Online data is a valuable source of insights for product development. It can help you understand your customers' needs, preferences, behavior, and feedback. But how can you collect, analyze, and apply online data effectively? Here are some tips and tools to help you use online data to inform product development.
Identifying online data that is relevant, reliable, and representative of your target market is the first step. Your own website or app analytics, such as Google Analytics, can track user behavior, engagement, conversions, and retention. Social media platforms, like Facebook and Twitter, can capture user sentiment, opinions, reviews, and interactions. Online surveys, polls or quizzes like SurveyMonkey or Typeform can collect user feedback, preferences, satisfaction and suggestions. Additionally, online communities, forums or blogs like Reddit or Quora can reveal user problems, questions, interests and trends.
It is essential that data strategy is an integral part of Product strategy. Product and data team should work to define and agree on - 1) Business Goals 2) Product Goals 3) KPIs to track 4) Capabilities to add, if not available now 5) Roadmap for capabilities development and enhancement such as - Real time reporting, Personalisation and data to Common data platform. 6) Visualisation to show for different stakeholders such as execs, investors, broader team etc. 7) Data sanctity once the data starts flowing in to pipelines and CDP 8) What kind of Insights and recommendations stakeholders would need to not just improve but market the product. 9) Taking actions using Insights and progress on a AB testing and personalisation roadmap.
The next step is to define what you want to learn from online data and how it will help you improve your product. You can use data to validate your product idea or concept, by testing the market demand, the value proposition, and the unique selling point. Additionally, you can use data to optimize your product features or design, by identifying the most important, useful, or attractive elements for your users. Moreover, data can be used to enhance your product experience or usability, by finding out the pain points, frustrations, or difficulties that your users face when using your product. Furthermore, data can be used to increase your product loyalty or advocacy, by measuring the satisfaction, retention, and referral rates of your users.
The third step is to choose the most appropriate methods to collect and analyze online data according to your goals. For example, A/B testing can be used to compare two or more versions of a product or website to determine which performs better on a specific metric. Additionally, customer journey mapping visualizes the steps users take from discovering a product to becoming loyal customers, while sentiment analysis uses natural language processing to classify user emotions or attitudes based on their online comments, reviews, or feedback. Lastly, cohort analysis segments users into groups based on shared characteristics or behaviors, such as acquisition date, device type, or feature usage, and tracks their performance over time.
The final step is to apply the insights that you gain from online data to inform your product development decisions. To maximize value, prioritize your data insights based on their impact, urgency, and feasibility. Communicate your findings to stakeholders using data visualization tools such as charts, graphs, or dashboards. Experiment and iterate with your data insights; test your assumptions, measure your results, and learn from your failures. Additionally, keep collecting and analyzing online data to validate product improvements and discover new opportunities.
Before applying the insights it is crucial to understand your business’s unique context and strategic goals. Every business and it’s customer spread is different and distinct. Looking at the insights in the context of overall business vision not only helps in more meaningful actions but also avoids missapplication or misinterpretation of data.