Most of us use embedded data analytics frequently as consumers. For instance, a travel search site like Kayak lets us search for flight information in one place instead of visiting multiple websites, using search parameters for items such as price, airline and flight times, and then book our trip directly from the site.
Similarly, embedded data analytics that allow business users to access data from within applications in which they are working can help democratize data, experts agree.
Today Salesforce is introducing Sales Wave Analytics, the first of what the company promises will be a series of role-specific embedded data analytics apps. Like Kayak and other apps we use frequently as consumers, Sales Wave Analytics is designed to deliver specific insights and allow users to quickly take action, said Anna Rosenman, senior director of Product Marketing, Salesforce Analytics Cloud.
Built on the company's Wave platform, the new sales app includes three key components:
- Pre-configured accelerator templates designed around common sales activities like pipeline management. They include KPIs, metrics and best practices gleaned from Salesforce customers and Salesforce's own sales team. The company offered the example of a sales executive who could conduct a real-time pipeline analysis and cross reference it with product sales performance to identify which deals need to be accelerated to hit sales targets.
- Historical analysis, with dashboards designed to help users surface historical trends and year-over-year comparisons, so they can identify seasonal trends, behavioral patterns and cyclical issues. The dashboards are designed to replace "hundreds of spreadsheets," Rosenman said.
- Wave Actions, which give users the ability to take actions such as creating a task or initiating a conversation directly from the app. Because the app is natively integrated with the Salesforce1 Platform, pre-defined data flows will not only enable changes made in the app to be reflected automatically within Salesforce, but will also update all corresponding metrics in Salesforce related to that change.
The overarching goal for the new app is to reduce time to value, Rosenman said.
Denis Pombriant, managing principal at Beagle Research Group, said he expects to see more of these kinds of apps, from Salesforce and other companies.
"Customers and customer processes generate a lot of data; we know this. But analytic apps give everyone the ability to see into a variety of processes to surface important customer signals," he said. "For instance, in the sales process there are obvious buy signals that we need to capture. There are also signals that show growing customer disenchantment, signals that might not yet be top of mind for customers, that would provide fast-acting businesses with the time they need to get into customers' moments of truth and potentially change things."
While the current focus is on primary signals from sales, marketing and support, Pombriant said customers will ultimately want to add multiple signals or metrics or KPIs together to derive even more information. "For example, a churn indication might need to be correlated with sales and marketing signals about upgrades from support or cross sells from needs brought up in a service encounter," he said.
While the app is packaged as a standalone solution, Rosenman said Salesforce expects most customers will want to use it with Salesforce's other products. Sales Wave Analytics is currently in beta and should become generally available later this year.
The Wave Analytics Cloud, which the company introduced eight months ago, has become its fastest-growing product ever, she noted, although Salesforce did not release sales numbers. GE, Akamai and Verizon are among the customers using it. Last month Salesforce announced integrations with leading Big Data platforms such as Cloudera and Google.
Ann All is the editor of Enterprise Apps Today and eSecurity Planet. She has covered business and technology for more than a decade, writing about everything from business intelligence to virtualization.