Prospecting—Intelligent Farming Strategies

Finding new customers/members is essential to growth for any financial institution. Consider this; there are about 36 million consumers who might be convinced to switch financial institutions. The opportunity is out there. According to an online Harris Poll, 38% of consumers considered opening an account at their neighborhood bank or credit union, but only 5% said they might actually do it. Convincing them to switch to your institution is the challenge.

Prospects are out there and they are interested in switching to local banks and credit unions. To reach and motivate them, your offers must be timely and relevant in addition to websites being easy to find and navigate.

To SEO or SEM …

The first step for most consumers is usually an online search. There are 3.5 billion Google searches a day! And that grows about 10% every year. Search Engine Optimization (SEO) and Search Engine Marketing (SEM) have been around a while now. When implemented properly, there should be an increase in the quality and quantity of web traffic. SEO attracts organic traffic to your site and takes more time to build. But it is unique to your brand and message. And it’s free. SEM isn’t. For an established fee, SEM helps gain visibility and funnel traffic to your site. In its ideal form, your institution appears at or near the top of the search results page.

This is not an either/or proposition. They both increase traffic and brand credibility; they both need to be part of your marketing budget. SEO may take more time to ramp up, however, it’s more sustainable and not easy for competitors to imitate. On the other hand, SEM delivers faster results, scales easily and targets specific segments. Used together, they optimize your search strategy to drive more viable leads.

When developing your search engine strategy:

  • Determine keywords based on strengths
  • Create compelling, keyword-rich content
  • Tell your unique story
  • Think like a customer/member

Location-based Marketing

Mobile has disrupted everything by transforming customer experience and expectations. The one term tied to mobile is “on the go.” People are no longer attached to one place. Location-based marketing takes advantage of that mobility by delivering offers based on physical proximity.

Geo-fencing

Geo-fencing creates a virtual perimeter around a business solely to target advertising. When a compatible device enters the perimeter, it receives an alert and/or email. For example, if a potential lead is playing on their phone within a defined perimeter, the lead might receive targeted advertisements for other businesses within the geo-fencing zones.

  • Establishes virtual fences to give marketers incredible control over placement.
  • Utilizes a virtual barrier around a phone’s IP address.
  • Displays ads on a device within the pre-established area
  • Targets those entering and leaving the perimeter, regardless of whether the location is your own or that of another

Geo-targeting

Geo-targeting is more focused than geo-fencing. It delivers messages based on location, past purchases and data points like demographics and P$ycle. The more data you have, the more you know about your customer/member and the better you can deliver relevant messaging. Data sources and segmentation are essential for a successful geo-targeting campaign. Using an industry benchmark of 0.40%, financial institutions’ click-through rate (CTR) performances for geo-targeted mobile displays improved to 0.64%.

  • Find the right venues where your prospects are most likely to be
  • Exclude locations where your prospects are not likely to be
  • Use location-based keywords
  • Analyze data sources
  • Use segmentation

Beacons

Bluetooth beacons are discreet, wireless transmitters retailers place around their stores. When beacons detect a shopper’s Bluetooth enabled app, it sends a signal and the app is activated and the shopper receives relevant communications. For instance, in the retail world, someone browsing boys clothing could be alerted to a great sale on hoodies or sneakers. Financial institutions can set up branch beacons to enhance customer/member experience and deliver relevant offerings. Standard push notifications garner a 7.8% open rate; beacon notifications average a 22.5% open rate. This low-cost solution is an effective way to deliver relevant messaging to a targeted audience.

  • Improves in-branch conversion rates
  • Alerts customers/members to relevant targeted offers
  • Tracks and guides in-store movement

Responding to prospects.

You’ve optimized SEO and SEM strategy. You’ve expanded and enhanced location-based marketing. The leads are coming in. Wouldn’t it be great to engage in real-time while they are still actively engaged? We’ve all experienced it. Search for ACME Shoelaces, and shoelace ads and banners start appearing. Marquis enables similar prospect communication through WebTrax, a part of our DocuMatix on Demand digital product suite. But, instead of showing banners and ads, it sends emails and letters. It enables an automated, secure, non-invasive method to monitor traffic and make offers. Once a lead visits your site, WebTrax notes which pages are viewed, then automatically sends communications based on the pages visited. One Marquis client attributes over 50 accounts and $1 million in balances directly to WebTrax, with a 5.6% response rate over a 90-day tracking period.

