What are the best practices for a successful post-launch analysis?

KPIs, metrics, etc. are all important, but you should have defined all of those BEFORE the launch ever took place. The article's suggestion of having "a clear idea of what you want to achieve with your post-launch analysis" is a bit like closing the barn door after the horses are already out of the building. The post-launch analysis tells you what happened and if you hit your launch goals. Data analysis will uncover hidden insights and maybe trends you had not previously considered, but truthfully, you should have defined all of that prior to the launch, not afterwards when you're starting the data analysis. If you do it that way, it's very easy to make the data appear to show what you want it to show, instead of what actually happened.

Launching your product without specific goals is like sailing blindfolded. You might get somewhere, but where? To avoid this, be laser focused on determining what you want to achieve with the launch (increased sales, user engagement, etc.). Then, define measurable metrics to track progress (conversion rates, social media mentions, etc.). For example: Instead of a vague goal like "improve brand awareness," set a clear goal like "increase website traffic by 20% in the first month post-launch." Track relevant metrics like unique visitors, page views, and social media referrals to gauge success.

Goals and metrics should have already been defined before launch. However, post-launch is a time to identify areas for further investigation. Consider questions you still have about your product's performance. Are there features with lower than expected usage? Have specific user segments shown different engagement patterns? What are user pain points or feedback themes? Identify areas where data can answer your questions and inform future actions.

Um lan?amento de produto bem sucedido come?a definindo quais s?o as metas e métricas de negócios que desejo mexer com esse go to market. Esses aspectos DEVEM ser mapeados no momento de constru??o do lan?amento, antes do produto ir pra rua. Para definir isso, sempre gosto de trabalhar dividindo entre metas e metricas de marketig e metas e metricas de produto. é muito importante que, nesse momento, os PMMs tenham cuidado com as métricas de vaidade, pois correm o risco de reportarem e acompanharem indicadores que n?o, necessariamente, contribuem para o sucesso do produto. Sem ter a defini??o das metas e métricas, a minha estratégia de GTM tende a ser falha.

Define clear goals and KPIs upfront. Know what success looks like before launching. Establish a baseline by analyzing pre-launch data. This allows for accurate post-launch comparisons.

Track user behavior over time, not just the initial launch period. Understand long-term trends. Analyze different user segments separately. One size doesn't fit all.

Be proactive! Identify all data sources relevant to your goals (website analytics, user surveys, customer support tickets, etc.). Establish a system to collect and organize your data regularly, making it easily accessible for analysis. Use analytics tools and dashboards to automatically collect website traffic and user behavior data. Conduct post-launch surveys and implement a system to categorize and analyze customer support tickets.

Start by aligning your post-launch goals with relevant metrics, user behavior tracking, and anticipating potential issues. Leverage website/app analytics and server logs for quantitative data, and enrich it with user feedback surveys, interviews, and support tickets. Implement automated data feeds and manual collection methods for consistency. Organize your data efficiently and document your process for clarity. Remember, prioritize high-impact data, ensure privacy compliance, and start small, iterating as your needs evolve.

Implement custom tracking tags before launch for granular analysis. These tags can help you understand user behavior in more detail, such as which features are being used the most or the path users take before converting.

Ao mapear as metas e métricas a serem acompanhadas, o PMM precisa garantir o fácil acesso a esses resultados e que eles sejam consumíveis. Na maior parte da vejo, vejo o produto nascendo sem os eventos corretos que devem nos entregar dados relevantes para avaliar o sucesso de lan?amento. O PMM sempre deve se antever a essas necessidades, entregando ao time de produto os dados que ser?o necessários para metrificar o sucesso do GTM.

Try to understand and identify trends, patterns, and correlations. Dig deeper to understand the "why" behind the numbers. Look for user quotes, feedback, and support tickets to paint a human picture.

To analyze, use tools like Google Analytics, Mixpanel, or Tableau to analyze numerical data and uncover correlations and trends. Use text analysis software or manual coding to analyze user feedback, reviews, and support tickets to understand sentiment and pain points. To interpret, don't just focus on statistical significance, understand what is behind your findings. Consider limitations in your data that might impact your conclusions. Finally, align your interpretations with your pre-launch goals to measure progress and identify areas for improvement.

Use sentiment analysis tools on customer feedback for quick insights into what users love or dislike about your product or campaign, saving time on manual analysis.

Absolutely, real-time customer feedback is essential for a comprehensive post-launch analysis. It provides valuable insights into customer satisfaction, pain points, and areas for improvement that may not be captured by traditional KPIs alone. Integrating mechanisms for gathering real-time feedback, such as surveys, feedback forms, chatbots, or social media monitoring tools, allows for immediate identification of issues and enables prompt action to address them. Incorporating both quantitative KPIs and qualitative customer feedback ensures a holistic understanding of the product's performance and facilitates agile decision-making for continuous refinement and enhancement. #productmarketing #realtimefeedback

Be collaborative! Share your findings with relevant stakeholders (marketing, product, sales, etc.) through clear and concise reports, presentations, or even interactive dashboards. Develop actionable recommendations based on your analysis, and work together to implement them. Present your post-launch analysis to the team, highlighting key successes and opportunities for improvement. Collaborate on a plan to address user pain points identified in the data. Track progress on these actions and measure their impact in future analyses.

Use competitive intelligence tools to gather data on competitors’ performance and strategies. This can uncover hidden opportunities or threats and provide a deeper understanding of the market dynamics.

Make sure you spend time looking in the rearview mirror and learning. 1) establish definition of success early in the process 2) define key metrics 3) review and report 4) communicate results broadly 5) get buy-in for next steps

It is one thing to document the good and bad of a launch, but if the feedback ends up in people's inboxes with no plan of action to implement change on the next cycle, the feedback is useless. Ensure that project managers, operations leaders, and all stakeholders know what they are accountable for if a task to drive future improvement is within their domain.

Incorporate user feedback loops. Going beyond quantitative data analysis, actively solicit and integrate qualitative feedback from users. This could include surveys, user interviews, or monitoring social media discussions. Understanding user sentiments, pain points, and suggestions can provide invaluable insights into areas for improvement or future iterations. Integrating user feedback loops into your post-launch analysis ensures a holistic understanding of your product's performance and enhances your ability to make data-driven decisions for ongoing development and refinement.

A post-mortem is a good standard practice for good collaborative, cross-functional teams to use to assess their inputs and outputs, as well as the result of the launch. These conversations should include honest and direct dialogue, but should also be handled with tact, respect, and dignity. When things seem to go well, post-mortems are still critical. When a launch goes well, the focus should be on documenting the practices and procedures that could be written into new SOPs or other guiding documents.

Make sure you continue to analyze data and insights over a period of time not just post launch. Sources and engagement can vary from time to time so while a channel or source might initially bring you traffic or leads it can change with time. Its important for product launches to have regular KPI check in reviews to make sure you are investing in the right channels consistently.