This article was originally printed in BAI Banking Strategies on May 15, 2013.
Using customer data at the point-of-sale with eligibility analytics can help banks implement a simpler and more efficient sales process.
Retail banking has never had to focus on a comprehensive sales process. Because of profits from margin, loans and fees, banks have historically never felt a need to ensure customer loyalty through multiple account commitments and have shied away from proven sales methods found in other industries.
However, now that the market has become competitive, the lack of sales infrastructure hurts. For example, while banks today are selling product through multiple channels, including the branch, contact center and online, they rarely are able to ensure that product recommendations are consistent with eligibility across all channels. The branch may be recommending different products than the website or vice versa. This presents several challenges that lead to operational sales inefficiency, such as no way to track which products were recommended as compared to which accounts were actually opened; an inconsistent and possibly confusing customer experience; and very few pre-qualified sales leads entering the sales funnel.
A recent survey conducted by the Boston Consulting Group found that banks that were strong operationally delivered superior financial performance and listed five key trends needed to achieve operational excellence: strengthening the customer experience; increasing sales performance; improving end-to-end productivity; enhancing organizational efficiency; and reducing complexity.
Let’s take a closer look at these trends in the context of improving the retail banking sales process:
Strengthening the customer experience. With continuing low interest rates, new regulations that increase operating costs and sluggish employment growth, retail banks are planning to generate internal growth by increasing revenues and profits from existing customers. This means that banks are going to spend the vast majority of their time in 2013 and 2014 strengthening the customer experience primarily by cross-selling to their customer base. The challenge is that customers are taking greater control of their banking relationships by switching banks, changing their behavior and demanding improvements.
The first step to strengthening the customer experience is to understand the customer. I was recently speaking with executives of a large bank that has approximately 500,000 unique inbound visitors per month to the small business section of their Website. Web statistics illustrated what information the visitors were interested in and some buying behavior. However, the bank still had the challenge of vetting out what the prospect needed and, more importantly, what they were eligible for. This needs to be done at the point-of-sale because without that information, unqualified sales leads flood the sales funnel and the sales team has a very difficult time closing on the lead. There is nothing more demoralizing than giving a sales team a huge number of leads that don’t turn into sales.
Don’t Push Products, Reduce the Complexity. Putting customers in the right account is the second step to garnering customer loyalty. However, this is very difficult due to the sheer number and complexity of available products. Banks often offer more than 100 products yet regularly recommend and sell only eight or 10. Each product has its own set of characteristics as well as eligibility requirements. It requires a highly skilled sales force to be able to learn to effectively sell 100 products, as some of these products have a very complex vetting process.
Customer service representatives typically sell the most popular product in each category. For example, free checking is the most popular but it is not necessarily the best product for the customer or for the bank given its low profitability. According to our own studies, based on three million interactions, retail banks recommend the wrong product between 30% and 65% of the time. What the sales reps don’t realize is that most customers are eligible for between seven and eight products. By presenting the seven or eight eligible products at the point-of-sale and educating the customer, the likelihood of selling multiple products and opening multiple accounts increases significantly.
Increasing sales performance, end-to-end productivity and efficiency. Technology now enables banks to gather customer data online and in real time at the point-of-sale using a recommendation guide, a real-time personalized and automated sales playbook that matches banking products with customers’ eligibility, needs and preferences. Combined with underlying analytics, this automated process can be used to gain immediate insight into a potential customer and to automatically pre-qualify the lead. This gives sales an opportunity to close more deals and become more productive.
This same technology can be used when a customer meets with a branch representative or calls into the contact center. Instead of the customer entering the qualifying information as they would when surfing the Website, the customer representative can engage in a conversation, gather the information and enter it into the recommendation guide.
Automating the pre-qualification and product recommendation process provides another benefit – sales performance analytics. Implementing a sales reporting system with profit-based metrics is a key success factor in increasing sales performance. Productivity reports using various analytics that illustrate what was recommended, what was sold and a gap analysis of what should have been sold is an invaluable tool for management in helping boost sales productivity.
Whether the sales staff exceeds or fails to meet the established productivity standards, the productivity report keeps the manager informed. When a salesperson or sales staff does struggle, looking at the raw numbers can offer insight into the problem. Productivity reports can also provide insight into the profitability of what the team is selling.
Although banks purchase quite a bit of customer research, the data is transactional-based and not necessarily based on what the customer wants or needs. The trends illustrated tend to be broad-based market trends and not necessarily relevant to the bank’s current customers. For example, the bank that generated 500,000 online visitors per month realized that most of its business customers were using manual payroll. This trend was never uncovered in research that the bank had purchased and prompted it to come out with new, high profit products to address this need.
It is clear that analytics is changing the way operationally excellent retail banks are selling their products and learning about their customers.
