Está abrumado con las fuentes de datos para las decisiones de marketing de productos. ¿Cómo priorizarlos de manera efectiva?

Recomendo agrupar os dados: 1. Consumidor 2. Mercado Competitivo 3. Desafios Internos. E diante dos principais insights de cada grupo, ir desenhando a estratégia que possa atender!

Start by pinpointing what really matters for your product marketing. What's your main goal — more brand buzz, website traffic, or better conversion rates? Getting clear on your objectives is like having a compass in a sea of data sources. It helps you focus on the info that'll actually move the needle for your business. So, take a step back and ask yourself: "What does success look like for me?" Once you've got that figured out, you'll find it much easier to prioritize your data sources and make smarter marketing decisions.

Establish an understanding of your data lineage as well as points of inflection of data from the source. Once you have established the right data required for your analysis, clearly list down your objectives from the data. One data set can be used in multiple ways with different outcomes (Descriptive, Diagnostic, Predictive or Prescriptive), ergo be explicit in defining what is your end goal from the data set as well as what sort of deviation is acceptable. Use of AI tools at this point could be really helpful to increase accuracy & efficiency. However keep in mind the concept of GIGO, it applies to all tools. As you go about setting your objectives, pay attention that they follow the SMART model with a scope of revision if needed.

Start by identifying your key business objectives, such as increasing market share or boosting customer satisfaction. Once those are clear, map each data source to these goals. Ensure each source provides actionable insights supporting your objectives. For example, if your aim is to improve customer satisfaction, prioritize sources like customer feedback and social media analytics. Focus on data that directly informs your goal, and use the SMART model to define specific, measurable outcomes. Remember, a well-defined objective turns raw data into strategic action.

Leaning into Tableau for visual analytics and Qualtrics for customer sentiment analysis supercharged our approach to data quality. This blend of tech allowed us to visually map out discrepancies in real-time, while Qualtrics provided the pulse on customer feedback directly tied to our offerings. A breakthrough came when we identified a misalignment between perceived user experience and actual feedback. By addressing this with pinpoint precision, our strategy pivoted to uplift customer satisfaction, which in return, ramped up loyalty metrics. Harnessing the right tools not only fine-tuned our data accuracy but also turned insights into impactful actions, solidifying our market position.