When leads visit your site and opt in, they receive relevant, personalized offers they can relate to. It shows your bank or credit union is interested in them as unique individuals and understands their needs. This is key in attracting 58% of consumers who prefer community financial institutions, hopefully motivating them to make the switch and open an account.

Four Segmentation Models for Increased Sales, Deeper Relationships and Stronger Retention

Personalization is a marketing imperative. But it is virtually impossible without segmentation, or the grouping of members/customers with shared characteristics. Successful segmentation allows an institution’s understanding of members/customers to shine through marketing. It lets members/customers feel special and appreciated and is one of the primary retention drivers. Did you know 56% of consumers feel an increased loyalty to brands who understand and act on their personal preferences, priorities and differences?

Defining Segmentation Models

It can be confusing finding segmentation models that apply to financial institutions. Unlike the retail world, a returned product does not present an opportunity to delight the consumer. A closed checking or savings account could indicate that household will not be interested in future products and services. Financial institutions require more focused segmentation models.

When defining segmentation models, financial institutions need to consider opportunity and risk factors, the ability to cross-sell and the likelihood of account closure or balance diminishment. When you take into consideration the vast amount of data available to financial institutions, segmentation can deliver a deep understanding of your members/customers. The following segmentation models enable financial institutions to create winning campaigns founded on personalization. The right message is delivered to the right household at the right time.

Segmentation Model 1: Value Scoring

Value Scoring is an analytical approach that leverages information such as profitability, balances, tenure and product mix to help identify members/customers that drive value. Value Scoring allows you to rank households based on the value they bring to your institution, then compares and contrasts households based on profit, balances, tenure and number of unique products.

This is extremely helpful since losing one major household requires adding eight new average households to make up for the loss. By determining your most valuable members/customers, you can use the Value Score to guide your marketing strategies and nurture those top relationships.

Segmentation Model 2: Lifestage

To determine Lifestage, this model leverages demographic ingredients to provide further visibility into the member/customer based on their financial lifestage. After all, a college student has different needs than new parents. This model gives you the data you need to create campaigns targeted at members within various lifestages and their propensities for having a baby, taking a vacation or paying for a wedding. It enables greater insight on buying activities and behavior. This, in turn, helps craft solid member/customer profiles to inform and influence marketing campaigns.

Segmentation Model 3: Look-alike

Look-alike segmentation learns from those who engage, and finds those who fit a similar profile as the performers. Once you have your customer/member profile, you can evaluate it to find those who fit a similar pattern. For instance, Mary is a 40-year-old mid-income, married female with two children. One is 16. She recently took out an auto loan and each year she establishes a vacation savings fund. Kay is also a 40-year-old mid-income, married female with two children. But she doesn’t have an auto or personal loan. As Mary’s look-alike, offering her an auto or personal loan makes more sense than a credit card offer.

Profiling consumers based on a household’s relationship, lifestage and demographic data allows you to define target audiences based on those attributes and group them together. Then, your team can create offers that the group has a propensity for and potentially bump them into a higher value group.

Segmentation Model 4: Next Product

This is where art meets science, leveraging many of the aspects of the other segmentation models and is best used for point-of-sale channels. Purchasing patterns exist. What’s a hamburger without fries? Pizza without antacid? Analyze your data to determine who buys a specific product, then determine which products they are likely to buy next. For instance, an auto loan can be easily tied to opening a checking or savings account to expedite monthly loan payments.

Go forth and segment.

Once the data is gathered, it’s time to put it in action. For over 30 years, Marquis has helped financial institutions across the country create winning marketing campaigns with measurable ROIs. We focus on adapting proven marketing strategies to the specialized needs of banks and credit unions and have developed a three-step process for leveraging marketing segmentation.

Assemble: Leverage available data sources to identify which variables best select your target audience.

Analyze: Group data sources into segments to simplify your tactical options.

Act: Leverage automation and repeatable processes to act on the segments identified, creating more granular options based on member/customer personalization, including channel preference, product preference, tailored offers and much more.

Putting it all together.

Financial institutions have access to large quantities of data, and that data needs to be segmented, analyzed and used to create intuitive and relevant marketing messages. When segmented properly, it will elevate overall marketing results, allowing you to retain and upsell your members/customers while maintaining their loyalty.

You’ve got the data. You’ve got the strategy. Let Marquis help you put it into action!

*ABA endorses ExecuTrax and OnTrax data analytics solutions for marketing and business intelligence.

HMDA and Public Access to New Data

How HMDA data and increased transparency can affect fair lending.

