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MATCHMAKING: Data segmentation as a tactical tool
data segmentation for bank marketing

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June 5, 2024

The disruption of the financial services industry is here. The growing presence of innovative fintech and big tech companies, increasing consumer demand for efficiency in managing finances, and the tightening of regulatory attitudes are impacting how marketers operate today.
Financial institutions following best practices can effectively implement data segmentation and create more personalized and targeted marketing campaigns. That means following the best practices of successful data segmentation, including defining segmentation criteria, using reliable and accurate data, avoiding over-segmenting, developing target-
If you ask Jamal English, all roads lead to and from data. The founder and CEO of lead generation and marketing company EDM Lead Net- work helps develop marketing campaigns that attract quality leads and produce fast results for clients.

English recalls a company he worked with that used data segmentation to improve its campaigns by segmenting its book of business list based
on household income, life triggers, geography and purchasing history. After acquiring a look-alike consumer list, the company created targeted outbound campaigns that included personalized recommendations and promotions.

As a result, the company saw a significant increase in marketing campaign performance, customer engagement and sales. “Data seg- mentation improves targeting and personalization by allowing organizations to create more tailored marketing messages and offers that resonate with their audience,” English says. “By identifying specific custom- er segments based on demographic, behavioral or psychographic data, you can create marketing campaigns that address your audience’s unique needs and interests.”

To effectively implement data segmentation, you should start by clearly defining your goals and selecting the most relevant data points to use for segmentation.
— Jamal English, CEO, EDM Lead Network

There are several data types that can be used for segmentation, including demographic, geographic, psycho- graphic and behavioral. This data can be collected through various sources, including customer surveys, website analytics and customer relationship management (CRM) systems. Data analysis tools such as Excel or more advanced analytics software can be used to sort, filter and segment the data.

“To identify and target specific customer segments, start by analyzing your data to identify common characteristics, preferences and behaviors among your customers,” English says. “You can then use this information to create targeted marketing campaigns that speak directly to each segment.”

 

The art of data segmentation

Data segmentation can be a powerful tool. By using data to better understand your clients, you can deliver more personalized and targeted content. Nothing engages with customers more than finding what they want and need.
In the commercial printing industry, companies like NextPage use client data to segment their customers based on product and solutions purchased, search history and website behavior engagements. NextPage Strategic Marketing Manager Jennifer Turgeon says data segmentation can help improve targeting and personalization in a number of ways. This includes identifying specific customer groups based on certain criteria, understanding customer needs and preferences, delivering targeted content, and helping to optimize campaigns.
“Depending on your goals, various types of data can be used for segmentation,” Turgeon says. “For example, demographic data (age, gender, income, education and geographic location), behavioral data (purchase history, website activity, email engagement and social media activity), psychographic data (values, attitudes, beliefs and lifestyle preferences) and firmographic (company size, industry revenue and location).”
Segmentation data can be collected through various methods like customer databases, web analytics, online surveys, sales reports, social media analytics. From here, the data can be further analyzed using statistical tools and techniques. “Keep in mind that leveraging data should be done in accordance with data privacy laws and regulations,” Turgeon says. “Be transparent about the data collected and how it will be used. You always want to protect your customer data.”
Financial institutions following best practices can effectively implement data segmentation and create more personalized and targeted marketing campaigns. That means following best practices of successful data segmentation, including defining segmentation criteria, using reliable and accurate data, avoiding over-segmenting, developing targeted content and messaging, testing and optimizing, and aligning with ethical considerations.

With every step, be aware of potential challenges and limitations. Some of the challenges NextPage has seen include things like data quality, where you must make sure you are using clean data. Others include too much segmentation (start small), bias (be careful when using factors like race, gender or age) and cost (the practice can be expensive for smaller companies).

In the end, the goal is to identify and group similar data points to better understand your customers. Giving your financial institution that type of advantage will help create more effective marketing strategies and improve overall business performance.

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