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detractors business impact on financial services

The business impact of detractors for financial services

While most companies focus heavily on new customer acquisition through different marketing channels to increase revenue, a more efficient way to drive growth for financial services is to reduce the detractor rate and therefore its financial impact. This is especially true in the context of financial services (bank/insurance/etc.) because the customer lifetime value (CLV) is heavily correlated to the account activity.

The goal of this guide is to answer 4 questions:

  1. For non-CX expertsWhat are detractors?
  2. Why is it a harder problem to solve in the financial service industry?
  3. How to measure the total financial impact of detractors?
  4. How to reduce the financial impact of detractors?

For non-CX experts, what are Detractors?

Detractors, in the realm of customer feedback, are individuals who have had negative experiences with your company’s services or products. An effective way to identify detractors is to ask an NPS (Net Promoter Score) survey from 0 to 10 “How likely are you to recommend our company to your friend or family?“, every customer that replies with a score under 7 is a detractor. These customers are not just dissatisfied; they are likely to discourage others from using the company’s services, posing a risk to brand reputation and customer loyalty.

NPS survey can identify detractors at many touchpoints in your customer journey, a couple of examples could be:

  • After opening a new account/credit line/credit card or any financial service
  • After contact with your customer support team
  • After using your company’s new mobile application or new online account page
  • At a given frequency (every quarter/year/etc.)

Why is it a harder problem to solve in the financial service industry?

The financial services industry, which includes both B2B and B2C sectors, is particularly affected by detractors because of its essential role in clients’ finances. Here are Feedier’s top 5 observations to address this question:

  1. Less churn but… sleepy detractors. While many industries can detect an unsatisfied client because he doesn’t buy back or leave a bad review or simply churn, in the financial service in 95% of cases a reactor is going to be a “sleepy detractor“. This means the customer will not close his account due to closing fees or the time it takes. The volume of transactions and services used is, however, going to significantly decrease to near 0 and so will his Customer Lifetime Value (CLV).
  2. Massive impact on One’s life: Financial services directly affect individuals’ and businesses’ economic health, making any negative experience more impactful and potentially long-lasting.
  3. B2B vs B2C. The expectations and relationships differ significantly in these 2 segments, with B2B clients looking for reliability and strategic partnerships, whereas B2C clients prioritize convenience and personal financial growth.
  4. Personal data’s integrity, confidentiality, and security. Identifying detractors at scale and solving the problem means being able to centralize different data sources (CRM/customer feedback/activity/agents/etc.) that are in the financial services context usually siloed for security and confidentiality reasons.
  5. Scores of new digital native competitors. With digitalization in our everyday lives in the last decade, a wide array of competitors has come out to replace traditional services. These new players are 100% customer-centric and focused on disrupting existing institutions, making the cost of detractors even more impactful.

So, while it’s not straightforward to identify detractors, the financial impact is usually so important that it outweighs the pain and investment.

How to measure the total financial impact of detractors?

Formula and explanation

Although, so-called experts would likely give you a more complex formula, a simple yet efficient answer would be:

Total financial impact = (A) Number of unique detractors x ((B) Average cost of a detractor + (C) CLV)

A good scope would be to look at it with data on a monthly or quarterly basis.

(A) How do I find the number of unique detractors?

Very simple, the answer lies most likely already in your customer feedback for the given period you are calculating for. You can identify in all your NPS touchpoint surveys / or customer reviews the sum of detractors and divide this number by their unique customer ID. So, if you have a very unhappy customer who is identified as a detractor on 2 channels (for example with your company’s customer support, mobile application NPS), this client is only counted as one detractor.

(B) How do I calculate the average cost of a detractor?

Quantifying the average cost of detractors is a little bit more tricky than (A) and (C). It involves measuring:

  1. Additional support costs
  2. Negative impact on new customer acquisition due to tarnished reputation

For the first one, Additional support costs, you can use data from your support center to get the time spent on the detractors’ cohort. Where it could get more complicated is that most detractors, when they are not in “sleepy“ mode, so at the moment they become detractor, will call/email/chat multiple times. Therefore, the goal is to get the average time per detractor (in hours on the frequency you have chosen) and multiply it by your internal support hourly cost. If it’s not so clear, please refer to the example below.

Regarding the second one, you would need the customer acquisition cost and a way to measure impact if you were to improve the conversion rate of new customers. So, if you were to reduce the number of detractors, it would increase online review scores and customer feedback levels, leading to a higher conversion rate and therefore lowering the cost of acquisition.

(C) How do I calculate CLV (Customer Lifetime Value)?

The Detractors’ CLV is used to get a very accurate number for revenues at risk. There are a lot of available methods to calculate CLV for every industry — including financial services, but it does vary a lot based on service type and client type. Before trying to calculate it yourself, we highly recommend asking internally, you very likely already have this information internally.

If not, here are some research you might consider:

Example

Let’s do an example to calculate the impact for the last quarter.

  • We have identified 5,500 unique detractors across all customer feedback in the last quarter.
    So, A = 5,500
  • We have identified that the cost of customer support per detractor is on average 10 min per month, so 30 min last quarter, with a cost per hour of support of $60, so $30 per detractor last quarter.
    So, B = $30
  • Let’s assume that in our example CLV is $3,500. So, C = $3,500

Total financial impact last quarter = (A) 5,500 x ((B) $30 + (C) $3,500) = $19,415,000

Global Impact

The variable you have the most control over is (A) — The number of detractors, the goal is to get (A) as close as possible to 0.

Detractors can significantly reduce EBITDA through direct loss of revenue and increased operational costs (support cost). Measuring the shift in customer satisfaction and its correlation with financial metrics can help quantify this impact at scale.

How to reduce the financial impact of detractors?

