It is obvious that the better the customer feels about the product, the better the sales.  A delighted customer usually becomes an evangelist for the product and thus, an extended member of the sales team. To ensure a delightful customer experience, the product team should know the customer – his motivations, his pain points, his aspirations. 

Product Analytics can help them figure this out.

What is Product Analytics?

Data about customers are everywhere, and collecting this data is the first step in the process of understanding it. Once data is collected, the necessary steps to obtain meaningful insights from these data points need to be carried out – these become valuable pointers on the table during product strategy discussion. The whole process of ‘understanding the customer’, starting from data collection to generation & presentation of actionable insights for decision making is called Product Analytics.

Product Analytics is especially crucial for technology products, as customer footprints are placed digitally here and can be accurately tracked to better the performance of the product and make it better suited to the customer’s expectations.   It also enables automated classification/segmentation of users across their life cycle based on multiple parameters and factors. The data generated would also be beneficial to understand customer churn and probable reasons for it. Such analysis would also pave the way to predictive insights which can point out customers who are probable to churn in the future.  Analytical insights on customer journeys across various ‘funnels’ would also help to identify pitfalls and avenues for improvements in user interface and user experience offered by product websites/apps. 

Product Analytics must be adopted as a vision by the product team and should be driven as a holistic operation that encompasses continuous data collection from multiple sources (about customers), continuous integration of such data into a consistent single source of truth as a historical data warehouse, algorithms to discover meaningful insights from the data and presentation of the insights in self-intuitive visual formats via dashboards & reports, back to the product team. Strategies developed based on customer understanding can help to meet customer needs (even latent needs), improve customer experience, and thus create a delighted customer.

Why Product Analytics?

We live in an era that is becoming increasingly digital every day. The digital transformation wave has reduced switching costs for customers in almost all sectors & segments of the business.  Customers are empowered with capabilities to gain more product information, make faster buying decisions, and make their opinions on product websites/apps known to the public domain within no time. 

Thus, marketing strategy and advertisements for the product must be crisp and targeted segment-wise. It helps to increase the quality of incoming leads and conversion rates, and decrease marketing expenses as well. It is also crucial for organizations to be proactive & have systems in place to ensure customer retention and increase sales by upselling/cross-selling.

With the volume, variety, and velocity of incoming data increasing day by day, any organization would require an automated, tightly coupled, robust Product Analytics system in place that accepts data from multiple sources, processes it, and provides actionable insights, all in real-time. It enables the product teams to understand what the users do in real-time rather than assuming these actions from gut intuitions. According to a Mckinsey report,

“Companies that make extensive use of customer analytics are more likely to report outperforming their competitors on key performance metrics, whether profit, sales, sales growth, or return on investment. For example, companies that use customer analytics comprehensively report outstripping their competition in terms of profit almost twice as often as companies that do not.”

Who should adopt Product Analytics & when?

Product Analytics is a vision that needs to be adopted as a culture at any product company, irrespective of their size and volume of business.  Anytime is the right time to start with product analytics and it has to be considered a continuous exercise rather than a single-time activity. Digital transformation is bound to bring on more innovative changes to the business world, as it does today, across sectors like banking, retail, healthcare, education, travel & logistics, agriculture, etc. Data will always be available in plenty and competitive advantages will continue to be built around customer data.

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