Organizations are looking for ways to enhance their tools for both internal and external communications. Several unified communications (UC) companies are now producing platforms that combine UC with contact center functionality, with varying degrees of underlying integration. Building up those contact center components is a way for some firms to differentiate their offerings, with some vendors trying to make the contact center platform more of a business toolkit, tying it to the back office. Dialpad is among the companies taking this approach, notably by building out its use cases for artificial intelligence (AI), as well as building an underlying automation toolset and continuing to develop its analytics offering.
Dialpad is a cloud communications software vendor founded in 2011 that primarily provides business phone systems along with a contact center platform. It also offers a sales-related communication tool called Ai Sales, which marries outbound dialing with AI for sales coaching, real-time transcriptions, analytics and sales enablement. Dialpad supports native integration with Salesforce, Zendesk, ServiceNow, Microsoft 365, Slack and many others. Most recently, Dialpad released Ai CSAT which automates the collection of CSAT scores and gives insights into these scores.
Dialpad’s strengths are in its underlying AI layer. It has solid AI models that are trained on contact center data, along with predictive modeling, and it has been quick to evolve and innovate its technology. We assert that by 2025, AI will have become pervasive in the software stacks used to manage customer experience (CX).
The industry is coming around to the position that standard surveys are insufficient for real understanding of customer happiness: They don’t provide a deep enough view of the breadth of CX, and they don’t do anything to benefit the interaction in real time. This year, Dialpad launched Ai CSAT, an analytics offering that targets AI directly at one of the most basic issues in the contact center and CX environment: understanding customer intent and satisfaction.
One challenge of any AI-layered application is that of complexity. Many small and midsize companies tend to shy away from the use of AI and machine learning (ML) due to the perception of complexity and cost. To counter that, Dialpad is focused on the idea of “democratizing” AI for smaller and midsize businesses, especially coupled with a design sense that emphasizes simplicity and usability by line-of-business workers. Buyers are beginning to understand the benefits of having better analytics at their disposal. Contact center professionals are trained on metrics that are largely limited to performance along some very narrow lines. Other customer-facing teams are used to doing more with their data, especially marketers, who have more experience with both AI tools and with deriving customer sentiment and behavior. That makes Ai CSAT (and both Ai Contact Center and Ai Sales) good candidates for cross-departmental deployments that foster the integration of contact centers into wider customer experience and voice of the customer programs.
Dialpad made several acquisitions related to specific IP and expertise needs that targeted very clear gaps in the portfolio and integrated those technologies (from Kare and Koopid) quickly. Leadership appears to have a vision of the market potential and a strategy for getting there, and the execution within the last 18-24 months has been positive.
Dialpad is clearly showing an understanding of where the market is headed and capitalizing on the opportunities that are being presented. Ai CSAT is one example of this customer-centric strategy and has the ability to further enhance the customer experience. Any organization looking to build better customer relationships through AI should consider Dialpad as a contender.