Insights 25 December 2020

B2C Sector Expedites BIG Data-AI Use to Leverage Business Potential

Businesses that handle large amounts of data such as insurance, banking, telecommunications, and e-commerce should expeditiously use Big Data and AI to develop marketing tools with the Bluebik Win-Back system. The concept is to retrieve data of customers who are interest in goods and services yet making any purchases, for real-time analysis and prioritization for winning customers back to sales channels and to close deals as well as reducing mistakes from instinct-based decisions made by salespersons, with hopes to boost sales crippled by the COVID-19 crisis.     

Business should be focused on adopting technologies that help create business value in all aspects in order to strengthen competitiveness in the digital era. The sales process is fundamental to generating income and is a part of the business-customer interface that allows studies of customer behaviors. With good data management and relevant technologies, businesses can achieve advantages through customer insights, especially in times of economic downturns caused by COVID-19.

Bluebik Group, for instance, has developed a model to make sales closing simpler with the Algorithms Machine Learning technique. The technique is about analyzing and identifying relations between datasets, and creating customer patterns and segmentation to understand better customer insights. This helps businesses offer more personalized products, services, and promotions that cater to different lifestyles. This also applies in marketing automation tools named Bluebik Win-Back systemto perform real-time data analysis of registered customers that expressing interest in the goods/services but never bought or “lost” customers, who have explicitly churned, in a bid to turn them into real customers. The system stores basic data and essential details of potential customers for analysis and easier sales closing in the future.  

The Bluebik Win-Back process can be divided into 2 principles as follows: 

  1. Lead Prioritization: Creating a list of quality leads using Big Data and AI technologies to identify who are most likely to buy first. The Lead Prioritization Model retrieves data stored in the customer database and analyzes the possibility to win back each lost customer, a duty previously assigned to the salespeople. The customer with the highest possibility will be on the top of the list to help businesses reach direct targets more efficiently. 
  2. Win-Back Dashboard: Collecting and displaying each individual customer’s key data, a notable showcase of the Big Data and AI implementation. The dashboard enables more user-friendly data usage and faster access, leading to the overall improvement of team performance and the ability to re-engage potential customers into the sales process. 

Big Data helps the Win-Back process improve efficiently and effectively. The A/B testing was conducted to compare the system performance results with the normal operating results. The “A” team was equipped with the Win-Back system to prepare a list of prioritized customers based on their re-engagement possibility while the “B” team performed normal operations by randomly picking out names to call. The A/B testing results were based on 2 indicators, efficiency (the ability to strike a deal) and effectiveness (the successful results), as follows:

  1. With the Bluebik Win-Back system, the proportion of interested customers improved by 30%. For example, based on the 7,500 phone calls made to the existing customers per month, the sales closing rate was improved from 1,200 to 1,600 phone calls.
  2. The time spent on contacting irrelevant customers whose lifestyles did not match proposed products and services was reduced by 80%. 

The above results reassure businesses that sales can be achieved not only from those who bought products upon the first offer but also from the lost and returned customers if businesses know how to analyze and access the right groups of customers with the right products.

In the past, many operators misguidedly believed that their businesses would not be affected by the digital disruption, so they did not adjust themselves. Once they started to realize the situation, they were already left behind and had lost their market share. Therefore, all businesses must stand ready and dare to adopt customer database management and analysis technologies to maximize their operating efficiency and effectiveness.