Product Analytics: The Drama Behind the Numbers

How to use data to improve your product and user experience "without dying" in the process? Learn more here with us:

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Product Analytics is a discipline used to measure and analyze the performance of a product and user experience. Through data collection and analysis, patterns and trends in user behavior can be identified, allowing informed decisions to improve the product, user experience, conversion, and sales.

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Some questions that Product Analytics can answer include:

• What is the most demanded product?
• What features do the most attractive products have in common?
• What do users like most about the product?
• What is the user experience using the product?
• How can our product stand out in the market?

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These questions can be answered using the following tools:

• Tagging: Tags added to website or application pages and elements to track user behavior.
• Page views: The number of times a page or element has been visited.
• Form results: The number of times a form has been completed.
• Data storage: Information about user behavior, such as time spent on a page, pages visited, or products viewed.
• Clicks: The number of times a link or button has been clicked.

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Let's get to work! Basically, Product Analytics works as follows:

• Data collection: Data can be collected from various sources such as taggeos, page views, form results, data storage, and clicks.
• Data analysis: Data is analyzed to identify patterns and trends.
• Informed decisions: Data is used to make informed decisions about the product, user experience, conversion, and sales.

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The importance of Product Analytics

Product Analytics is a fundamental tool for any business that wants to improve its product and user experience. By collecting and analyzing data, companies can identify areas for improvement and make informed decisions to optimize their product and increase customer satisfaction and loyalty.

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What if there is no data?

Sometimes, companies do not have access to the necessary data for Product Analytics. This can be due to various factors such as a lack of resources, tools, or knowledge.

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However, even when there is no data, it is possible to perform Product Analytics to some extent. Here are some suggestions:

• Gather information through surveys and interviews: Surveys and interviews can provide information about user opinions, preferences, and likes.
• Research successful cases: Cases of other companies can provide information about successful strategies.
• Conduct market research: Market research can provide information about market size, trends, and customer preferences.
• Analyze secondary data: Secondary data, such as government data or academic research, can provide relevant information.
• Rely on experimentation: Experimentation can help identify patterns and trends in user behavior.

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A successful case of accessible digital banking

A financial services company needed to segment its client portfolio to launch a new product. However, the company did not have access to the necessary data for segmentation.

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The company decided to use a public database from Chile containing information about people with credit cards. By analyzing this database, the company could identify a pattern in the characteristics of people with credit cards.

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Once the company had this pattern, it used its own data to segment its client portfolio according to the observed pattern in the public database. This way, the company could successfully launch its new product.

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In conclusion, Product Analytics is a powerful tool that can help companies improve their product and user experience. Even when there is no data, it is possible to perform it to some extent.

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Do you want to enhance and accelerate your company's product? Let's talk and define together the next Product Analytics strategy. We are Raven, and we design to build. Write to us! philippe.duclos@raven.inc

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