HMDA submission season is just around the corner and your institution’s data will be under close scrutiny by more than regulators. Litigators, advocates and the general public can view the data and possibly use it to identify institutions at fair lending risk. But since HMDA data alone is not enough, this can lead to misinterpretation, unwarranted accusations and loss of reputation. To help mitigate these issues, maintaining HMDA data integrity is essential.

The Home Mortgage Disclosure Act (HMDA) was created to enhance the monitoring of lending patterns and to ensure financing needs are met across a diverse field of potential borrowers. Submitting loan origination and application data on borrower demographics and loan features enables enforcement agencies to identify financial institutions who excel at fair lending and those that require further investigation. In order to accommodate that goal, new data points were added in hopes to further keep biases in check and reduce barriers to homeownership for protected classes.

The new data delivers a deeper understanding of institutional borrowing practices. Regulatory agencies can now apply comprehensive data screening, data monitoring and statistical modeling routines across all lenders subject to HMDA reporting requirements. In addition, many of the new HMDA data fields, like age, credit score and debt-to-loan ratio, can be used for more effective identification of institutions with elevated potentials of fair lending risks.

With the release of the new data, 2020 is the first time members of the public will have greater access to some of the key determinants of underwriting and pricing decisions. Be assured, litigators and advocacy groups will be taking a close look for any sign of unfair practices. Since disparities are estimated after a broader range of pricing and underwriting factors are applied, litigators can present more credible fair lending cases that on the surface appear to be true than with previous HMDA data sets. Furthermore, journalists will also have access to the data, possibly increasing marketing and reputational risks.

Peer analysis also benefits from the new data. Because it is accumulated from all covered financial institutions, it is particularly helpful for defining local and national benchmarks. Peer comparisons can be expanded beyond penetration rates in minority census tracts to include APR, total loan costs, product features and so on. A clearer picture is presented, allowing regulators to more accurately compare benchmarks and identify institutions with elevated fair lending risks.

With more public access to HMDA data, regulators advise caution when interpreting this data, especially if it leads to accusations or conclusions of discrimination. According to a FFIEC Press Release, “HMDA data alone cannot be used to determine whether a lender is complying with fair lending laws. The data do not include some legitimate credit risk considerations for loan approval and loan pricing decisions. Therefore, when regulators conduct fair lending examinations, they analyze additional information before reaching a determination about an institution’s compliance with fair lending laws.”

In today’s world, businesses rise and fall on the whims of public perception. An unsubstantiated claim of discriminatory lending practices based on misinterpreted data could have far-reaching consequences. What can financial institutions do to protect themselves? Understand your data, especially when underwriting and pricing decisions can create and identify disparities. Realize how your data can be interpreted by public regulators, advocacy groups, journalists and litigators. And then be prepared to tell your story and/or present the corrective and preventive actions taken.

The only way to minimize or eliminate risk is to consistently monitor and analyze your own data for pricing, underwriting and redlining risk. Keeping data clean and relevant is essential for accurate interpretation. In addition, separate assessments should be conducted to identify possible anomalies generated by the expanded data fields. This can be an intensive undertaking. Automated compliance software for HMDA reporting will help ensure data accuracy. At the same time, it will help identify fair lending risk points in the application and origination process. When combined with analysis and interpretation, you should be able to identify any additional risk factors.

Marquis can provide a turnkey solution when combining industry-leading tools like CenTrax NEXT compliance software with the experienced and intuitive skills of the Marquis Compliance Professional Services experts. These services can make a great difference in your HMDA reporting process by regularly monitoring and cleaning your data and then helping you understand the HMDA Integrity Analysis. With cleaner data and a deeper understanding of how it can be interpreted, your institution will be better able to respond when your HMDA data is used by regulators and the public to evaluate fair lending risks.

Six Relevant Data Sources to Create Better Connections

It’s clear. In today’s data-rich environment, retailers must optimize the consumer experience to drive business through actionable insights. 83%[1] of marketers exceed their forecasted return on investment (ROI) by implementing personalization driven by data. 91%[2] of consumers assume brands will recognize and remember them. With first-year churn at 50% for financial institutions, it’s understood that personalization can help reverse that trend.

 “Data is the new oil. It’s valuable, but if unrefined it cannot really be used.”

Dave Humby, Chief Data Scientist at Starcount

Oil starts as crude and is only usable after it’s been refined. The same goes for data. To make it actionable and provide a personalized experience, we need to draw from multiple data sources. The following six data resources will help align your audience with your marketing efforts and help you create timely and relevant communications.

