Insiders Secrets to Onboarding Success in Banking

[vc_row][vc_column][vc_column_text]July 3, 2017 

What happens in the days and weeks after a consumer opens their new account or gets a loan can have a massive impact on long term profitability. Banking providers that cross-sell more products and services and grow their bottom line are those that engage with consumers from the start of the relationship. Here’s what the experts say you need to build an effective onboarding strategy.

 

What are the biggest onboarding challenges facing banks and credit unions?

Tim Keith, Partner and Chief Strategist at Infusion Marketing Group: Consumers don’t have the same financial needs, yet most financial institutions fail to use data to understand the needs of new consumers. This results in one-size-fits-all welcome letters. The communications aren’t relevant to each consumer.

Read More…Click here to read the full article.

 

Tim Keith is a former banker who in 2007 co-founded Infusion, a provider of data-driven direct marketing campaigns that generate strategic growth for community and regional financial institutions. He works directly with financial institutions to implement data analysis services, support marketing efforts, write and present comprehensive customer analysis, evaluate campaign results, and design strategic growth programs.

 

Original Source: https://thefinancialbrand.com/73187/onboarding-marketing-strategy-banking/[/vc_column_text][/vc_column][/vc_row]

The Discipline of Relevant Marketing

December 7, 2017 by Tim Keith

By understanding the importance of frequency, cadence and targeting, financial institutions can successfully managing both customer relationships and product portfolios at the same time.

 

Retail banking is inherently relational. Bank customers have a variety of financial needs which change and evolve over time, in terms of both the scope of needs a customer may have and the relative importance that customer puts on each individual need. Of course, banks offer different product lines designed to meet these various needs.

This dynamic results in…Click here to read the full article.

 

Tim Keith is a former banker who in 2007 co-founded Infusion, a provider of data-driven direct marketing campaigns that generate strategic growth for community and regional financial institutions. He works directly with financial institutions to implement data analysis services, support marketing efforts, write and present comprehensive customer analysis, evaluate campaign results, and design strategic growth programs.

 

Original Source: https://thefinancialbrand.com/69106/discipline-of-targeted-financial-marketing/

Digitally Target New Movers

September 1, 2017 by Tim Keith

Change the game by going digital with your bank’s new mover marketing strategy.

 

What is a “new mover” exactly? Simply put, new movers can be defined as someone currently in the moving, home-buying, or selling process. New movers are often divided into subgroups and categorized as one of the following:

    • Pre-mover: defined as someone who recently listed their home on the market.
    • Escrow: defined as someone who has sold their house but has not moved yet, or is under contract.
    • Post-mover: defined as someone who just moved into or purchased a new home, or sold a residence.

New mover data has always provided a “sizzle factor” to bank marketers, but is often viewed as too good to be true. New mover programs provide bank marketers with the opportunity to identify consumers during a physical move—a major life event that often prompts consumers to select a new financial provider—and methodically target relevant financial messages to them.

 

Unfortunately, the concept of a new mover marketing program has not lived up to the hype.

The biggest issues with traditional new mover marketing programs have been practical considerations. By the time a new mover is identified, a data file is created and prepped, marketing is produced, and mail is delivered, it is often too late—the consumer has already chosen a financial provider. Additionally, the data itself can be expensive to collect, and the week-to-week quantities are relatively low in most markets. These pain points associated with traditional new mover programs are why many bank marketers have abandoned efforts to make new mover marketing programs work.

But digital marketing is changing how new mover programs are implemented by removing the logistical and financial barriers of a traditional, direct mail program.
By shifting new mover programs to a digital channel, bank marketers can now make the identification of new movers and the deployment of targeted online messages part of one automated, continuous process.

 

What’s the biggest draw to a digital new mover program?

Potential targets are identified throughout the day, while targeted digital ads are automatically and immediately deployed on the websites that the target audience is browsing.

Since the tactics are carried out and streamlined to online channels, costs for a digital new mover program are lower due to the absence of postage and physical material expenses. Bank marketers must invest time on the front end of the program to develop the messaging strategy and associated creative treatments. But then, once the program is launched, the only ongoing time commitment is evaluating results.

