Customer Segmentation is being increasingly recognized by leading marketers to be a vital component of the financial marketing landscape. Every Financial Services brand has its own unique marketing objectives and needs. With respect to these needs, marketers are focused on capturing customers from specific sectors of the industry. These sectors include banking, insurance, securities, etc.
Financial marketers have certain target audiences within these sectors to whom they want to market to. To cater to these audiences, they need to duly sort them into groups or segments based on their shared attributes.
Customer Segmentation: Decoding Customer Data
For creating the right customer segments, financial marketers depend completely on consumer data. This data has different facets to it which marketers need to tap. All these facets in one way or the other are related to customer behavior. As a result, behavioral data has become the primary determinant when it comes to creating precise customer segments.
In the past, most user segments were built around basic demographic data. This included variables such as age, gender, income, and educational details of users. Although this method worked to a small extent earlier, it’s no longer relevant in today’s digital age. Customers flock to a financial provider’s website like bees. They are constantly in search of products and services that can satisfy their financial needs.
Each customer has a certain level of buying intent which drives his/her behavior on the website. If they don’t find what they are looking for, they immediately bounce. Banks, Financial Services, and Insurance companies should try to segment customers based on their digital behavior and then tailor their products and services accordingly.
Types of Customer Segmentation
There are two types of customer segmentation – normal segmentation and predictive or intelligent segmentation.
Normal Segmentation
This type of customer segmentation is widely used by every marketer in the Financial Services industry. Segments created here are based on certain customer attributes. These include:
- Visitors belonging to a particular demography
- Prospects from a particular geography
- Visitors from a certain industry
- Customers who have purchased certain products or services
- Customers whose email click and response rates are pretty high
- Visitors who spend more than 2 minutes on the site
- Visitors who downloaded an ebook from the website
The above segments are a set of rules that segregate users into specific buckets. Financial marketers target each bucket with personalized offers through various online channels such as programmatic ads, browser push notifications, e-mail, etc.
Predictive or Intelligent Segmentation
This type of segmentation incorporates the use of Artificial Intelligence (AI). Using advanced AI-based algorithms, financial marketers can automatically segment customers based on a certain factor such as buying propensity. This is done using various industry variables and parameters that aid the algorithms in learning from a customer’s past history. Analyzing a customer’s historical data enables the algorithms to accurately sort users into the right buckets or segments.
For example, users with the highest propensity to buy a certain product are categorized into a segment called excellent leads. Users with medium buying propensity can be sorted into another segment called mediocre leads. Users with zero propensity to buy the product can be put in a segment called bad leads. After these algorithms are set in place, returning website users are sorted accurately into these segments. This happens in real-time as and when a returning user visits the website.
Once accurate segmentation is done, financial marketers can derive meaningful insights by assessing the performance of the created segments. As a result, they can effectively optimize their marketing spend and tailor personalized campaigns for users via different channels.
Final Thoughts
Creating user segments allows financial marketers to focus on the right customers for targeting their products and services. Brand engagement and digital conversions can be significantly increased by personalizing the experience across the users’ preferred channels and devices.
The future of financial marketing is going to be heavily dependent on AI. Investing in intelligent algorithms will enable marketers to create predictive segments that can help optimize spend and campaigns more effectively.
To know more about predictive segments and how they can benefit your business, reach out to us at marketing@lemnisk.co.
By Bijoy K.B | Senior Associate Marketing at Lemnisk
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