Key Data Source 1: Demographics

Demographics, the study of a population and its components, provide insight into a household’s composition, including finances, life events, buying activities, buying behavior and major purchases. They also deliver facts, like age, gender, income level, race and ethnicity. These components help create solid customer/member profiles and are the foundation of any successful campaign.

Demographics, in combination with your core data, help determine segmentation, where they exist and their basic characteristics. Armed with this knowledge, you can confidently develop your marketing strategy and plan.

However, demographic data is limited. “It offers a singular view, like a snapshot in time,” offers Amy McConnell, VP of Marketing Strategy at Marquis, a financial services market leader. “To really harness the power of demographics, you should use this intelligence in conjunction with other data sources.”

Key Data Source 2: Psychographics

Psychographic data sets explore values, attitudes, interests and personality. From them, we can gain a deeper understanding of our financial institutions’ customers/members. This intelligence gives us insight on where they work, play and how they spend their money. All of which aids in understanding who our customers/members are and how to best reach them.

These insights into individual tendencies enable you to build a robust behavior profile, deepen your understanding of segment behavior and assist with strategic media placement. “Psychographics allow you to target smarter by knowing and finding who needs your financial institution’s services,” McConnell added, “They also help drive retention and enhance product offerings based on usage patterns.”

Key Data Source 3: Propensity

Propensity data defines who is in the market for a specific product, like an auto or mortgage loan, and who is likely to have products elsewhere. Drawn from transactions, online and social tracking, surveys and more, propensity data predicts brand affinity along with customer/member preferences and behavior. This data enables strategic targeting and allows you to implement a mirroring effect. However, propensity information is only the likelihood a consumer is interested in specific product, not a guarantee. It’s best to couple this information with other relevant data sources.

Key Data Source 4: Mapping

Mapping converts data into visual references based on location. The visual effect creates a new perspective, making customer/member and prospect clusters as well as their proximity to you and competitors’ financial institutions more visible. For example, in an area dominated by apartment buildings, a personal loan may seem appropriate; however, when demographic, psychographic, and propensity data are overlaid, the dwellers may be more prone to be in the market for a mortgage. It is important to partner with your compliance affiliates to avoid regulatory concerns and mitigate any risks with the usage of mapping and demographic data for marketing perspectives.

Key Data Source 5: Credit Scores

Credit score data leverages a secondary credit risk ranking to help create segments and determine opportunities. A strong credit score is a great indicator for prequalified offers and prescreening for credit increases and activations. However, credit monitoring services, like FICO, are highly regulated. If used with close monitoring and approval from compliance affiliates, the data can help create a powerful and personalized experience to delight your customers/members and strengthen your connection.

Key Data Source 6: Credit Monitoring

Credit monitoring data allows you to know what customers/members are doing outside of your financial institution. “What if you could monitor what your customers and members are doing outside of your organization and take action on it?” asks Andrew Lampkins, SVP of Marketing Client Relationships at Marquis. Credit monitoring helps drive timely and relevant marketing messages at the right time.

Data Management and Reporting

With the vast amount of intelligence collected from these sources, interpreting the data often can be daunting, time consuming, and utilize multiple resources. Using a partner to collect and interpret the data may help to alleviate the strain. Companies like Marquis put their experience and expertise at their client’s disposal. Marquis’ insights help develop strategic marketing plans based on their data, the institutions unique customer/member base and the financial institution’s product offerings.

Without measurable results, ROI can be attributable to other sources. Marquis also offers reporting tools to help their clients discover what campaigns are successful and where programs can improve. The Marquis NEXT Reporting Tool delivers a complete view of campaigns, from product performance to opening rates. Lampkins adds, “A tool like Marquis NEXT is ideal to see the growth of new products due to your campaigns.”

Go Forth and Personalize!

Data is valuable. The insight it provides is the basis of any personalization which guides us on who to target, what consumers want, when they want it and where they are most likely to view the message.

For these reasons, these six data sources are essential to your marketing strategy. They are the keys to winning campaigns with compelling offers and a personalized experience. You’ll gain valuable insights, allowing you to learn more about your audience and their needs. Multiple data sources will also uncover new marketable segments that enable continuous growth. Most importantly, personalized content with the right message delivered at the right time creates loyal and lifelong customers/members who will turn to you first for their financial needs.

[1] Invesp https://www.invespcro.com/blog/data-driven-marketing/

[2] Accenture https://www.accenture.com/_acnmedia/pdf-77/accenture-pulse-survey.pdf