The closure of stores, branches and call centres during lockdown has led many consumers to use social media when seeking help or information from the brands and services they buy from and subscribe to. Across six South African industries analysed by DataEQ, social media conversation has increased by nearly 150% since President Ramaphosa declared a National State of Disaster on 15 March.
Based on a collection of 957 759 social media posts from 1 March to 2 April 2020, DataEQ assessed the impact of COVID-19 on six SA industries: banking, retail, telecommunications, insurance, pharmacies and Internet Service Providers (ISPs).
Commenting on the findings, DataEQ chief executive, Nic Ray said: “There is an unprecedented demand for digital customer service in South Africa right now and this is likely to grow in the weeks ahead. It’s proving challenging for businesses who are looking for new ways to provide effective service to anxious customers. The likes of the pharmacies are not used to such high volumes of customer queries online. To improve their response rate and time, organisations that are able to empower their remote social teams with the requisite permissions and tools, and prioritise customer service issues will be able to maintain business continuity and mitigate reputational risk associated with poor service.”
Key findings
The data in this graph aggregates each industry’s response rates to consumer headposts on Twitter over 1March – 2 April. Industries are struggling to respond to consumer queries amid increased online conversation. Across all industries, the rate of response to customer posts that require attention dropped by 26.6% after 15 March. Banks suffered from the largest response rate drop of 39.2%
Methodology note
957 759 social media mentions, of which 144 191 pertained to COVID-19, were collected. Just over 202 366 mentions were processed by DataEQ’s Crowd of human verifiers for sentiment analysis. 57 365 mentions were assigned conversation topics. The range for margin of error on Net Sentiment between different industries was 0.3 – 2.3.