 

Another benefit of the digital approach: the ability to view real data on how consumers are interacting with the marketing.

In a traditional new mover campaign, a physical piece of marketing collateral is sent in the mail. But bank marketers have no way of knowing how many consumers read it right away, how many set it aside for later, and how many throw it away.

Now, by utilizing digital channels for ads, bank marketers have the ability to continuously measure the number of ad impressions and resulting ad clicks.

However, while this level of tracking can provide exciting and validating insights, it is not sufficient to determine a program’s true return on investment. Best-in-class programs will integrate impression and click tracking with actual accounts and balances opened by the program’s target audience. Fully closing this loop allows the marketer to home in on the messages about their bank that resonate most with consumers who are new to their markets. This allows the marketing to become more relevant over time and turn the “sizzle factor” into real results.

As banks move further into omni-channel marketing programs, digital new mover programs are an obvious category that should grow in both popularity and relevance to the growth strategies of individual institutions. Banks have made efforts to effectively market to new movers in the past, and now with digital channels, they have a cost-effective, timely alternative for reaching this niche market.

 

Tim Keith is a former banker who in 2007 co-founded Infusion, a provider of data-driven direct marketing campaigns that generate strategic growth for community and regional financial institutions. He works directly with financial institutions to implement data analysis services, support marketing efforts, write and present comprehensive customer analysis, evaluate campaign results, and design strategic growth programs.

 

Original Source: http://ababankmarketing.com/insights/digitally-target-new-movers/

How credit unions are avoiding data analytics mistakes

August 9, 2017 by W.B. King
Aggregating data is one thing, but effectively analyzing it or predicting member behavior is quite another. And, many times well-intended executives make mistakes in this all-important pursuit.

So what are the biggest mistakes CUs make when it comes to data analytics? Credit Union
Journal queried a panel of experts to find out.

“Our primary methodology was too focused on transactional data from within the core at first.
The challenge is that, like many credit unions, some transactional data, such as credit card and
mortgage servicing, is housed elsewhere,” said Redwood Credit Union’s CIO Tony Hildesheim.
“Without all of your loan data, your reporting engine is not all that effective.”

Symitar Solutions Team Business Consultant Patty Moore added that a common mistake she
sees CU executives making when collecting data is “failing” to view performance measures in
context.

“In talking with credit unions who are interested in or pursuing predictive analytics, they have
more certainty about what they want to predict,” said Moore, “such as which loans have a high
probability of charging off [or] which members are at risk for closing, but they do not always
have an associated action plan to go along with the predictions.”

Asking the right questions
For the $1 billion Santa Rosa, Calif.-based Redwood CU, which supports 285,000 members at
19 branches, data gathering must answer at least one of the following five important questions,
explained Hildesheim. Does the analytics report:

1. Allow you to take an action?
2. Allow you to make a decision?
3. Does the data drive profitability?
4. Does the report drive staff engagement?
5. Most importantly, does the report drive member engagement?

“Our primary methodology is to focus on bringing the data together and establishing
normalization and definitions,” said Hildesheim. “The actual analytics is not all that difficult, once both the meaning and question are established.”

In many cases, credit unions executives make data-related mistakes by looking at data in
isolation, said Tim Keith, co-founder and chief strategy officer of Infusion, a Little Rock, Ark.based firm specializing in in data analysis for marketing campaigns.

“Credit unions need to seek partners with a proven track record who are willing to devote
qualitative time to the partnership,” said Keith. “The unfortunate reality is that there are many excellent vendors who focus solely on larger institutions and simply do not have a servicing model designed to work with the vast majority of credit unions.”

Keith further explained that most credit unions operate as two to three member bases within a
member base. These include single-service savings members, indirect loan members (with only
a nominal savings balance) and relationship members. Without data integrated across products,
he said, there is “no way” of distinguishing these groups, which is “fundamental to
understanding” the member base.

