The News:
Sprinklr announced late last month the launch of Sprinklr AI+, its new AI offering that unifies proprietary AI from Sprinklr via generative capabilities powered by an enterprise API integration with OpenAI. The combination of the two types of AI allows enterprises to combine unstructured, CX data from 30+ digital channels, including social platforms, messaging platforms, communities, and publicly available news, blog, and review sites, with generative AI to create content, improve feedback and assistance, and more quickly identify insights and subsequent actions.Â
Sprinklr AI+ is currently in a limited availability beta, and you can read the full press release here.
Sprinklr AI+ Unifies Its Proprietary AI with Generative AI from OpenAI
Analyst Take:
A provider of enterprise software for customer experience management, Sprinklr’s May 23 announcement of Sprinklr AI+ highlights the combination of OpenAI’s generative AI with the company’s proprietary AI technology, which leverages more than 1,250 industry-specific AI models, spanning 100+ languages and 150 countries, to process petabytes of unstructured text, audio, video, images, metrics, and time series data. The combination of proprietary and generative AI models enables the extraction of structured insights from unstructured data, allowing faster and more efficient content, insights, and next action generation.
Delivering Accuracy and Consistency Across Live and Virtual Agent Interactions
In addition to productivity and efficiency benefits, one of the key benefits of incorporating generative AI within a CX platform is the ability to improve the accuracy and consistency of agent-to-customer interactions, as well as between virtual agents and customers.
Sprinklr Service’s integration of generative AI allows for content summarization and call notes automation, thereby helping to create an accurate account of what happened during each customer call. According to Sprinklr, these tools permit live agents to focus completely on each customer, eliminating the need to take notes during the conversation, and allowing supervisors to be served up a quick overview of conversations without reading entire transcripts.
Additional agent tools, such as reply assistance, enable agents to generate or improve content with a single click, and Sprinklr AI+ also offers the ability to automatically extract answers from the knowledge base directly within the platform. Both features ensure accuracy and consistency of responses without significant additional effort on behalf of the agent.
The accuracy and consistency of customer interactions are critically important, especially when support is offered via multiple interaction channels. Customers that call and speak with an agent are likely to be left frustrated and angry if they are provided with an answer to an inquiry that is incorrect, or runs counter to company policy. Furthermore, the consistency of responses to product questions, support issues, or administrative concerns is also critical when interactions switch channels, or feature hand-offs between virtual assistants, live agents, or a combination of the two. Sprinklr AI+ appears to address both issues by ensuring that all agents and virtual agents have the correct answers to queries, and that they are delivered in a consistent manner.
Generative AI Aids in Driving Accuracy and Consistency within Marketing Campaigns
Within Sprinklr marketing, the most interesting benefits that generative AI brings are improvements to efficiency and speed, as well as supporting accuracy and consistency of messaging. Sprinklr AI+ can deliver generative AI-powered suggestions to help customers build marketing campaigns, while also creating tone, voice, and visual style guidelines that ensure all communications align with accuracy and consistency standards set by the organization.
Efficient marketing automation tools are essential for not only reaching prospects and new customers, but ensuring that critical communications for existing customers align with overall CX objectives, key messaging points, and sales goals. Utilizing generative AI-powered suggestions that draw from a company’s internal datasets, combined with the historical best-practices for reaching out to specific personas and actions, can increase engagement and revenue.
Author Information
Keith has over 25 years of experience in research, marketing, and consulting-based fields.
He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.
In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.
He is a member of the Association of Independent Information Professionals (AIIP).
Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.
