Customer Acquisition Analytics for Banking Industry
First, we need to understand the role of customer acquisition analytics in the banking industry. No matter the industry you belong to, no matter the market you penetrate, no matter your industry size, the most crucial factor that leads to the success of any organization is undoubtedly customer acquisition. Organizations spend huge chunks of their budget running after logos to add to their portfolios. With the organizations in the banking industry switching over their focus from product-centricity to customer-centricity, the challenge now is not to develop superior products rather it is to reach the customers effectively.
The process of reaching the target audience starts even before the customer themselves decide to opt for any service offered by the bank. Considering this, the focus of organizations in the industry has shifted to client life-cycle management. Players in the banking industry are already ahead of players in any industry due to the huge amount of data they’re able to extract from their customers. However, many organizations are unable to understand this data due to its complexity, let alone actionable insights from it and share across the organization.
This is where customer acquisition analytics comes in, superior analytics allows the organizations gain granular insights on not only the current but future requirements of the customers. The organizations also need to target the most profitable customers by segmenting them into various buckets based on several factors, which can also be challenging. These challenges can take various forms such as personalized marketing programs, product design, reduce customer churn, acquire new customers, and strategies to effectively address customer needs.
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With the onset of digitization across the globe, the banking industry has also seen a plethora of changes. The customers are more digitally empowered, and hence are savvier than their predecessors, resulting in the traditional customer acquisition strategies being rendered useless. To gain an advantage against their competitors, players in the industry need to invest in enhancing their customer acquisition analytics-based strategies.
However, the increasing amount of data about consumers has become a double-edged sword for the players in the banking industry. ry. Although more data allows organizations to use the data and offer personalized services to their customers, the rapid digital transformation in the industry has left customers aiming for organizations with superior threat eradication measures. The typical consumer has become much more informed about our organization’s gather, use and store their data. This calls for superior safety measures, being necessary for every player in the banking industry to acquire new customers as well as retain their older customers. As a result, organizations have already started to prioritize transparency in their financial services to build a good rapport with their customers and instill confidence in their offerings.
Customer Acquisition Analytics Challenges Faced by the Client
Our client is a financial services provider based out of California, with operations spanning across the country. Based on market capitalization and total assets, the client is effectively one of the largest banks across the globe. After facing several fraud attacks by seemingly normal clients, the client wanted to implement a superior customer identification and acquisition model to identify high-risk customers and acquire customers falling under the ambit of the organizations’ scope, to reduce chances of frauds and other illicit activities.
The client was primarily facing these three problems:
Fraud Detection: After facing a significant number of fraud activities amounting to close to a million US dollars, the client wanted to check the profile of the customers and look for any discrepancies even before the customer joined their platform or opted for any service.
Customer Segregation: Due to the lack of any segregation strategies, the client was incurring significant costs for preaching to low-value customer instead of focusing on their high-value assets. A superior customer segregation function would have helped the client focus their initiatives to high-value assets.
Customer Acquisition: Just like every organization across the globe, our client wanted to increase their customer reach. The client wanted to offer the services exactly to the customers that were looking for them, instead of shooting in the dark. Despite being one of the biggest financial institutions across the globe, the client was stuck with low customer acquisition rates due to the lack of superior customer experience.
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Since the client was an industry veteran, they were able to (to a great extent) derive the data from their customer and extract actionable insights from the said data. However, the ever-changing field of e-banking was too complex for the client’s in-house teams to deal with. As a direct result, the client was unable to keep up with the recent developments in their customer satisfaction and service levels.
Revolutionary Customer Acquisition Analytics Solutions for the Client
Once the challenges were identified, the mountainous task to tackle these challenges began. Our clients took to the drawing board to devise the perfect solutions to help the client with customer acquisition. Since acquisition is an all-compassing challenge, everything the organization does has a direct impact on the acquisition rate, whether it’s a high number of fraud activities, low customer satisfaction, or less offerings. Our plan had to be completely exhaustive to help the client reduce their increasing customer attrition rates.
The first phase focused primarily on identifying the fraud activities and potential customers that had high chances of posing such threats. Due to the rapid digitization of the industry, the instances of fraud have increased, however, this data also increases the chances of identifying and tackling these frauds even before they happen. Along the same lines, our experts started working on a framework that could harness the power of this data and help the client proactively identify such threats through a single-pane-of-glass dashboard.
Once the framework was implemented and results started to pour in, the team decided to shift to phase two of solving the client’s challenges. The second phase focused on developing a segmentations strategy to help the client focus more on the high-value customers rather than focusing their initiatives toward low-value customers. Our experts decided that the best way to reach the desired result would be by assessing the demographic datasets available with the client and develop an AI-driven framework to analyze the competitors and various customer groups spread across the country.
This framework helped the client develop a unique customer segmentation strategy that helped the client create effective marketing campaigns driven by communication strategies separately for each target group. The client realized that by focusing their marketing efforts on the high-value customers, they were able to cut the costs of running campaigns that were encompassing all customers including low-value assets. This new technique helped the client cater to the needs of their customers in a consistent and professional manner throughout their journey.
The last phase of our solutions focused on reducing the customer attrition rate faced by the client and increasing the customer acquisition rates. As mentioned above, the client already had a well-planned data warehouse of all their customers, and this helped our experts create a model to understand the behavior and preferences of the customers better. After going through the datasets created by the client, our experts were able to implement churn metrics and analysis accuracy and deliver the uncovered insights to the client’s operations and sales teams.
Our experts also developed a customized dashboard to help the client uncover in-depth insights into their customers’ behavior. Our churn prediction modeling helped the client capture both hard churn and soft churn customer data allowing them to focus their efforts on improving their customer experience function. We also used the database to help the client improve their customer retention rates, realize higher customer satisfaction, which resulted in an improved market perception and growing base of satisfied customers.
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Improved accuracy in churn prediction by 2X
Enhanced customer retention rates by 70%
Improved overall annual ROI by 60%
Significant decrease in customer churn rates
42% increase in customer satisfaction levels