What is real-time analytics?

What is real-time analytics?

Real-time analytics allows you to analyze data within seconds of when it is created. This is important for time-sensitive decision-making that can help you improve the user experience, as well as your KPIs.

If you launch a new version of your app, for example, real-time analytics will allow you to immediately see if it’s working as expected. You can also use the real-time data you collect to trigger push notifications after a purchase is made, or generate alerts so you know when conversion rates dip or spike outside the normal range.

Most business intelligence (BI) solutions—like Tableau and Looker—are not real-time, but rather, rely on daily “batch updates” from a data warehouse. Similarly, marketing analytics tools like Google Analytics have up to a 24-hour delay between the time someone visits your site or app and when the data is available for analysis.

For these reasons, product managers, app developers, and growth marketers often rely on analytics solutions designed for real-time analysis, like Mixpanel.

How real-time is made possible

Real-time data availability: This is when user data streams from your website, app, or product into the storage component of an analysis tool within seconds of its creation. With this speed, you can make data-driven decisions with up-to-date information. Since BI tools only refresh data daily or hourly, it’s difficult to react quickly to the latest user behavior trends.

Real-time data visualization & analysis: Having data available in storage within seconds is only one piece of the puzzle. For truly real-time analytics, you also need to be able to visualize the data in seconds. Tools like Mixpanel enable you to select the data you want to analyze through a graphical interface, then see line charts, bar charts, funnels, and more. Running this type of “query” with SQL can take hours. Visualization speed enables you to explore your data by asking a series of questions in succession.

How is real-time analytics different—and what are the benefits?

To better contextualize some of the key differences between real-time analytics and other types of analysis, here are a few of the most commonly used processes and tools:

• Marketing analytics: Although popular web analytics tools like Google Analytics offer some “real-time” analysis capabilities, there is a notable limit on what insights you can extract from it, and how quickly they can be extracted. While users are able to see certain types of data in real-time, like current page views, the core measurement unit in tools like GA, a query for page views over the last 30 days would exclude the most recent data from its analysis. Additionally, since marketing analytics tools rely on anonymized traffic data as opposed to event-based tracking, most product teams using it in isolation will find it difficult, or even impossible, to get the answers they need.
• Business Intelligence (BI) tools: BI tools typically rely on batch analysis, which involves processing a large volume of data all at once. While this data can be extensive and thorough, the major difference is that there are delays at each step, from collection to storage to processing and, finally, analysis. This means that the turnaround on your query can take a significant amount of time. Not only is this inconvenient, but it also means you’re unable to capture the data that is being created right now, so you may not be getting the full picture from your data.
• Data and analytics teams: Some companies have a dedicated data team, through which other teams, like product or growth, might be required to submit their data queries. Depending on which data is being tracked, a data team might have access to a wealth of information, but given the often lengthy turnaround times and the lack of ability to capture the data in real-time, the decisions that are made as a result of the analysis may not be as timely or informed.

With the types of analysis discussed above, the cost of asking the wrong question or making a simple mistake can be high. With real-time analytics, however, a minor error in your query is not only immediately evident, but also easily fixable. And if the results of your query inspire a follow-up one, those answers are readily available and accessible not only to you, but to your colleagues and teammates as well.

One of the most notable differentiators of a real-time self-serve product analytics platform, like Mixpanel, is that it allows teams to achieve data democracy within their organization. With flexible and shareable reports, high-quality data is at everyone’s fingertips, and metrics like retention and conversion can be calculated effortlessly. By empowering each individual to be an owner and actor on their data, transparency and collaboration increase, the rate of innovation accelerates, and better results are achieved—faster.

Is real-time analytics right for my business?

How do real-time analytics impact businesses like yours? We’ll explore just a few of the many ways different industries may be leveraging analytics to improve their product, drive customer value, and grow their business.

A consumer app can make its launch more successful
When a B2C company first releases a new app or significantly updates an existing one, every minute matters. If the app has bugs or doesn’t function as expected, the team must fix the errors quickly before they damage the app’s adoption rate. Using a real-time analytics platform, product and engineering teams can identify bugs and anomalies and promptly fix them.

A credit card company can fight fraud
Credit card companies and financial services firms can leverage analytics to fight fraud throughout their networks. When a cardholder, for example, makes an uncharacteristic purchase—say, in a foreign country, or for a large sum online—the credit card company can trigger a workflow that suspends the card and alerts the customer. The team’s fraud-detection and customer service department can also monitor this data in real-time to provide proactive and satisfying customer service, and to forecast trends in fraudulent behaviors.

A SaaS company can increase conversions
SaaS companies often acquire leads through their website, so If visitors encounter errors on the site or the user experience is subpar, it can adversely impact their conversion rates, which translate into lost profits. By tracking how users sequentially perform certain actions (events) on their website, from entry to exit—also known as user flows— product and engineering teams can identify the points at which drop-offs or other negative behaviors occur. If the team detects common points of frustration, they can make the necessary adjustments to improve the experience and increase conversions.

A media streaming site can deliver more tailored content recommendations
Media streaming websites and apps can examine how users interact with their products and identify trends in their behaviors, tastes, and preferences. This allows them to recommend similar types of content to viewers, as brands like Netflix, Hulu, and Spotify have done, which, in turn, leads to increased engagement and retention.

An eCommerce company can increase purchasing rates and boost conversions
To combat cart abandonment and increase conversions, an eCommerce website can leverage real-time analytics to identify which events precede customer drop-off before completion of purchase. Then, when users perform that series of actions, the site can use engagement marketing to send a message or prompt, nudging them to the next step.

As you can see, companies of varying sizes and industries can benefit from the insights that real-time analytics provides. Not only does a platform like Mixpanel allow teams to access their data instantly, it creates a more comprehensive and granular view of it, resulting in clearer insights, faster decisions, and ultimately, better products.