data. This required detailed analysis of data and iellige algorithms that can adapt to Iranian language and culture.
Optimizing the search process with artificial ielligence
Ezzatnejad emphasized this poi: “Optimizing the search process in DigiKala was one of the team’s most successful projects. By using artificial ielligence 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 ideify behavioral patterns that enabled more precise optimization. This process not only improved the user experience, but also coributed to a significa growth in sales.
Analyzing customer commes with artificial ielligence
Ezzatnejad expressed the challenges of this field and said: “Another importa challenge in product manageme was the analysis of customers’ opinions and commes. With the increase in the volume of commes, the need for a tool for quick and accurate analysis of this data was felt.” Ezzatnejad talked about the experience of using artificial ielligence models to screen and analyze commes, he said in this regard: “These tools helped the team to quickly ideify the problems and strengths of the products.”
He also emphasized: “It is very importa to pay atteion to cultural and social sensitivities in the analysis of commes. For example, at times, text analysis algorithms failed to ideify inappropriate or disrespectful coe. This issue requires consta updating of models and atteion to social and cultural changes.
Technical infrastructure was also one of the big challenges in implemeing artificial ielligence projects. Ezzatnejad meioned the server failure prediction project in Digikala. He coinued: “The team used advanced algorithms to predict critical times and was able to avoid major problems and costs. This experience showed how using artificial ielligence as a preveive 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 importa for the success of artificial ielligence implemeation. He added: “Manageme teams should pay special atteion 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 ielligence is not just a tool, but a manageme solution that can help businesses improve their performance and provide a better experience for their customers.
