Editor's Note: This piece originally appeared in the October MReport, click here to view the full issue.
As a lender, you’ve talked to a lot of people about their mortgage options over the years, and many of them probably slipped through your fingers. They may have gone with another lender, decided not to buy a house, or simply become distracted and decided refinancing wasn’t a high-enough priority for them to set aside the time. Whatever the reason, wouldn’t you like to know when they become interested in that mortgage again so you can time your outreach perfectly? You would probably like to have additional insights about:
- which customers in your portfolio are shopping around online;
- whether your aged leads are continuing to shop for a lender;
- which consumers have high intent (high interest versus window shoppers) and should receive more aggressive marketing; and
- which consumers aren’t ready to buy and are an inefficient use of marketing dollars and time.
If lenders knew all this, they could drive more relevant conversations and experience better outcomes, resulting in more funding. Protecting a portfolio takes a few simple, yet effective steps. By blending people-based marketing with rich data insights, lenders can tell if their stale lead has re-entered the market before they show signs of intent that the competition can see.
Protecting Your Portfolio
Servicers may have won the battle to acquire a new customer, but they won’t grow a successful business by just passively sitting back and collecting mortgage payments. Knowing which customers are at risk of leaving the portfolio for a new mortgage lender and then engaging them to retain their business is a vital part of growth and profitability. Acquiring early signals of in-market activity not seen by other lenders shines a spotlight on which customers are expressing interest in a new mortgage before they talk to another lender. This creates opportunities to maintain pro t-margin goals while greatly im- proving portfolio retention rates.
Data is the key to consumer insights, and the data-as-a-service (DaaS) industry is creating an ocean of information available to lenders to help take marketing engagements and contact strategy to the next level.
With activities such as investigating rates and online comparison shopping now possible, lenders could represent opportunities to acquire, retain, or grow that customer relationship. Jornaya research reveals that, on average, consumers are shopping for a loan 170 days before they sign closing documents. One in three new leads continues shopping for a lender in the 90 days after filling out an online quote form. When used correctly, this type of data can provide the competitive advantage lenders need to thrive in this new mortgage environment.
Marketing in the mortgage industry has evolved over the past 20 years. There was a time when sales managers would print leads and hand them out to the sales floor, and the loan consultants would have three folders on their desk for hot, warm, and cold leads. The rest would take care of itself (or not). Today, lead management systems are driving automated contact strategies, lead routing is more intelligent and based on scoring algorithms, and auto-dialers blaze through calling thousands of leads faster than you can say, “Let’s get you locked in before rates jump again.” When a lead is delivered into a lender’s ecosystem, the consumer enters marketing automation purgatory—receiving hundreds of auto- mated calls, emails, and texts for months and months. Marketers are expending a lot of resources to reach out to as many consumers as possible, in many ways, multiple times each, unaware of their current level of interest and contact preferences. This is the worst-case example of “lead-based” marketing—and it has grown expensive, stale, and unappreciated (to say the least) by the consumer.
Today, top marketers are driving results, especially in mortgage, with data-driven tactics using behavioral and attitudinal data sets. This data is being incorporated into contact strategies to create more sophisticated and individualized interactions that generate a positive response. This methodology is called “people-based” marketing. It revolves around insights from a growing set of simple, easy- to-understand data outputs that allow lenders to deliver the right message to the right consumer at the right time in the right medium. The results have been astounding, and the customer experience is dramatically improved, resulting in higher conversion rates.
Attitudinal and Behavioral Data
Attitudinal data is information about how a person feels toward a product, service, or their experience with a lender. Simply put, it reflects their attitudes. This dataset is used to form consumer profiles that help the marketer understand how a customer typically buys. Are they a techie who will love the digital mortgage- application process? Will your direct-mail piece immediately go in the recycling bin? Will they be receptive and responsive to text messages? Knowing a consumer’s preferences enables a more in- depth experience and optimization that results in higher-quality conversations and engagements. Behavioral data is the champion of predicting outcomes and delivering insights based on specific consumer actions. This data set provides clarity on the consumer’s changing intent throughout the buying journey. Are they just curious about today’s 30-year fixed rate? Do their actions indicate they are ready to buy now? Are they a “window shopper” or seriously considering their options? What time of the day is best to reach them?
Credit triggers are one solution for measuring a consumer’s intent. Unfortunately, it also means they’ve likely selected another lender and are late in the buying cycle. The same goes for MLS listing alerts. So many lenders subscribe to these services that it’s a rat race and difficult to achieve success relying on these as your sole source of behavioral data. However, there are newer sources of behavioral data points available with in-market indicators available well before a credit trigger. These will give you a leg up on the competition, such as time spent on a mortgage-related website, the number of visits to these sites over time, when those visits occurred, and more. These data points are indicators of a consumer’s likelihood to start the mortgage process and can drive optimally timed calls, emails, and texts.
Driving Better Results
Lenders can spend a fortune on marketing to potential customers and can put an enormous effort into optimizing lead management strategies for maximum returns. Studies have analyzed performance relative to speed-to-contact attempts, and the quickest mortgage lenders achieve a mind-blowing four seconds between the time they receive the consumer inquiry and when they dial the consumer.
This unprecedented need for speed-to-contact has caused industry marketers to quote Ricky Bobby, Will Ferrell’s character in “Talladega Nights,” by saying, “If you ain’t first, you’re last.” But with the robust amount of data available to lenders, this is no longer the case. Industry-leading marketers are now focusing on the people behind the lead. They are tailoring their outreach optimized to the likelihood a person will respond positively. People-based marketers are playing chess while others are playing checkers, with the cost of acquiring a new customer improv- ing substantially as a result.
Onboarding and taking action on unique data sets are no longer overwhelming tasks. Lenders share basic consumer information with their DaaS partners to unlock an array of complex and valuable insights delivered in a simple and actionable manner. Regardless of a lender’s level of data sophistication, there are a few predefined ways to take action: simple, matrix, or artificial intelligence (AI). Here’s how each of these models works:
- Simple models combine a basic understanding of different groups by quadrants. The consumer is either high or low value, with high or low in-mar- ket activity creating four buckets of high/high, high/low, low/high, and low/low. It deploys a unique contact strategy for each group. This upfront effort to move away from a one-size-fits-all strategy will pay dividends.
- Matrix combinations create even more groupings. For example, a four-by-four matrix will create 16 buckets that are more granular and can include details such as a preferred method of contact and in-market activity. Testing and optimizing these buckets is where the real magic lies. A healthy amount of focus is required to execute a matrix strategy, but the bene t to the customer experience generates far greater rewards.
- Though marketers widely discuss AI, it remains a mystery to many. This hyperpersonalized approach is very tempting (and sounds really cool) but is currently limited to lenders with deep pockets and resources. However, the industry is looking at ways to make AI capabilities more accessible for everyday lenders.
Gaining a clear view of customers and their preferences is what elevates lender performance in today’s mortgage environment. It’s becoming easier than ever to connect your consumer information with additional data sets in order to paint a complete picture of the consumer with whom you are trying to create or deepen your relationship.
People-based marketing has helped improve conversions, create a better customer experience, and save valuable marketing and operational dollars through efficiency gains. Add rich data insights and lenders will drive more timely and relevant interactions with their consumers while driving increased revenue to their bottom line.