JL: “We see similar needs among many of the firm’s clients. Already, a need for skills around both expert data profiles, supervised or extended by leaders who can reconcile an end-to-end vision, data and product. But perhaps even more, there is a crying need to make interactions and the product vision more fluid between numerous stakeholders – business, tech, business – whose interests are not always aligned. Creating environments that allow the circulation of data between these parties is an absolutely strategic challenge for the success of product teams, and this requires, as is often the case, the right processes and the right tools.
These Massive Challenges, Which are Technical
DS: “We are beginning to feel very concretely the considerable leverage that artificial intelligence can represent for a company that wants to continue to invest and bet on its product management, with new israel phone number library professions such as AI Product Managers , Data Product Owners , etc. As in other functions of the company, AI should generate significant productivity gains in the performance of tasks with lower added value. I advise you, if you haven’t done so yet, to ask your favorite LLM to write you a recipe book , you will see, there is a before and an after!
There are also many use cases in all tasks related to the exploitation of product data: querying a database in natural language, soon by voice, and obtaining in return for this query a graph, a data visualization, usable for decision-making, this is now possible, today, with the AI solutions of the main publishers. AI at the service of “product ops”, in other words, we are there.
Even more exciting, I believe that a great deal of value lies in AI’s ability to access ! and make sense of data that would otherwise be virtually inaccessible. Take a source of spontaneous ! customer feedback collected on the web: if you market a consumer product, your corpus is potentially made up of millions of customer verbatims scattered across a large number ! of review platforms, forums, and social networks.
Business Organizational And even Cultural?
Analyzing such volumes, applying a notion of sentiment, measuring the progression of certain conversational items over time, comparing with the competition… and sharing all this material in real time in these fluid plaud note: the test of the dictaphone of the future version chatgpt! environments that Jérémie mentions: we are now able to do this thanks to AI, at Converteo, with our proprietary semantic analysis technology.
New data sources are becoming accessible, and above all, new or old, these ! sources are more easily exploitable, faster and more simply integrated into product management operations. Well understood and mastered, these mobile list uses of AI already enable significant ! efficiency gains for product departments: we are there, and this is part of the key ! missions that we are starting to carry out with our clients. It is our ambition and our desire to support all the players who wish to progress in this direction.