Drive Valuable Insights About Your Web3 Application Using API Analytics
What can your API data tell you about your Web3 app? Learn about leveraging API analytics to keep your users happy and your business growing.
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Join For FreeWhat's your API data telling you about your Web3 App? By lifting relevant information from your App's API transactions and call logs, you can identify and proactively catch issues before your customers surface them. As a result, keep your customers happy and reduce churn, making your customer success team performant.
Generate Insights From Transaction Data
Web3 adoption is increasing. Between 2015 and 2022, blockchain adoption increased at the same pace as internet adoption did between 1991 and 1998. If that continues on the same trajectory, then Web3 users will hit one billion by 2027.
For early Web3 adopters, there are plenty of opportunities that insights from transaction data can help to identify. API Analytics helps with this by elevating transactional data from crypto companies and other Web3/blockchain adopters to visualize the data and generate insights.
What Information Can Transaction Data Hold?
Transaction data can provide a wealth of information when you have the right tools in place. Your data can reveal insights into conversion rates, popular endpoints, and API payload anomalies. It can even help identify instances of fraud. As Bloomberg points out, working with a leading provider can reveal the stories in your data. You can then use what the data reveals to your advantage and further your business, improve your product and gain more customers.
Actionable insights gleaned through your analytics can help you to operate your business more efficiently and enhance your customer experience. The insights from transaction data from your Web3 application can unlock hidden business growth potential, just as analyzing Web2 API payloads can.
Where Is Transaction Data Stored?
Blockchain transaction data is stored in different ways by different blockchains. Because of the open-data structure that sustains blockchains, they are unsuitable for storing large amounts of data. This is why many dApps offer decentralized storage. As decentralized applications, the blockchains are stored in 'nodes' worldwide.
Bitcoin, for example, uses an Unspent Transaction Output database to store the change from Bitcoin transactions. The Ethereum blockchain, meanwhile, uses a trie (digital tree) data structure that includes state tries, storage tries, transaction tries, and receipt tries.
Transaction KPIs That Matter
Are people using your service effectively or not? If not, you are at risk of them heading over to the competition. Measuring your transactions' Key Performance Indicators (KPIs) can provide plenty of insight here. But, of course, that means you'll need to spend some time working out which transaction KPIs matter.
The differences between Web2 and Web3 can appear very stark at this point. The decentralized nature of Web3 means that many key performance indicators that were essential for Web2 might not make sense for Web3.
What KPIs Should You Measure for Payment Processing?
When it comes to payment processing, getting your financial metrics in order is key – they are something that every successful business needs to track. Web3 payments use secure ledgers to process money movements as a form of decentralized finance. As a result, payments tend to be processed without the personal data requirements and fees that are associated with big data, centralized banks, and Web2.
Whether it's a financial KPI or a developer KPI, management consultant Peter Drucker points out that "If you can't measure it, you can't manage it." This is the cornerstone of deciding which KPIs to measure. Whether it's customer satisfaction, customer retention, customer acquisition, or lifetime value that you're digging into, the right KPIs will unlock detailed insights.
For Web3 payment processing, relevant metrics include transactional KPIs, security KPIs, and reconciliation KPIs. For example, transactional KPIs might include measures such as the number of miners, number of transactions, or hash rate. Security KPIs, meanwhile, could include the number of fraud detection/alerts or a number of data breaches prevented. Finally, on the reconciliation front, you could measure metrics such as on-time reconciliations, the number of aging reconciling items, or the percentage of automated reconciliations.
Retaining users is just as important as gaining new ones, so monitoring your conversion rate is a fundamental part of your Web3 API analytics. Whether as a means of gauging customer satisfaction or operational efficiency, your user behavior can be used to inform your product decisions.
How Do KPIs Fit Into Your Engineering Roadmap to Ensure Customer Success?
How you build your engineering roadmap underpins everything from operational efficiency to customer success. After all, there's only so much you can do to provide winning customer service if you haven't got the fundamentals right. Land on the nose; your net promoter score could go through the roof.
Thinking about KPIs early on will help. Which are the transaction KPIs that matter to you? Only by knowing that can you ensure you build the capacity to track and monitor the right elements of your Web3 products.
Fitting KPIs into your engineering roadmap, therefore, needs consideration when you prioritize your major themes and when you are integrating with project management, data analysis, and other tools. Therefore, you first need to identify the KPIs you want to track, then implement the right data analytics for Web3 to enable you to do so.
How Can KPIs Detected by API Analytics Help You Understand Deviations in User Data?
Incorporating API analytics into a Web3 platform helps retain developer customers and conform to governance rules.
Part of this involves using KPIs to identify any deviations in user data. API analytics does this by enabling you to create dashboards with workspaces representing different metrics. You can analyze each workspace, reviewing the historical performance of each metric. The graphical nature of the data means that any deviation is quickly apparent, allowing for quick action to solve business and product issues.
You can also set up alert rules that notify you when a metric passes a certain threshold. This instantly flags any deviations beyond the thresholds you set and communicates the deviation instantly via our Slack integration or built-in behavioral email tool.
Grow Your Product With Real-Time User Monitoring
By strengthening your Web3 business with the right product analytics, you can grow your product with real-time user monitoring. Monitoring real user data can be far more effective than synthetic monitoring, as it dives into the real user experience you are delivering and flags any performance issues. This means that you can make changes to your product, strategy, and delivery model to deliver an enhanced customer experience. This can lead to accelerated growth since the decisions made are backed up by real user data.
How Do Analytics Accelerate Growth?
Analytics accelerate growth by helping you understand how people use your product and where they get stuck. For example, you can understand where they are facing challenges, identify patterns that lead to customer churn, and see what happens when they hit your paywalled services.
By understanding in greater depth, you can identify ways in which you can better serve your customers and support them to change their behaviors in ways that benefit both them and your business. For example, you can identify the need to iron out bugs in your product and find new ways to enhance the user experience. Essentially, analytics means you can convert your log data into actionable information that you can use to elevate your product.
RUM vs. Synthetic Data
Real-time user monitoring (RUM) means using real-user monitoring to analyze your product's performance and underpin accelerated growth. It uses the logs to deliver data-based customer feedback and insights into your users' actions.
Many companies let you test your product using synthetic data instead. Still, those fake endpoints and fake analytics can't tell you what true users of your service will actually do when they face a challenge or hit a paywall. This means that testing with synthetic data can only take you so far. It's a theoretical approach to what your users might do rather than feedback based on the reality of what's happening.
This is why there is so much more scope to grow your product with real-time user monitoring. RUM delivers value that synthet
ic data can't. It delivers insights into what's happening in your business at any given moment and on an ongoing basis.
For example, if the number of developers who convert to paying customers is lower than expected, you can use RUM to discover their pain points. Then you can solve those pain points and witness the impact of your changes through real user monitoring.
Alongside other forms of customer feedback, this gives you the powerful ability to optimize your product to deliver an outstanding user experience that supports long-term user loyalty and continuous product evolution.
Published at DZone with permission of Rachael Kiselev. See the original article here.
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