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

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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!

Getting Your Message Across Without Shouting in a Storm

Marketing, Uncategorized, ,

In a little more than a decade since the global financial crisis, things are looking up, especially for U.S. financial institutions. With the calmer waters comes fierce competition. On top of brick-and-mortars, Fintech and Neobanks are hitting their stride while Big Data companies like Amazon and Google are jumping on the lending wagon. Consumers are bombarded with messaging from all sides. How can your bank or credit union’s voice be heard through all this static?

Attracting and Retaining Households

Although it’s true that spending is up, acquiring new households is down and retaining current ones is an issue. Half of all accounts are single-service households. This presents potential retention issues, especially since new single-service households are 50% more likely to leave within a year. The likelihood of leaving halved if they add just one more product. With four products, the potential for leaving decreases to a mere 5%. Concerted efforts to add at least one more product to a household is essential for retention. But it has to be personalized and sent at the right time to the right person. Flooding households with untargeted messaging just doesn’t work, whereas a vehicle loan offer aimed at households with teenagers might do the trick.

Meeting Consumer Expectations

Today’s consumer voluntarily supplies enough information for brands to know and predict their preferences. Nearly three-quarters of global consumers expect brands to treat them as individuals, not anonymous parts of a larger whole. In a world of anonymous avatars and usernames, they expect brands to use the data to approach them as individuals with relevant, personalized experiences. That includes financial institutions.

The Backbone of Effective Marketing Efforts

It’s no secret. If properly utilized, Big Data enables the personalization consumers are looking for. When properly interpreted, you’ll know who your customers/members are, what they need, and when to engage them. Take it one step further to increase growth and profitability by leveraging the data for Growth Analytics.

The Analytics Growth Engine

Growth Analytics is used to identify growth attributes and metrics. An Analytics Growth Engine gives direction and purpose to your Growth Analytics by combining artificial and human intelligence to deliver insights to fuel consistent and predictable revenue growth.

Mark Gibson, Senior Consulting Associate at Capital Performance Group, suggests that growth engines for financial institutions need to have specialized stages.

Stage 1 – Prospecting

Stage 2 – Acquisition

Stage 3 – Onboarding

Stage 4 – Activation & Utilization

Stage 5 – Relationship Expansion

By using data and analytics as tools at each stage, you’ll have precise and scalable data that measurably improves performance and efficiency.

The Super Tools

A strong marketing plan is based on how consumers learn about and buy financial services. It’s about the journey from the prospect to full engagement. Gibson’s Analytics Growth Engine model requires data be applied as a tool to each stage of the process. These tools – Segmentation, Targeting, Engagement Strategies, Life Stage Marketing and Customer Value and Attrition Propensity – lead to a deeper understanding of customer/member needs. In turn, offers are more pertinent to targeted consumers and likely to elicit a response.

Putting It All Together

You have your Analytics Growth Engine. You have your super tools. When the tools are applied, insights will be more meaningful, leading to increased sales, deeper relationships and stronger retention.

Segmentation is the foundation of any targeted marketing strategy. Before prospecting, determine who your best customers/members are, what products and services they use and where they are on their financial journey.

Use Targeting at Stage 1 Prospecting to find prospects who resemble your best account holders. Combine predictive and look-alike modeling with third-party data to target individuals with potential for best value and profitability based on your Segmentation analysis.

Use the Engagement tool to define the onboarding process. Understand what services and products a fully-onboarded customer/member uses. Realize the vision by applying the Engagement tool to Stage 2 and 3 of your Analytics Growth Engine to develop a personalized approach for each customer/member. Then, use the Engagement tool for reboarding to increase activation and utilization.

Life Stage Marketing is perhaps the most important tool for customer/member personalization. Apply it to Stage 4 Relationship Expansion to understand where each customer/member is on their financial journey. Now, you can give relevant advice and predict what products make sense for your customer right now. For instance, a HELOC is meaningless to a 20-year-old college student, but a student checking account might do the trick. This tool helps deliver the right message at the right time.

You’ve reached Stage 5 – Relationship Expansion and your prospect is fully-engaged. Use the Customer Value and Attrition Propensity tool to determine their value to your organization. This allows you to fix a value on retention efforts in both time and money by targeting accounts that historically realize the most value.

You Are Not Alone

Developing a robust Growth Analytics program driven by a strong Analytics Growth Engine is essential in today’s banking landscape. However, most financial services marketers are short on time, training and manpower. Even though financial institutions have remarkably more data than other lines of business, many are unprepared to make the most of this opportunity. But consumers expect us to know who they are and what they want before they even know themselves. If we don’t deliver, we risk losing both prospects and current customers/members. That’s where a company like Marquis can help by leveraging the strength of technology, analysts and creative services needed to extend your reach.

Marquis works closely with your team to develop a strong marketing plan dedicated to attracting new customers/members, expanding product adoption and increasing product use. The Marquis team assembles data sources and provides the tools and expertise to analyze and understand customer/member relationships and opportunities. Using Big Data and Growth Analytics, companies like Marquis become your partner, helping you elevate performance and increase effectiveness. They become your Analytics Growth Engine.

Time for Action

To successfully compete in the current environment, you must engage with customers/members on a deeply personal level and develop a marketing strategy that meets consumers’ expectations of personalization. An Analytics Growth Engine puts your vast amount of data into context to discover new opportunities and promote revenue growth. It’s how you attract prospects and engage with those customers/members most likely to add new products. It makes your message heard in the ultra-competitive world of retail and business finance.

Image courtesy of Mark Gibson, Senior Consulting Associate, Capital Performance Group.