Here's how you can advance your future career in Product Engineering using data analytics.

Uma coisa que percebo, é que a gest?o do portfólio de indicadores deve estar sempre sensibilizando as pessoas envolvidas nesse produto a perceberem o que realmente é resultado. Os dados ajudam bastante, pois, na maioria das vezes, as pessoas acreditam que realizar iniciativas ou desenvolver coisas é um indicativo de resultado. Muitas vezes desenvolver coisas simples podem trazer bastante resultado, enquanto desenvolver algo em complexo pode ser ter sido empolgante e desafiador, mas no final das contas n?o trouxe resultados consideráveis para o produto.

Data is like bread and butter for every product guru and nothing to be added in this paragraph related to the importance of data analytics However I think I can add something Never ever think about the number and forget that numbers are representing human behavior You should remind yourself that there is a untold part of the story which is the psychological aspect Imagine what could be wrong that cause this amount of drop offs Or why users do this thing just after the onboarding Or how much time your user take to do the activation action you need them to do Always remind yourself and your team that these numbers are not just numbers they are activities conducted by humans

Having a strong grasp of data is crucial, enabling teams to align on the problem space and tackle challenges effectively. Leveraging data analysis techniques like Funnel analysis or the 'expected outcome' method, popularized by Zynga, can be particularly powerful. For instance, by examining the user journey and identifying the highest drop-off points, you can pinpoint specific areas for improvement. This allows you to rally team members around a clear problem statement, focus efforts on solving it, and drive meaningful impact. By doing so, you'll be well on your way to making data-driven decisions that enhance product value and user satisfaction.

As we are not following physics theory or a fact and all of us know that 99% of the product management activities start with some sort of hypothesis, so we should believe in the iteration ?? method of implementation First you have multiple variables some of them are controllable and some of them are not Let’s start with an assumption, giving value to the mysterious uncontrollable variables and let’s implement our solution based on that Iterate, trying hard to reach the closest possible value of this variable Another advice, determine a confidence level to reach, otherwise you will waste time and money in infinite iterations

N?o é incomum que mesmo com bastante experiência cometamos erros ao desenvolver ou melhorar um produto. Realizar pequenas itera??es nos ajuda, especialmente no nascimento de produtos, pois a chance de errarmos, mesmo realizando pesquisa e testes com protótipos, s?o altas. Apostar em lan?amentos apoteóticos aumentam as chances de falhar, e isso se desdobra em perder confian?as das partes patrocinadoras do modelo de negócio. Pensando nisso, o melhor mesmo é errar e acertar em pequenas itera??es que leve o produto para a dire??o correta.