Our insights are based on our existing customers, but every company is unique, even in a similar industry.

Go from Feedback Management to Customer Intelligence

Feedback management or Voice of Customer system will help you to measure NPS at given touchpoints, report NPS scores (structured feedback data) and close the loop on the field. Besides the low ROI, several limits exist in such a system:

  • Lack of centralization from other sources of detractor signals: emails/reviews/interviews/etc.
  • Limited usage of your business data, most of them will link to your CRM or customer support system but will not connect to other critical data sources (entities mapping, agents mapping, customer segments, tag manager, etc.). Furthermore, most integrations are not agile and are built by external consulting services.
  • Poor usage of unstructured feedback data (text), most of the answers to solving the detractor problem are already in the feedback but it’s a matter of making the insights visible and easy to act on. When they do, your customers’ most important data and the company’s insights (weaknesses according to customer feedback) are used to train an industry-specific AI model that your competitors could access if they were to choose a similar vendor.

The goal of a Customer Intelligence Platform is to turn feedback signals into reliable customer intelligence which are easy to access, easy to understand, and easy to act on.

Key principles include:

  • Centralizing feedback signals from all sources into one place — no data silos.
  • Enrich customer feedback from as many data sources as possible to identify root issues faster.
  • Provide ultra-secure architecture (ISO 27001 certified) and advanced data governance.
  • Empowering non-data-savvy employees to act with an ultra-intuitive interface provides a reasoning level for generating insights and triggering actions.

Once this task is completed, what are the subsequent steps to reduce our number of detractors to zero?

Identify root pain points

One approach to addressing the issue, commonly adopted by many organizations, is called “Close the Loop”. It involves reaching out to detractors immediately after they have been identified as such by field agents or support center teams. However, this method presents a significant drawback: it is not only highly costly but also comes too late. It focuses on resolving the outcome rather than tackling the root cause of the problem.

A second approach is more of a reactive process to identify the root pain points in the customer experience. To identify root issues, you need 3 types of data correlated together to have 3 levels of analysis:

  • Level 1: Structured feedback data (review scores or NPS scores)
  • Level 2: Business/Operational context (CRM/CDP/Support system/etc.)
  • Level 3: Unstructured feedback data (text answers to open-ended questions like “What can we improve?“)

When you mix the 3 and use software to answer the following questions

  • Level 1: Who is a detractor?
  • Level 2: What are the top 10 contextual attributes that correlate with detractors the most?
    Some examples of contextual attributes are customer age segment, customer support center, services used, agent in charge, customer type, etc.
  • Level 3: For every attribute that is correlated with detractors, what are the key pain points mentioned by customers?
    This level requires AI to help you process thousands of unstructured feedback and do tasks like synthesis, topic generation, list of improvements, etc.

This should give you a list of 10 pain points that are highly correlated to detractors. For every pain point, you want to have:

  • The number of detractors related to this pain point
  • Key business attributes (for example: 80% of customers mentioning this pain point are 60+ old clients)
  • List of improvements from customer feedback using AI
  • Action plan from your CX team

Prioritization with an ROI model

When ordering the list of root pain points by the number of detractors and attaching the related revenues at risk, this will give your team an action sheet that is reliable and driven by customer expectations and business value:

[fusion_table fusion_table_type=”1″ fusion_table_rows=”” fusion_table_columns=”” margin_top=”” margin_right=”” margin_bottom=”” margin_left=”” hide_on_mobile=”small-visibility,medium-visibility,large-visibility” class=”” id=”” animation_type=”” animation_direction=”left” animation_color=”” hue=”” saturation=”” lightness=”” alpha=”” animation_speed=”0.3″ animation_delay=”0″ animation_offset=””]

Pain point # Detractors last quarter Business impact (CLV x # detractors) Key business attributes Key topics Aciton plan
ROI is here.

[/fusion_table]

Measure Improvements impact

After implementing improvements based on customer feedback, it’s important to evaluate the impact of these changes by measuring trends in detractor rates and overall customer satisfaction. This variation, or “delta”, between pre- and post-intervention measurements offers tangible evidence of the effectiveness of your efforts and their positive influence on customer satisfaction and loyalty. This evaluation process is the starting point for rigorous monitoring of various key performance indicators (KPIs).

Among these KPIs, the Net Promoter Score (NPS) stands out by assessing the degree to which your customers are likely to recommend your services to their friends and family, directly reflecting their level of satisfaction and loyalty. Similarly, the Customer Satisfaction Score (CSAT) allows you to capture customers’ immediate feedback on a specific experience with your brand, while the retention rate reveals your company’s ability to maintain customer interest and commitment over the long term. In addition, Customer Lifetime Value (CLV) quantifies the total value a customer represents to your company over the whole of their relationship with it, providing a perspective on the effectiveness of your loyalty strategies.

When tracked optimally, these indicators provide valuable insights into the effectiveness of customer experience improvements. Analyzing them, you can identify key successes, highlight points requiring further adjustment and, ultimately, turn your company towards an ever more effective customer-centric strategy.

Conclusion

Detractors in the financial services sector pose a significant risk that is too often ignored by leadership, not just due to potential revenue loss but also because of the critical nature of the services provided.

By understanding the unique challenges of financial services, measuring the financial impact of detractors, and taking targeted data-driven action to address detractor feedback, companies can mitigate these risks, enhance customer loyalty, and improve financial performance.

About Feedier

Looking to reduce the number of detractors? Feedier’s Customer Intelligence Platform simplifies customer data mastery (from both non-structured feedback data and structured business data) and accelerates decision-making at the operational level, empowering our users to lead with impactful insights. With Feedier, they harness their customer data and take advantage of AI, and automated reports to illuminate the path forward to rd, ensuring they’re not just competitive but ahead with confidence and clarity.

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