Technology

ParTech taps machine-learning tech for loyalty software

Logo provided.

September 27, 2022

ParTech Inc., a wholly owned subsidiary of Par Technology Corp. and provider of point-of-sale software and integrated technical solutions to the restaurant and retail industries, has expanded the capabilities of its Punchh loyalty software with three machine learning features.

The technology features will allow restaurant and c-store operators to boost the personalizastion of loyalty offerings, according to a press release.

The three features are feedback sentiment, smart segments and send time optimization.

The feedback module provides insight into guest feedback by applying natural language processing analysis to app reviews. Smart segments provides templated segments based on pre-defined categories of guest loyalty behavior, measured through industry-specific combinations of visit recency, visit frequency, monetary spend and more. Send time optimization helps marketers increase guest engagement with email and push notifications by personalizing the send time of the message through automated analysis of past interaction data.

By utilizing ML — the use and development of computer systems that learn and adapt using algorithms and statistical models to analyze and draw inferences from patterns — all existing and new customers will be able to utilize inferred sentiment of guests through feedback left in app reviews, access auto-generated segments derived from guest loyalty behavior patterns and increase guest engagement with marketing communications.

"We're very proud of the work that our Punchh team has done to launch these new features," Par CEO Savneet Singh said in the release. "They are all unique in the current marketplace, and no other loyalty program in the industry offers ML features as robust and analytical as Punchh. At Par, we always strive to maintain our leadership position in the industry aimed at improving and innovating our clients' experiences with their customers. These types of innovations are a prime example of us doing just that."