Customer Engagement

3 Brands Crushing Their Customer Experience and What You Can Learn from Them

5 mins read
October 22, 2019
By
Total Expert

Customers aren’t sizing your financial brand up against other banks or credit unions, they’re sizing you up against all other companies. And the competition for great customer experiences is stiff.

Your credit union may not sell everything under the sun, but you’re still competing with online retailers around the globe who have vast resources and hoards of data scientists spinning their clicks into valuable insights. These brands have mastered personalization and they’ve raised the bar for everyone.

The good news is that you don’t need to be funded by Jeff Bezos to deliver a great customer experience – you just have to be open to learning from the masters and applying their lessons to your financial brand. To get you started, here are three of our favorite approaches to creating an excellent, memorable customer experience that come from three major brands:

1. Turn Your Experience into a Club Like Starbucks

There are few success stories as bold as Starbucks Rewards. The coffee giant introduced this program in 2009 and saw incredible growth in use: Active membership was up to 16 million as of December 2018, a healthy 14 percent increase over the prior year.

But how did they get to a place where Starbucks Rewards transactions account for 40 percent  of tender in their company-operated stores? They build a great mobile experience – so good that customers would rather order and pay by app than with cash from their old, leather wallets.

In this push, Starbucks did three brilliant things:

  1. They gamified customers’ orders using a points system that incentivized developing regular purchasing habits and trying new items.
  2. Their app acts as a recommendation generator that introduces customers to products they may not have tried before.
  3. Starbucks uses their app to soft launch new products and give users the sense that they have an exclusive edge on the rest of Starbucks shoppers.

What makes Starbucks Rewards successful is that is makes being loyal fun and rewarding, and it’s accessible in the app, on a desktop or wherever you need their services. Their choice to go omnichannel may not seem all that important, but being both mobile-forward and desktop-friendly, they enable office workers to order a cup of coffee and pay online without taking out their personal phone at their desk. The experience they’ve built demonstrates that they understand their customers’ needs and caters right to them, wherever their customers are in their day.

2. Become a Recommendation Engine Like Amazon

Amazon doesn’t have loyalty at the level of banks yet, but they do have the traffic: 9 out of 10 consumers check a product’s price on Amazon before making a purchase. As the first point-of-contact when a customer needs to know what the best product to buy is, Amazon has established itself as the defacto search tool for getting the best product at the right price.

The good news for financial brands is that Amazon has yet to claim this position when it comes to financial products and services. Your organization can leverage user data to position itself as the resource customers seek out when they need information.

Serve up recommendations that are relevant to your customers every time they have a questions and customers will think of you as the first point-of-contact or resource when their next question arises.

3. Let Customers Live Your Brand Like Capital One

Encourage customers to live your brand by making it a part of their routine. For example, if your credit union is all about supporting your community through financial health, you might redesign your branches to be community-oriented social spaces.

The best example of this actually comes from a financial brand. In 2018, Capital One opened its first Capital One Cafes, where baristas sling coffee at half-price to the brand’s customers and at full-price to folks who are just dropping in for desk space and a hot beverage.

Capital One staffs these locations with customer support representatives and financial advisors, putting their bank’s services in close proximity to busy folks looking for coworking spaces. And this fits in perfectly with the level of customer support their brand promises and delivers: they’re there for you when you need them. In their new Capital One Cafe experience, they’re also there with a cup of coffee and convenience.

The other way Capital One integrates their brand promise into their customer’s daily lives is Eno, an AI app that helps flag suspicious transactions and preempt fraud by monitoring customer accounts. Eno provides customers with peace of mind by sending emails or alerts to help customers address suspicious transactions or extra-generous tips on restaurant bills.

Capital One makes it easy for customers to place their trust in the brand by being accessible and easy to interact with, digitally and in-person.

Use Modern Marketing Techniques to Lead in Your Industry

Modern marketing has changed banking forever, and this is a good thing. From Starbucks’ exceptional rewards program to Amazon’s incredible price comparison machine, big brands are pushing the envelope and showing everyone else what we need to do to lead in our own industries.

It may feel intimidating to realize that you’re competing with Netflix to have the best customer support in town, but this is a good thing. The techniques you borrow from big brands can help you figure out how to incentivize customers to open up a new line of credit or they can lead you to diversify the products available within your brand ecosystem.

Deploy proven marketing tactics to become a leader in your own vertical, and watch your financial brand’s foothold grow.

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By Pete Karns, Chief Product Officer, Total Expert

AI is no longer a future state—it’s already here, embedded in everything from ride-sharing apps and food service to factories and farms. In the world of financial services, though, this ubiquity comes with pressure to integrate AI fast, appear innovative, and keep up with competitors—all while being mindful of evolving federal and state compliance requirements. Moving fast without a plan or awareness of up and downstream implications often leads to AI-enabled solutions that either underdeliver or don’t deliver at all.

At Total Expert, we’ve taken a different path: thoughtful integration over flashy announcements. As more financial institutions wrestle with what “real AI adoption” should look like, here’s what we’ve learned and what lenders need to consider to get it right.

Where enterprise AI goes wrong

Too many financial services leaders have experienced what I call “AI failure to launch (and scale).” They’ve rushed to try unintegrated AI-enable offerings and bolt on AI tools—often generalist chatbots, white-labeled versions of generative tools, and/or hooking up to MCP servers—without a clear sense of how these tools will solve their business problems or add potential risk. The result? The occasional value-add result. However, what we see more is poor user adoption, wasted spend, and limited impact.

