You're facing conflicting marketing analytics results. How can you ensure your data tells a consistent story?
When your marketing analytics aren't aligning, it's crucial to find the truth within the data. To navigate this challenge:
How do you approach conflicting data in your marketing efforts?
You're facing conflicting marketing analytics results. How can you ensure your data tells a consistent story?
When your marketing analytics aren't aligning, it's crucial to find the truth within the data. To navigate this challenge:
How do you approach conflicting data in your marketing efforts?
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Data doesn't have emotions and is purely logical and analytical Businesses and people use data to achieve a unified goal of sustainability in the economic slowdown Use Empathy Statements," Let's talk about how to resolve the issues of data interpretation together" "Our data is how we reflect our reality in our systems.If some of our reality has changed,some of the interpretations should change" Broaden your perspective and focus on business processes and systems that are a part of data interpretation Think from the Enterprise Perspective and find a solution to benefit the organization as a whole Recognise that Data Governance Professionals are qualified to resolve interpretation issues Foster creativity in understanding data
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Data doesn't give conflicting results, it is just data. The conflict is in how you are gathering it, how you are interpreting it, or perhaps your story is wrong or too simplistic. If the shift in analytics is sudden then it may simply be an error in how the data is gathered, unexpected interference with the data, e.g., a bot, or of course there could be a genuine sudden shift in user/customer behaviour. It is your job to find out which and respond appropriately!
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To ensure your data tells a consistent story when facing conflicting marketing analytics results, start by verifying the accuracy of the data sources. Ensure all tracking tools like Google Analytics, Adjust, or Firebase are correctly implemented and aligned in their reporting configurations. Next, establish a single source of truth by focusing on the metrics that align most closely with your goals, and cross-check discrepancies between platforms. Apply consistent attribution models and timeframes across all analyses, and regularly audit your data collection processes. If necessary, consult with experts or data engineers to identify and resolve technical issues. This way, you can confidently base your decisions on reliable, consistent data.
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To manage client feedback alongside research deadlines without compromising quality, prioritize clear communication. Set expectations upfront about timelines and the scope of work. Create a structured feedback process that allows for timely input without derailing your schedule. Break tasks into manageable milestones and regularly check in with the client to address any concerns. This approach lets you integrate feedback while keeping your deadlines in sight.
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Cross-checking findings is crucial to validating conflicting results. If the B2B segment shows an increase in product inquiries or client visits, but a decline in contract signings or project approvals, it’s essential to explore other metrics. Cross-reference customer feedback from product demos or follow-up meetings to identify potential issues with the proposal. Additionally, examine competitor pricing or new market entrants that might explain the shift in decision-making. This approach ensures a comprehensive view of the sales pipeline and helps uncover the root cause of the inconsistency, leading to more informed decisions.
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