Your members and prospective members are very unique, each with diverse emotional triggers. Data analysis and creative assets are oriented towards finding the unique messaging that optimizes their response. The more the communication aligns with the needs and behaviors of your current and perspective member the higher the likelihood of their acceptance of an offer because it is relevant to them. The discovery is designed to identify the best opportunities, consistent with your stated strategic goals, for effective personalization of offers.
Where do you start?
First ask yourself, what historical data is currently available and accessible for analysis? To determine where you are going you’ll need to know where you are now and how you got there.
You must understand the role your credit union plays in the financial well-being of your members and prospective members and how easy it is to do business with you. Additional discovery includes analysis of current and historical marketing campaigns. We learn from our successes and failures and make adjustments accordingly to continuously improve the process. Important as well, append your data with third-party databases to create a fuller view of the member and prospective member within your segs.
Data that is commonly appended include:
- Financial lifecycle triggers
- Prizm personality scores
- Employment information
- New mover data
- Public Facebook or Twitter data
The 4 Steps to Effective Data Modeling
Step 1: Define Segmentation and Clustering Strategies
First, develop segmentation strategies to link personas to a product for the advantage of predicting the right messages and channel to influence the member or prospective member.
Step 2: Analyze and Cluster
It’s important to analyze which historical campaigns produced the desired behavior. Then analyze the attributes of these members to form clusters. The segmentation and clustering strategies will then be applied to predictive modeling for future campaigns.
Step 3: Score
Once the performing clusters are identified, create performance scores to each member. In addition, create a second lifestyle score based on other demographic and lifestyle attributes identified.
Step 4: Identify Highly Likely Targets
The outcome of segmentation and clustering data strategies produce “likelihood to accept” scores. In addition, scores take into account the ideal message and channel to produce the highest conversion likelihood.
Integrated Marketing Credit Union Case Study
The following case study is from a credit union in a suburban, major metro area, under 400 million in assets, fewer than 30,000 active members, 8 branches and membership from residents in 14 counties and an employer base.
Aggressive asset and membership growth goals as well as a brand upgrade.
- Little to no growth
- Acquisition and retention struggles
- Competitive product and service pressure in a saturated banking market
- Stale brand with inconsistent exposure.
Data Analysis Solution
Dialog Direct benchmarked the credit union’s performance with their peers and uncovered 12 areas of immediate need including weak, missing or poorly promoted financial product. We also uncovered service offerings where demand existed and built retention and acquisition strategies around each.
To determine the recipient of a relevant financial product or service, member segments were created using demographic, financial product/service, etc. data. Scores were assigned to each member or segment of prospective members. These scores determine the product, creative asset, method of delivery and cadence of an offer. Strategies are categorized as retention or acquisition and tactics are created to execute on the marketing plan.
Integrated Marketing Strategy Part 1
New Mover Acquisition: Using our in-house new mover data base and data such as age and income, we identified an average of 10,000 new movers monthly into the Credit Unions geographical footprint. We presented each with a personalized offer of a loan product, deposit product and/or benefits of membership, multiple times, with follow up, call to action and track the results.
Next Blog will continue our review with Contact Approach and Content Development of this credit union’s progress toward a robust multi-channel member engagement program to achieve its strategic goal.