How do you navigate stakeholder feedback that contradicts customer data insights in product decisions?

It's hard to emotionally connect to data. It's much easier to connect to the struggle of a real person. If you want to change an executive's mind, show them a couple videos of customers struggling to do something that should be easy. THEN provide your statistically significant data set.

absolutely, first make double sure your data is right and then take it for the discussions, such discussions are hard but that's your job to present the truth and give intelligent insights

Persuasion requires knowing your stakeholders and what motivates them - Logos (data), Ethos (credibility), Pathos (emotion) or "Egos" (their own self esteem). You may even need to appeal to all of the above. Assessing data will only work for those motivated by Logos. For the others, consider the following: Credibility - if you don't have it, find another leader who is well respected to support you. Emotion - Show videos to support your data. Egos - Appeal to vanity or how your direction will support KPIs for the stakeholder's department.

#Verify Data Integrity: Ensure customer insights come from robust, statistically significant data sets. #Check Data Collection Methods: Review methods to confirm they accurately represent your customer base. #Validate Analysis: Ensure the analysis is sound and not misinterpreted. #Build Confidence: Be confident in your data's accuracy before comparing it to stakeholder feedback.

Knowing your stakeholders' motivations - Logos (data), Ethos (credibility), Pathos (emotion) or "Egos" (their own self esteem) - will help you identify biases. Professional biases could fall under Ethos. Sometimes partnering with those who the stakeholder trusts reduces potential biases and helps support your view.

Org or team culture plays a crucial role in these conflicts. Collective product team power over individual influences needs to be promoted to ensure decisions are more democratic and not biased

#Identify Biases: Recognize inherent biases in stakeholder feedback from their background and experience. #Contextualize Feedback: Understand the context in which feedback is given, influenced by personal preferences. #Acknowledge Bias: Acknowledge these biases without disregarding stakeholder input. #Filter Feedback: Use this understanding to filter and integrate feedback with customer data insights more effectively.

Stakeholder communication: Early and often is valuable. In fact, taking the time to interview stakeholders before a project starts or conducting a workshop is a good way to access their point of view, build trust, and learn from them.

#Promote Open Communication: Engage stakeholders with open dialogue to address customer data conflicts. #Share Insights: Present gathered customer insights clearly to stakeholders. #Explain Methodology: Clarify the data collection methods and their robustness. #Discuss Implications: Explore the product implications based on the data. #Encourage Dialogue: Foster discussion to gain new perspectives and considerations.

Treat stakeholder feedback as hypotheses that can be tested against customer data. This approach can help validate or refute the feedback with evidence.

We need to understand the root of the differing perception before we try to address it. The best thing to do before responding is ask lots of questions. For example, "How do you see your feedback fitting in with what the data is showing us?" or "Before we make any changes, what data from the customers would you find most valuable to help shape our approach?". Even simply asking if anyone has sat and discussed the data with them and how they feel about the data can go a long way.