This is the same trap we saw with “digital transformation” a decade ago, or the original horizontal SaaS applications that evolved or were replaced by vertical-specific solutions. AI-enabled solutions offer tremendous, generational promise but they risk becoming vanity-first, value-later tools. We are focused on the former.

AI that thinks and adapts: Welcome to agentic AI

Let’s make one thing clear: not all AI is created equal.  

Chatbots have been commonplace in financial services for a decade now, but remain rigid, rule-based tools that handle repetitive tasks.  I’ve worked with “AI” services for more than 15 years and each had their own place and potential when used properly. Herein lies the opportunity. Modern lenders that are focused on retaining and growing their customers in an ultra-competitive market need something more dynamic. Enter AI agents that can understand context, adapt on the fly, and speak in a human-like way. These agents are coachable, brand-aware, and learn from every interaction. They don’t follow scripts—they think in real time. And when built correctly, they become a seamless part of your customer experience.

This is the evolution from AI as a support function to AI as a trusted team member.

Total Expert recently launched an AI Sales Assistant that puts this principle into action. It functions as a scalable, intelligent teammate—able to engage leads, deliver personalized conversations, and identify high-potential opportunities—all while staying aligned with your brand voice and compliance requirements. It’s not a chatbot bolted onto a CRM—it’s a fully integrated AI-enabled solution, utilizing data, embedding within workflow orchestration, and playing nice with application logic because it has the necessary context to work within your lending ecosystem.

The real “why” behind AI adoption

Before choosing any AI solution, or any technology solution, financial services firms must ask themselves: What business problem are we solving?

For example, when mortgage rates dropped for a few weeks in September 2024, our customer intelligence capabilities identified nearly $2 billion in immediate refinance opportunities. But no team of loan officers could scale quickly enough to reach every qualified lead. That’s where AI tools prove invaluable—automating first-touch outreach at scale, surfacing the best opportunities, and empowering human teams to scale up execution to drive retention and growth.

Why embedded beats bolted-on

The types of AI-enabled solutions we are talking about can’t function effectively in isolation. Without access to timely and accurate customer data, and invoked within a specific workflow process, it can’t personalize interactions, anticipate needs, or drive conversions at the right time.

Picture an AI assistant offering a refinance to a customer, only to stall when asked for more details. If it doesn’t know the customer’s current rate or financial profile, the experience feels hollow. That’s not just ineffective—it damages trust.

By contrast, when AI-enabled solutions are embedded within a unified customer experience platform like Total Expert, it draws on a 360-degree view of the customer. It knows the data, understands the history, and delivers contextually rich conversations that convert.

This is why we’re designing our AI capabilities with a focus on the unique needs of financial services organizations. The same purpose-built approach has earned the Total Expert platform its unmatched reputation for usability and time to value.

Generalist AI offerings can be a gamble that increase costs—and time to value

Implementing AI that’s not purpose-built for financial services introduces two major risks:

1. Usability failure: Your team must spend months customizing and configuring a generalist AI tool to make it work for your specific needs—if it will ever work at all. For example, imagine you’re a loan officer and one of your referral partners introduces you to a borrower. Now, you have to choose the best way to approach the first conversation with this borrower. There are countless permutations of questions and answers which all require deep personalization, compliance awareness, and consistent representation of the sales processes and brand tone of the lender. Generalist AIs will quickly reach their limitations in these complex use cases.

An industry-focused AI offering will be trained on this specific use case and provided with the context needed to hold a dynamic conversation with the borrower. This type of AI learns and adapts with each interaction, performing the most time-consuming tasks so you don’t have to.    

2. Compliance risk: Without built-in industry guardrails, you’re gambling with regulatory violations and brand safety.  As we know, the compliance landscape for financial services is broad and evolving at the federal and state level.  Look for AI offerings that are regulatory aware and enable you to configure them based on your organization’s risk tolerance and interpretations.

Lenders don’t need more tools—they need the right tools—ones that work out of the box, understand industry nuances, and deliver immediate, compliant value.

Ask these questions before you commit to an AI offering  

To maximize the probability of success, here’s a quick checklist for vetting solutions:

  • Can it solve a real, high-value business problem, and how? Review specific examples and ask to speak with other organizations that have implemented the tool.
  • Does it function as a true AI agent, not a static bot?
  • Can it be deeply integrated into your core system(s), workflow orchestration, and data?
  • Does it include financial industry compliance and brand guardrails?
  • Can it scale without sacrificing quality or regulatory integrity?

Building the future with purpose-built AI

Total Expert has always designed technology with financial services in mind, and our approach to utilizing AI is no different. We’re not chasing hype. We’re solving problems.

Our focus on AI isn’t simply building standalone features—it’s about embedded, intelligent, and deeply integrated AI solutions. It’s helping lenders scale smarter, engage more meaningfully, and turn data into action. Our AI Sales Assistant is just the beginning—an example of how purpose-built, AI-enabled solutions can solve real problems and deliver tangible value. We are already testing and exploring other AI-enabled solutions and I could not be more excited about the current and potential value our clients and our market will achieve.

Because when AI works, it’s not just impressive—it’s indispensable.

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