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   ARTICLE   |   From Scotsman Guide Residential Edition   |   April 2015

Attract More Customers With the Right Nectar

Customer segmentation and predictive analytics help you get your message into the right hands

Attract More Customers With the Right Nectar

Consider, for a moment, what degree of success you found in your last direct mail or mass e-mail marketing campaign. Did your marketing materials focus on a specific segment of borrowers in your database, or did you send a one-size-fits-all message? Most consumers have become jaded with impersonal marketing materials that have little or no personal relevance to them.

Like humming birds zooming past birdfeeders in search of the particular splash of color that indicates the sweet nectar they desire, today’s consumers are more selective in the messages they read. To find the right marketing nectar, many financial institutions are turning to predictive analytics and sophisticated segmentation to help them more effectively reach target audiences by putting the right offer in front of the right person at the right time.

When clients receive information from mortgage lenders or neighborhood brokers that speak directly to their current interests — refinancing a home, entering the purchase market or obtaining a line of credit to pay for college expenses — they are much more likely to read the message and respond. Predictive analytics can help you segment your markets to more effectively target your messages.

Predictive analytics

Predictive analytics is the process of using data science to predict which customers in a database are likely to perform certain actions. Companies can use predictive analytics to develop sophisticated customer segments based on a wide range of factors and identify untapped opportunities to gain a competitive advantage.

Many lenders and brokers already collect a myriad of structured data, such as loan application information, responses to feedback surveys and payment histories. These companies can increase the value of their analytics programs by adding the ability to examine unstructured data, as well, such as social media content, call center logs and feedback from loan officers.

Adding unstructured data analytics tools can allow brokers to constantly monitor their brand and reputation as well as the reach and impact of their competitors through online content and customer reviews. This information can then be integrated with other data to help determine the relevance of various topics important to customers, and focus marketing content on products that will generate the most profitable opportunities available.

Sophisticated analytics tools allow originators to process structured data (i.e., professional reviews) and unstructured data (i.e., conversations) to spot and analyze trends. For example, text analytics give companies the ability to track consumer sentiment about their products and services through common words or phrases — and even popular slang terms or idioms — found online.

Predictive analytics then use all of these factors to help companies integrate marketing communications, identify proper messaging, and choose the best design and medium choices to get favorable responses from their target markets.

Segmentation models

Predictive analytics also provide the foundation for building stronger customer segmentation models. As a starting point, mortgage originators can use data mining to separate customers into customized groups based on demographics, attitudes, buying behavior and more. Many companies already do this to some extent. For example, you may segment customers based on products or investor types. Few companies, however, take into consideration the actual person making the transaction when they segment.

Predictive analytics is the process of using data science to predict which
customers in a database are likely to perform certain actions.

The simple approach is rarely enough to ensure that you align the right message with the right people at the right time. To increase your marketing effectiveness and boost the potential return on investment of your marketing efforts, you need to use predictive analytics programs to target messages more precisely.

Predictive analytics enhance customer segmentation by identifying precise and nuanced target groups for marketing campaigns. These tools use your data to generate specific segments with minimal effort on your part. Sophisticated software builds predictive models that find patterns in the data that are too complex or too subtle to discern manually.

Value or vulnerability

Mortgage brokers can use two methods for segmenting customers and potential borrowers. First, you can look at customers who bring the most value to your organization. To determine the long-term value of borrowers in your database, identify borrowers such as rental investors, clients who provide frequent referrals, customers with multiple business lines, and consumers who are more likely to refinance or can benefit from home equity lines of credit.

After identifying the correct factors and assigning value points to each, brokers can then rank customers based on their value to the organization. Some costs and revenue streams can be hard to identify immediately, however, so you may need to review financials and revise profitability models regularly.

The other segmentation approach is to identify those customers at greatest risk or vulnerability, such as clients who may be on the verge of leaving for a competitor. Remember that acquiring a new client will always cost more than maintaining an existing one, especially for smaller companies. As competition continues to increase in the mortgage industry, highly qualified borrowers will carry the most significant value because they are more likely to purchase additional loan products in the future or refer their peers.

By focusing on vulnerability when segmenting customers, you can send out targeted offers to those customers on the brink of ending their relationships with you and work on maintaining or regaining their business.  Furthermore, vulnerability segmentation provides valuable insight into issues causing customer churn, which can help you make adjustments to your operation as needed.

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The better your company knows its customers and understands their needs, the more effective your marketing efforts to those customers will become, which can generate significant rewards for your business. Combining predictive analytics of structured and unstructured data with advanced segmentation models can give you the insights you need to prosper in a competitive mortgage market. 


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