Lending

Customer Profiling: Evaluating for Engagement

5 mins read
November 27, 2017
By
Total Expert

Every company needs a legion of eager, self-starters fanning out across the marketplace to generate production and profit. But it takes a lot more than personality, proficiency and product knowledge to make the connections necessary to become a consumer’s choice for one of the biggest transactions they will make in their lifetimes: mortgage financing. For salespeople to be effective, they can’t simply hit the pavement with what they want to sell – they must first spend some time considering the people who need what they have.

Delivering an elevator speech about 20% down jumbo loans to a renter in the first-time home buyer price range is the mortgage equivalent of trying to sell a speedboat in the Sahara Desert. Before a lead can convert, a consumer must engage, and consumers only engage with what they find relevant and interesting. Taking time to profile your target customers saves time and increases effectiveness. Customer profiling isn’t a one-time exercise: consumer mindsets shift with market conditions – and your marketing approach should too.

In order to properly connect with the public, companies and mortgage loan officers (MLOs) should first take time to assess target customers and uncover their apprehensions. Next, juxtapose the goals and concerns of your prospect audience with your own agenda and the messages you typically use. You may find that what you’re saying, promoting and sending out doesn’t address the questions and concerns of the people you’re targeting. One major area of public misunderstanding offers tremendous opportunity for companies and MLOs to educate and truly be of service: down payment requirements.

Perception vs. Reality

Anxiety about having to amass a significant amount of money is easy to understand when we see how often 20% is touted as the typical down payment by the mainstream media, financial advisors and even industry experts like Zillow Chief Economist Dr. Svenja Gudell, who regularly uses 20% as a baseline in her reports and market commentary. The commonplace usage of 20% as “the” required down payment explains the public misconceptions, but professionals in the mortgage industry know better. Recent financing patterns noted in the National Association of Realtors (NAR) 2017 Profile of Home Buyers and Sellers proves 20% down payments aren’t necessary – or even common:

  • 88% of recent home buyers financed their home purchases and the average loan-to-value was 90%
  • First-time home buyers who financed their purchases put 5% down
  • 43% of home buyers saved for their down payments in six months or less

Whether the professionals questioned by Genworth were responding with what they think consumers have trouble with or based their answers on actual client experiences, the belief that 20% down is required to buy a home is certainly prevalent.  

Companies and MLOs need to do regular “mindset checks” and compare their own opinions with current consumer data and evaluate whether their marketing, outreach and overall communications are accurately addressing consumer attitudes and concerns. For example, drip campaigns and messaging that urge consumers to act on favorable interest rates, the importance of getting pre-approved for a mortgage and promoting the long-term benefits of homeownership won’t be effective if the recipients don’t think they’ll ever be able to come up with a down payment. Debunking this misunderstanding provides mortgage professionals with a great opportunity to engage consumers.

Speak to the Issue(s)

Review what your company and loan officers are saying and sending out – is it outdated, dull or so generic that it’s meaningless? Since down payment is a universally daunting aspect of the home buying process, a large portion of the public will find communication that addresses that obstacle head on relevant and helpful. Whether initiating a long-term campaign or simply firing off emails to various leads, try provocative subject lines like these to capture interest:

  • 5 is the new 20…
  • Home in six months?
  • Take 5 (percent)…
  • 0 to down payment in six months?

Include information like stats from the NAR report in the body of prospect emails so your leads will see that a large portion of successful buyers were able to get into their homes with less than what most people assume is the minimum:

Dear [Prospect],

Did you know that most home buyers aren’t putting 20% down? According to the National Association of Realtors 2017 Profile of Home Buyers and Sellers…

  • 5% was the typical down payment for first-time home buyers
  • 10% was the average down payment for all home buyers

Additionally, 43% of recent home buyers were able to save for their down payments in six months or less.  Do you know what options are available to you? I’m here to help you find out!

Though down payment isn’t the only issue facing people interested in becoming homeowners, it affects most potential buyers, so the topic has broad relevance for marketing. Evaluate other market segments such as your past clients, sphere of influence and geographic target areas for other specific issues as well.  “Getting your name out there” is fine, but converting leads and closing transactions is better. Make customer profiling a regular, periodic exercise to ensure that your outreach is effective and profitable. You’ll find that it pays to keep up with what your target customers are thinking.

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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.

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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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