How do you validate your value attribution?

1 Choose a suitable model

The first step to validate your value attribution is to choose a model that fits your business goals, customer journey, and data availability. There are different types of value attribution models, such as last-click, first-click, linear, time-decay, position-based, and data-driven. Each model has its own advantages and disadvantages, and no one model is perfect for every situation. You should consider factors such as the length and complexity of your sales cycle, the number and diversity of your marketing channels, the level of granularity and attribution you need, and the data sources and tools you have access to. You should also evaluate the strengths and weaknesses of each model and compare their results and insights.

2 Test and compare multiple models

The second step to validate your value attribution is to test and compare multiple models to see how they differ in their outcomes and implications. You can use tools such as Google Analytics, Adobe Analytics, or custom solutions to run experiments and simulations with different models and scenarios. You can also use metrics such as incremental revenue, return on ad spend, cost per acquisition, and customer lifetime value to measure the performance and impact of each model. By testing and comparing multiple models, you can identify the gaps and biases in your value attribution, understand the trade-offs and assumptions involved, and find the optimal balance between accuracy and simplicity.

3 Validate your data quality and consistency

The third step to validate your value attribution is to validate your data quality and consistency. Data quality and consistency are essential for any value attribution model, as they affect the validity and reliability of your results and decisions. You should ensure that your data sources are accurate, complete, timely, and relevant, and that they capture all the relevant touchpoints and interactions along the customer journey. You should also ensure that your data sources are consistent, meaning that they use the same definitions, formats, standards, and identifiers across different platforms and channels. You should also check for any discrepancies, errors, or anomalies in your data and resolve them as soon as possible.

4 Incorporate qualitative feedback and insights

The fourth step to validate your value attribution is to incorporate qualitative feedback and insights from your customers, stakeholders, and experts. Qualitative feedback and insights can help you complement and validate your quantitative data and analysis, as they can provide you with a deeper and richer understanding of the customer behavior, preferences, motivations, and pain points. You can collect qualitative feedback and insights from various sources, such as surveys, interviews, focus groups, reviews, testimonials, social media, and analytics platforms. You can also use techniques such as customer personas, journey maps, empathy maps, and voice of the customer to synthesize and visualize your qualitative feedback and insights.

5 Monitor and update your model regularly

The fifth step to validate your value attribution is to monitor and update your model regularly. Value attribution is not a one-time or static process, but a dynamic and ongoing one. You should monitor your model's performance and accuracy over time, as your business goals, customer behavior, and market conditions may change. You should also update your model as needed, based on new data, feedback, insights, and learnings. You should also review your model periodically, and test new models or variations to see if they can improve your value attribution and ROI.

6 Communicate and share your results and insights

The sixth and final step to validate your value attribution is to communicate and share your results and insights with your team, management, and other stakeholders. Communication and sharing are vital for validating your value attribution, as they can help you gain buy-in, alignment, and support for your model and decisions. You should communicate and share your results and insights in a clear, concise, and compelling way, using data visualization, storytelling, and actionable recommendations. You should also explain the rationale, assumptions, and limitations of your model, and how it aligns with your business goals and strategy. You should also solicit feedback and suggestions from your audience, and incorporate them into your model and analysis.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?