May 1, 2021
Companies are gradually moving from survey-based customer understanding to AI-driven predictions. Despite being an important tool for customer research, the survey-based measurements fail to meet the CX needs many times. Primarily, the time and effort in managing questionnaires and boosting the response rates always had a room for human error. The metrics resulting from Predictive analysis is seen to make better business progress, process, employee benefits and future investments.
Predictive analytics is a category of data analytics that help businesses predict future events, behaviours and sales and marketing outcomes based on historical data, feedback, and techniques including statistical modelling, Artificial Intelligence (AI) and machine learning.
The predictive analytics market has been growing by the rate of 21% each year since 2016. Zion Market Research predicts (2018) shows that it will reach approximately $10.95 billion by 2022 globally. Therefore, companies are increasingly adopting PA as a part of their business strategy.
The PA innovation not only reduces errors, its insights only get better with time, as the tools continually learn and adapt from the data inputs. In the process PA offers:
As a tool PA can be used for a personalised user experience par excellence. It can determine the best customer service; cater to customer demands, and help exceeds expectations through phone calls, emails, social media feeds, escalations, and data from other channels. It works for any industry and can immensely improve internal operations too along with customer service.
With PA businesses can anticipate customer needs even before the customer does. It encourages proactive follow up, messaging, product recommendations, and implementation of marketing tools. These elements of the personalised experience attract customers. PA enables forecasting of customer needs based on:
PA can offer instant gratification to the customers by predicting preferences, views, demographics etc. are useful factors. Amazon provides personalised suggestions for products based on buying history, offer combinations along with what customers with the similar choice have bought.
With increasing competition, customers’ churn is becoming a major risk. With PA, companies can pay closer attention to customers before they leave for a competitor. Through an NPS score PA can identify:
PA-powered systems can generate ‘predictive alarms’ wherever needed and drive decisions on customer satisfaction management. Businesses can create “What If” scenarios and analyse them for behaviour prediction.
PA improves internal operational and resource allocation which indirectly improves CX. Transparent and efficient internal operations offer ease of service. Efficient internal systems can also greatly improve staffing, inventory forecasting, and management customer queue management based on historical data and patterns. PA also streamlines shipping processes with potential shipping issues prediction and points to the instances that will expedite shipping.
With its ability to give an edge in the competitive CX landscape Predictive analytics is defining the future CX standard.
Interested to discuss more, please feel free to contact the author at ashish.bhalla@dbp.com.sg
Ashish has almost 30 years of industry experience in a wide range of business solutions primarily focusing on end-to-end customer experience management. He is the founder and CEO of Digital Business People (DBP), an omni-channel customer experience management company headquartered at Singapore with it’s development and delivery centers in India.