Here's how you can identify patterns and trends in customer behavior using logical reasoning.

Data collection is key, but even more important is knowing what data to collect. Action metrics are what matter, since it will base current (and hopefully better future) outcomes. In a customer experience context, the Pirate Metrics framework—Acquisition, Activation, Retention, Revenue, Referral— offers a streamlined view of where to focus in your data collection efforts. Vanity metrics, in contrast, look appealing but lack actionable insight. Vanity stats, if not checked, lead to a quantity-over-quality trap, looking at a bunch of numbers that don't move the needle.

All inference wrt consumer behaviour is based on research, data and consumer listening. Gather as much information thru surveys, feedback, social media, website and customer service analytics The data will show trends and patterns - it is good to deploy AI (for numerical & text) or NLP (for voice data) to extract real insights and repetitive issues/ preferences. It may also be helpful to find co-relation in data to develop hypotheses, which can then be put to customer validation through a quantitative study. The results obtained will then be very dependable. Based on the insights derived from data and/or validated by customers, one may take decisions that impact consumer positively.

Your solution is only as good as the data you collect. It's key to understand your customer across all touchpoints. You may want to send an email to a customer to upsell a product but if you don't know he has an issue with his or her current product purchase from your service/ support department it would just weaken your relationship with them. Understanding their behaviour is key - each customer has their own unique wants and purchase patterns. Understanding his or her need and being relevant to them at the right time only helps build a better experience. Also intuitively changing your offering by understanding their life stage also would help.

Para complementar la formulación de una hipótesis, es necesario que la data recogida se pueda vertir en un análisis del Blueprint del cliente, para poder encontrar verdaderos cuestionamientos e hipótesis más precisas.

Feedback loops are some of the most underutilized processes we have available in our toolkit. You spend months building a process or product, take care of it by acknowledging feedback and improving your tools. This not only allows you to maintain momentum, but it puts you in a place to be an innovator. Most organizations struggle to hear their customers, when you implement a feedback loop you ensure you're not one of them.

This article mentioned feedback loops, but in all other points= data, analyzing, hypothesis etc. Can't help of wonder: have we totally forgotten how to just ask your customers? Dashboards, metrics, numbers, assumptions... Where is all involment with actual people and customers, improvement by customer feedback? Just ask, and people will tell you?