Pegasystems launched Tuesday Pega Sales Coach, an artificial intelligence tool added to Pega Sales Automation .
Pega Sales Automation targets B2B and commercial enterprises. According to Chris Benedetto, Pega's director of product marketing for sales automation, this can benefit companies with 100 employees and Fortune 500 companies whose sales exceed 500 million US dollars.
Pega also offers a version of the sales automation product that can be optimized to meet the unique needs of partner sales teams, he told CRM Buyer.
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Pega Sales Coach analyzes more than 50 distinct actions that a typical sales representative takes daily. It proactively alerts underperforming managers and generates real-time coaching advice to help salespeople to initiate, grow and close more business.
An intuitive set of dashboards allows managers to view the performance of their entire sales team and track progress against coaching plans.
"The sales coach works with Pega AI," said Benedetto, to generate "opportunity ideas, the best actions and the best deals."
He is working on the salespeople population in a company, he noted, "so that there are many examples of data that the model can use in real time to compare the Representative A and Opportunity B to thousands of representatives and similar opportunities.the past. "
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Pega Sales Coach "plays on Pega's strengths in automating processes," said Rebecca Wettemann, vice president of research at Nucleus Research.
"Pega has also done a good job helping managers understand the assumptions behind the recommendations," she told CRM Buyer, "which will help in the short term in credibility, trust in recommendations and l & # 39; adoption. "
Deal with underperformers
The predictive analytics feature of Pega Sales Coach provides insight into the probability of success for new salespeople in three months instead of the usual 12 to 18 months required.
The shortened period may be insufficient to properly assess performance, especially for new employees.
Companies selling the Fortune 1000 "could watch cycles of 9-12 months [sales]," suggested Cindy Zhou, senior analyst at Constellation Research.
"There are two ways to deal with this – customizable targets or deadlines, and transparent AI," said Benedetto de Pega.
Pega Sales Coach users can change the evaluation period to nine months, and can also change goals – prospects, opportunities and revenues, among other things.
The transparent AI offers the ability to view and modify predictors and make adjustments to it, as well as on how the model works and learns, Benedetto said.
"We do not think you're going to lose high-performing players," he said, or "giving up salespeople who have historically been the best performers – but you'll see things you do not have probably never seen before ".
Other market players
Salesforce Einstein Forecasting, Oracle Adaptive Intelligence and Infor Coleman "are other examples of using artificial intelligence to extract intelligence from sales performance," Zhou told Constellation & # 39; s CRM Buyer
SalesDirector.ai, PeopleAI and Kiite have launched AI-based sales coaching modules or software some time ago.
"Our capabilities are not limited to working only within the Salesforce Developer Community or Microsoft Stacks, like some competitors," said Benedetto de Pega.
Pega's predictors and models "are much more advanced than simple rules or black box analyzes, and we process multichannel data," he explained. "The more you log in, the more you can refine the model and deliver a review of what is happening with the representative and their client or prospect."
In addition, Pega Sales Coach "is 100% unified with our own customer service and marketing applications, so you have no work to integrate data, models and processes between you, as you would with most of our competitors ".
"The value of the Pega solution is the coaching aspect beyond measurement," Zhou said.
However, "it's unclear exactly how Pega processes data outside of Pega Sales," noted Wettemann, "as in non-captured emails in CRM, which is essential to provide a complete picture of the problem. AI prediction activity. "
Richard Adhikari has been a reporter for ECT News Network since 2008. His areas of interest are cybersecurity, mobile technologies, CRM, databases, software development, the 39, mainframe and mid-range computing and application development. He has written and edited for numerous publications, including Information Week and Computerworld . He is the author of two books on client / server technology.