According to Statista, the online food delivery market is set to accelerate from nearly US$17 billion in 2018 to more than US$24 billion in 2023. To cope up with the industry growth, an on-demand food delivery company is transforming the way goods move within cities by enabling anyone to have anything – specifically restaurant favourites – delivered on-demand. This significant platform connects local couriers with customers which can deliver everything from batteries to a complete meal for a crowd within minimal amount of wait time.
Business Challenge
With the growth of the company, the demand for high quality customer service was also at the peak. It was hard to match the influx of inquiries received during the lunch and dinner demand spikes which led to cancelled orders and refunds on inaccurate or late orders by the company. Subsequently, this marked direct impact of revenue of the company and drove low CSAT scores. To manage the non-peak performance became too difficult.
Additionally, the non-urgent inquiries including changing a credit card after payment, explaining a delivery fee, and reporting minor missing items such as utensils, did not get the same resolution sensitivity. Hence the requests were severely backlogged in the system.
The Solution
TaskUs studied the historical data to tackle workforce and volume issues. It then translated the data to actionable resolutions to optimise peak and non-peak efficiency. The service provider also hosted weekly meetings to review assumptions, handle items, productivity and SLAs by ticket type and volume.
Further, to manage non-peak demand, TaskUs analysed the backlog of support tickets and discovered that about 60 percent of open tickets were the same 25 questions.
Therefore, TaskUs bucketed these tickets, wrote scripted answers and systematically cleared the queue. Post that the remaining queue was way more manageable.
The service provider developed a part-time employee program to subsidize its full time workforce during peak demand hours. This led to increase in orders and reduction in refunds for inaccurate or late orders by providing enough teammates during peak hours to assist customers.
Results
The provided efficiency positioned TaskUs to be more agile to real time volume, and to continue to scale as its clients’ business grows.
