We must do validation from different sources to make sure that received data reflect the fact on ground You can collect data from - your team feedback - IMS Data -Historical data And many other sources

Navigating the sea of marketing analysis can feel overwhelming, especially when you’re faced with conflicting research results. Start by checking the credibility of your sources trustworthy studies from reputable organizations often hold more weight. Take a closer look at how each study was conducted; a solid methodology can make a big difference in reliability. Finding common threads among different studies can help you see the bigger picture. Ultimately, it’s about piecing together insights from various credible sources to transform confusion into clarity and make informed decisions. Remember, it’s not just data it’s about understanding the story behind it.

When faced with conflicting results, follow the logical process:
 1. Asses data sources and its credibility - avoid unreliable & old legacy data
 2. Prioritize data that aligns with proposition led insights & opportunities over broad, generic trends - focus on understanding targets response to behavior, preferences and motivators linked to your proposition
 3. Finally layer external research with our own past customer data to identify patterns that are most relevant to our business and deploy pilot testing This will not only ensure your decisions are embedded in actionable insights rather than relying solely on generalized market data, but also provide actionable output from pilot testing to scale up your efforts.

To decide between conflicting data, I prioritize reliable sources and examine methodology, looking for robust samples and transparency. I also consider data recency, consistency with other evidence, and potential bias by assessing who funded the research. These criteria help form a balanced view.

When faced with conflicting research data in marketing analysis, it's essential to approach the situation with a critical and methodical mindset. Several factors can help determine which data is more reliable: Source credibility: The first step is to evaluate the trustworthiness of the data sources. Are they from reputable institutions, industry leaders, or independent studies? Data from well-established sources typically carries more weight than those from less reliable or biased entities. Context and relevance: It's important to consider whether the data is up-to-date and relevant to your specific market or situation. Outdated or irrelevant data, even if from a credible source, may not be useful for current decision-making.

In the age of information overload, navigating a sea of marketing data requires precision, clear goals, and discernment. First, define specific objectives to prevent drowning in irrelevant metrics. Prioritize data sources based on credibility and relevance, focusing on insights that align with your business goals. Utilize powerful analytical tools to streamline data processing, helping turn raw numbers into actionable insights. Regularly revisit your metrics and ask critical questions to ensure they align with real-world outcomes. Lastly, embrace storytelling—transform data into narratives that not only inform but inspire action, connecting insights with the core truth of customer needs.

Test data credibility using sample size, methodology, and source reliability. Prioritize varied, current samples and transparent methodology in investigations. Compare results to market trends and consumer behaviour. If results conflict, validate insights with controlled tests. Trust solid evidence and real-world results.