A/B testing is the most effective way to observe users’ behavior with two or more different versions of the same screen or in-app experience. It can help you test variations of an item, generally UI based, to determine which one performs better. Directing some users to version A and others to version B allows you to observe user behavior for each.
“What should you and your business focus on when trying to create better customer journeys and beat competition?” That was the question we asked Countly data captains (also known as Countly customers) when trying to determine how well they collect customer experience metrics and how well they were using that data to make data-driven decisions.
Some time ago, we covered the key metrics that a Product Manager in a fintech organization should make a top priority when determining their KPIs, breaking them down into five groups: Session-based data, Customer Feedback, Technical Metrics, Action Stats, and Revenue. With that in mind, we conducted a series of surveys on LinkedIn, asking PMs in the fintech industry which of those groups were the most important for them while running digital product analytics.
Ever wondered what it would be like if we weren’t able to see all of a sudden? Being born blind and facing blindness and low vision at a later stage are very different experiences. When you first feel the loss of vision, the panic and the helplessness are real. It’s that feeling of losing something important that we took for granted. Let’s just take a moment to appreciate that we can read this all thanks to our healthy eyesight.
Cybersecurity research website CyberNews recently interviewed Countly’s CEO, Onur Alp Soner, discussing everything from Countly’s origins to the role of cybersecurity in product analytics and how this might shape digital products in the near future.
Never before has data become so prevalent in everything we do. Sorting out the best way to make sense of incoming terabytes of data has turned into an extreme sport. Likewise, it has become a life-or-death decision in every organization, regardless of their level of maturity, to determine an analytics strategy to harness the potential power of all that data without running the risk of overwhelming teams and paralyzing processes.
Product Managers, especially those in start-ups, have no easy job to do: product tweaks, project management, QA, release notes, you name it. With such a dynamic and all-encompassing role, things can get tricky. So much so that, in a recent poll we conducted via LinkedIn, we found out that “Testing and Launch” is the second most problematic stage in the life of a digital product, according to almost 27% of product managers.
The EU’s General Data Protection Regulation is approaching its 4th year anniversary since it was implemented in May 2018. Since its inception, it has been hailed as a groundbreaking framework for making users’ rights on the Internet a human right. Its impact in many other markets has been undeniable and it truly has affected how the world of the Internet works, even outside EU borders.
Almost 6 years ago, the European Union’s General Data Protection Regulation (better known for its acronym, GDPR) changed the world of personal data protection forever. The groundbreaking ruling has since been replicated, albeit with changes, in over a dozen other markets.
The KPIs that apply to each product are as different as products come. There are infinite variables that come into play when determining what exactly a KPI should be. Because these KPIs are centered around customer journeys, they are all user-based and purposely omit technical-based KPIs (such as crashes or errors). In a recent article in our Product Analytics Academy, we covered what makes a strategy a good one when understanding and choosing relevant metrics to form KPIs based on product analytics.
