This article is brought to you by InStore.ai.

With average industry turnover rates over 100%, according to data from NACS, operators continue to focus on retaining their workforce. And while there are numerous retention tactics a retailer could try, these dynamics persist. “It’s expensive and disruptive to address high rates of attrition by simply hiring and training new employees again and again every time a staff member leaves due to burnout, dissatisfaction or frustration,” said Jay Blazensky, co-founder and CEO of the Silicon Valley-based InStore.ai.

Instead, Blazensky said, c-store operators should look to proven frontline transformation from adjacent spaces, such as call centers, and invest in:

• Helping frontline employees develop the skills necessary to better handle customers.
• Equipping employees with the tools to deliver exceptional customer service that drives loyalty.
• Encouraging a culture of continuous learning that inspires employees to think creatively and contribute innovative ideas that drive the business forward.
• Motivating and rewarding employees based on recognition and positive reinforcement.

“Investing in employee experience is a win-win for retailers, their employees and their customers,” Blazensky continued. “Well-trained and efficient employees can enhance the overall shopping experience and encourage repeat visits, and employees who feel valued and motivated contribute to a positive store environment.”

But without a broad and deep understanding of the challenges facing employees in stores, “It is impossible to know what investments should be made to improve the retail experience for all sides without a deeper understanding of the in-store experience. This requires new tools and methods to ensure the right investments are being made in the employee experience,” explained Blazensky.

One of those methods is listening more.

“Listening” is one of the fundamental aspects of InStore.ai’s AI-powered voice analytics technology, which uses microphones strategically placed to capture interactions between employees and customers in the store. The recordings of conversations are processed, analyzed and made accessible to c-store leaders so they can use behavioral data to improve store operations.

With its analyzed findings, InStore.ai aims to help managers understand and improve both the employee and customer experience.

“By analyzing employee interactions with each other and customers across the entire business with InStore.ai, it is possible to prioritize the changes that will have the broadest impact on customers and the business. And the consistent measurement before and after the changes are made enable retailers to quantify the impacts of their investments in in-store experience,” said Blazensky.

InStore.ai surfaces insights and recommendations based on conversations via proactive notifications and searchable, interactive dashboards shared with operators. The natural language processing (NLP) machine-learning technology can interpret keywords, phrases and sentiment based on conversations, Blazensky said. For example, operators can see not only how well employees adhere to a script for promoting the loyalty program but get a sense of their general friendliness and knowledge. Managers can see trends, spot areas of improvement and recognize and reward top performers—which helps increase job satisfaction, boost morale and motivate employees to perform better. All in service of elevating the customer experience, increasing transaction sizes and encouraging loyalty.

“Fueled by the insights that AI voice analytics can bring to the table, managers can enact minimal interventions and incentives to better train staff and keep them motivated and happy,” Blazensky concluded.