Did you know that 98 percent of companies say embedded analytics contributes to their revenue growth? Modern BI capabilities are giving application teams new ways to engage users with the latest dashboards, reports, and embedded analytics—and today’s developers have access to hundreds of new features to dazzle users.
But how do you know which features will truly make the difference in setting your application apart from competitors? Here are the 5 analytics features our customers are requesting:
1. Data Strategies
Customer Request: Is there something better I could be doing with my data?
Sophisticated applications use data in a number of different ways, and companies have several options for housing and optimizing their data. Choosing the correct data strategy for your use case—whether you’re dealing with transactional data sets, reporting data, ad-hoc self-service, or a combination thereof—will ensure that you glean the most value from your analysis. While there is no “silver bullet” strategy, most customers utilize one of the following:
- Data warehouses, to bring data from disparate sources into a single location
- Columnar stores, to provide an optimized repository for reporting data
- Data in place, for connecting directly to where your data already lives
Customer Request: I want to tie mapping technologies into my application.
Location or geography is a key dimension in most datasets. That’s because you don’t have to be a data scientist to understand a map. Integrating mapping with analytics is an ideal way to provide a high-level snapshot to a vast audience of users. Maps are also an intuitive interaction point to allow users to move through your data—from a global overview to more granular details. Mapping is a particularly useful feature for depicting sales, marketing, survey, and polling data.
3. Predictive Analytics
Customer Request: I need my application to give me insights before they happen.
Many applications provide users with insights on things that have happened in the past. Predictive applications, on the other hand, provide insights on what will happen in the future. As you can imagine, this information can be incredibly valuable.
For instance, a traditional customer churn dashboard tells you which customers churned last month, but a predictive analytics dashboard tells you which customers will churn next. This predictive data enables you to optimize your business strategies to achieve the outcomes you want. Going with our previous example: If you predict customer churn to be 10 percent next month, you can prepare by looking for ways to reduce it by 1 to 2 percent.
4. Session Variables
Customer Request: I need to provide different experiences to my users without managing different applications.
User populations are becoming more global, and every user varies in his or her level of need for an application. That means customers are having to provide different experiences to these different users—and understandably, they don’t want the headache and resource drain of managing multiple versions of the same application.
Session variables are a way to meet this growing demand without expending undue development resources. Using adaptive integrated security, dynamic theming, and localization, they provide your application with access to key user information so that users each get their own customized “views.”
Customer Request: I want to automate certain aspects of my reporting.
Because many reporting needs are recurring (i.e., weekly or monthly roll ups), users are clamoring for a simple way to distribute this content to their colleagues. By integrating scheduler services into your application, you can automate alerting and reports based on specific events (often keyed off of time schedules).