“Single service members typically make up 15 to 50 percent of an institution’s member base.
Without a household-level view that brings together accounts within a relationship, the institution has no way of distinguishing the member who has five different account types with the institution versus the member that only has savings,” he said. “Identifying single service members allows the institution to begin the process to assess how much potential those members have to bring additional business.”

Among Infusion’s clients is the $550 million Bartlett, Tenn.-based First South Financial Credit
Union. A recent data-gathering pain point centered on analyzing credit card data and signing
members up for cards during the onboarding process, explained Senior Vice President of
Marketing Delynn Byars.

“Marketing to indirect loan members has been a huge success,” said Byars, whose CU supports
approximately 56,000 members at 16 branches. “Many credit unions face a challenge with these
members because they don’t have the same level of awareness or attachment as those who
opened their accounts via other avenues.”

Byars explained that the CU worked with Infusion to develop an onboarding strategy, which
included an onboarding process with offers geared toward indirect members. At the beginning of
2016, she said, the CU’s product and service penetration was 2.89 for indirect members. By the
end of June 2017 that figure had increased to 3.35.

“Now that may not sound like a lot, but these members have basically no loyalty or affinity for
us,” said Byars. “They’re more like prospects.”

Data warehouse woes
One way to avoid data missteps is by understanding what data should be stored where,
explained Hildesheim. It doesn’t make sense, he said, to “copy data from one database to the
warehouse” if the analytics engine can access that data directly without performance of that
system.

“Transactional and financial data are two types of data that we determined needed to be stored
in the warehouse versus, for instance, web and online banking use that is directly accessible,”
said Hildesheim. “We are fortunate that our core provider [Symitar] also has a data solution
called Advanced Reporting for Credit Unions.”

Moore explained that Symitar’s ARCU has 315 pre-built standard reports. ARCU clients range
from $52 million in assets to $8 billion, with the average asset size for an ARCU client being
$1.1 billion.

“The larger-than $1 billion in assets credit unions are typically the ones with the in-house
resources to pursue predictive analytics on their own,” he said. “Trend reports include year
over-year, month-over-month, day-over-day comparisons so that anomalies can be detected,
patterns identified and data viewed in historical context along with goals and peer comparisons.”

Recently, Hildesheim employed ARCU to answer data-related questions, such as “Why do
members leave” and “How to detect signs of potential mobile fraud.” For the latter question, five critical elements were identified, including deposit velocity across the entire member base and geolocation data.

“Leadership needs to focus on making sure the right questions are being asked for the results
that they trying to achieve,” said Hildesheim. “Otherwise, you risk just ending up with a report
that doesn’t add value.”

Original Source: https://www.cujournal.com/news/how-credit-unions-are-avoiding-data-analytics-mistakes?brief=00000158-73f9-d502-a5fd-7bfbd3d10000

3 Bank Marketing Myths Debunked

New article by Tim Keith, strategy leader at Infusion:

Over the past two and a half decades, bank marketers have fallen victim to the same myths over and over again. It is obvious when tracking and reporting campaign results that these beliefs cause more harm than good in making smart marketing decisions. Before working on a direct marketing campaign, it is good to consider these three myths…

Read the full article:
3 Bank Marketing Myths DebunkedThe Financial Brand, June 9, 2017.

Use Data Analysis to Boost Growth

New article by Tim Keith, strategy leader at Infusion:

Core data analysis isn’t just for the banking giants. Community and regional banks have more to gain from data driven marketing.

Community and regional bank marketing teams often miss out when it comes to utilizing core data—and it could be costing them big money. Many banks just assume that their marketing plans are successful, or that they need a multi-million-dollar marketing budget to take their marketing programs to the next level. As a former banker, I understand the fear of taking a risk when trying something new. But, with careful analysis of core data, small to mid-sized banks can more accurately direct their marketing efforts to drive growth without breaking their budget. And I would strongly urge bank marketing teams to become more familiar with this concept.

Here are the key steps banks need to know to build a successful data driven-marketing program that directly connects to the bank’s larger strategic objectives:

Read the full article:
Use Data Analysis to Boost GrowthABA Banking Marketing, April 20, 2017.

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