Big Data: the best way to harness product intelligence

Big Data Product Intelligence

Do you know the current performance of your product for consumers? Would you be interested in improving it with the most advanced techniques for handling large volumes of data in real time? Product intelligence is a key piece of business to keep customers satisfied and engaged with your brand. Currently, there are three groups in your company that can benefit the most from product intelligence: product managers, product designers and engineers and marketers.

Today the relationship between product intelligence and Big Data techniques is getting closer and closer. It is the key to understanding how each consumer uses the product that your organization markets. This requires collecting, analyzing, and acting on data to help create a better experience. This concept also allows you to know how the competitor’s product is used and, thus, compare that experience with that of your company.

Let’s suppose that the managers of a financial services or fintech company want to know what the experience that their users have with the use of the online payment application, and optimize that experience according to the current behavior of their target. Product intelligence will be the solution to that specific problem.

Another example could be a high-growth startup in online retail, whose purpose is to understand what the users who demand its service are most interested in, to offer them promotions and discounts tailored to the consumer and, in turn, understand what attributes of the product they make it more attractive and favor customer retention on the platform.

With product intelligence, you can detect the changes you need to implement to create a better customer experience and accelerate innovation, obtaining measurable results. You can strategically attack the following core business problems: Who are your power users? How do they use the product differently from other users? Why are some users converting and others not? How does retention differ by user type? Is it higher or lower when people interact with a particular function? What are the main drivers of engagement, conversion, and retention? Did the launch of a new feature cause the desired behavior change?

Identifying opportunities for innovation is one of the competitive advantages of product intelligence: it can reveal new technology solutions to meet customer needs or find unexpected ways in which customers use the product, thus providing countless opportunities for business profitability. Clearly, companies that do not use product intelligence run the risk of losing market share to competitors by failing to make the necessary improvements to stay ahead in their industry.

One of the main challenges in implementing a solid product intelligence strategy has to do with the fact that the enormous volume of data required to obtain actionable insights is usually found from multiple sources. Thousands of user behavior data and product metrics must be combined with customer data from CRM systems, marketing and market research tools, and customer experience applications such as satisfaction surveys. When all of these data sources are integrated for analysis, the true power of product intelligence can be harnessed.

In short, through the sophisticated techniques and tools of Big Data you will be able to:

1) Collect data automatically on product performance: Your product intelligence becomes more scalable and easier to act on. It also saves you time and resources.

2) Analyze consumer feedback: Text analysis tools and web data extraction techniques enable constant customer feedback analysis. In this way, your team can understand which product characteristics are most important, define and measure product metrics, and continue to create products that your customers love.

3) Conduct follow-up testing: The product intelligence data that is collected can serve as the basis for testing new product features and enhancements. It’s about testing different messages and features, and measuring how those changes affect conversion rates and customer sentiment. Tracking movement in product analysis KPIs and continually adjusting your product based on results means you are always one step ahead of your consumers.

Contact our data science specialists for all the key information you need for your product strategy.