Baker Hill Prosper 2017 - Grow, Optimize, Protect: Using Business Intelligence and Marketing to Get a Bigger Slice of the Pie
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Presented by James McHale Regional community banks and credit unions understand they must outperform their national brand competitors when it comes to fully engaging their customers -- but sometimes overlook their direct and/or online-only banking counterparts. This session showed how advanced analytics tools provide unique actionable insights which, when coupled with a sustained marketing strategy, help them compete more effectively to maximize customer acquisition, engagement and retention -- and most importantly profit.
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Baker Hill Prosper 2017 - Grow, Optimize, Protect: Using Business Intelligence and Marketing to Get a Bigger Slice of the Pie
- 1. GROW, OPTIMIZE, PROTECT: USING BUSINESS INTELLIGENCE AND MARKETING TO GET A BIGGER SLICE OF THE PIE James McHale, SVP/GM Analytics at Baker Hill Bryan Thomas, VP of Lending at On Tap CU
- 2. PROFIT RISK AND HOW TO IDENTIFY AND MITIGATE IT
- 3. Confidential & Privileged Document According to Forbes, 87% of companies think big data will make big changes to their industries before the end of the decade. Even more think that not having a big data strategy will cause their companies to fall behind. “Only the most informed and profitable will survive and prosper …”
- 4. Confidential & Privileged Document Profit risk management Profit Risk: concentration of income statement vs. distribution and diversification of income streams When profit risk is minimized, income volatility is mitigated and income and capital are sustained and grow, and the financial institution remains viable.
- 5. Confidential & Privileged Document Five most common uses of big data 1. Fraud Detection 2. Compliance and Regulatory Requirements 3. Customer Segmentation 4. Personalized Marketing 5. Risk Management
- 6. Confidential & Privileged Document Your call to action 1. Get your integrated database system up and running 2. Start to understand profitability dynamics in detail 3. Evaluate your income statement based upon achieving sustainability
- 7. Confidential & Privileged Document Your call to action 4. Define acceptable “Profit Risk” concentration levels 5. Set “Profit Risk” objectives and goals to spread profitability over a greater spread of customer/member relationships, products, markets, branches and officers
- 8. Confidential & Privileged Document Your call to action 6. Establish “Profit Risk” discipline 7. Develop “Profit Risk” strategies and tactical plans 8. Define institutional success based upon increased profitability, earnings and capital growth
- 9. Confidential & Privileged Document What your institution will gain 1. Improved identification of market opportunities 2. Higher levels of acquisition, retention and protection of market share 3. Higher, irrefutable return on investment with respect to revenue capture
- 10. Building our future – Strategy shift to On-Tap CU 10 • Perceived Exclusive Field of Membership • Aging Membership • Strategic Directional Change from Billion Dollar Brand
- 11. 11 Organizational ScoreCard Elements: • Millennial Wallet Share – Products & Services • Millennial Membership Growth (Overall) Building our future – Strategy shift to On-Tap CU
- 12. Marketing and growth initiative 12 • Opportunity: Target Millennials – Certificate of Deposit • Cross sell to Millennial group without CD (3,873 Relationships) – When a Millennial has a CD in relationship: Average Profit per Relationship increases 1,290% Cross-Sell Service Ratio increases 158% Cross-Sell Account Ratio increases 278%
- 13. Confidential & Privileged Document Marketing and growth initiative • Deepen Indirect Relationships – New Interest Rewards Checking – New Online Banking Solution (Q2) 13
Editor's Notes
- Customer Segmentation Banks have been under pressure to change from product-centric to customer-centric businesses. One way to achieve that transformation is to better understand their customers through segmentation. Big data enables them to group customers into distinct segments, which are defined by data sets that may include customer demographics, daily transactions, interactions with online and telephone customer service systems, and external data, such as the value of their homes. Promotions and marketing campaigns are then targeted to customers according to their segments. Personalized Marketing One step beyond segment-based marketing is personalized marketing, which targets customers based on understanding of their individual buying habits. While it’s supported by big data analysis of merchant records, financial services firms can also incorporate unstructured data from their customers' social media profiles in order to create a fuller picture of the customers' needs through customer sentiment analysis. Once those needs are understood, big data analysis can create a credit risk assessment in order to decide whether or not to go ahead with a transaction.
- Customer Segmentation Banks have been under pressure to change from product-centric to customer-centric businesses. One way to achieve that transformation is to better understand their customers through segmentation. Big data enables them to group customers into distinct segments, which are defined by data sets that may include customer demographics, daily transactions, interactions with online and telephone customer service systems, and external data, such as the value of their homes. Promotions and marketing campaigns are then targeted to customers according to their segments. Personalized Marketing One step beyond segment-based marketing is personalized marketing, which targets customers based on understanding of their individual buying habits. While it’s supported by big data analysis of merchant records, financial services firms can also incorporate unstructured data from their customers' social media profiles in order to create a fuller picture of the customers' needs through customer sentiment analysis. Once those needs are understood, big data analysis can create a credit risk assessment in order to decide whether or not to go ahead with a transaction.
- Customer Segmentation Banks have been under pressure to change from product-centric to customer-centric businesses. One way to achieve that transformation is to better understand their customers through segmentation. Big data enables them to group customers into distinct segments, which are defined by data sets that may include customer demographics, daily transactions, interactions with online and telephone customer service systems, and external data, such as the value of their homes. Promotions and marketing campaigns are then targeted to customers according to their segments. Personalized Marketing One step beyond segment-based marketing is personalized marketing, which targets customers based on understanding of their individual buying habits. While it’s supported by big data analysis of merchant records, financial services firms can also incorporate unstructured data from their customers' social media profiles in order to create a fuller picture of the customers' needs through customer sentiment analysis. Once those needs are understood, big data analysis can create a credit risk assessment in order to decide whether or not to go ahead with a transaction.
- Customer Segmentation Banks have been under pressure to change from product-centric to customer-centric businesses. One way to achieve that transformation is to better understand their customers through segmentation. Big data enables them to group customers into distinct segments, which are defined by data sets that may include customer demographics, daily transactions, interactions with online and telephone customer service systems, and external data, such as the value of their homes. Promotions and marketing campaigns are then targeted to customers according to their segments. Personalized Marketing One step beyond segment-based marketing is personalized marketing, which targets customers based on understanding of their individual buying habits. While it’s supported by big data analysis of merchant records, financial services firms can also incorporate unstructured data from their customers' social media profiles in order to create a fuller picture of the customers' needs through customer sentiment analysis. Once those needs are understood, big data analysis can create a credit risk assessment in order to decide whether or not to go ahead with a transaction.
- Customer Segmentation Banks have been under pressure to change from product-centric to customer-centric businesses. One way to achieve that transformation is to better understand their customers through segmentation. Big data enables them to group customers into distinct segments, which are defined by data sets that may include customer demographics, daily transactions, interactions with online and telephone customer service systems, and external data, such as the value of their homes. Promotions and marketing campaigns are then targeted to customers according to their segments. Personalized Marketing One step beyond segment-based marketing is personalized marketing, which targets customers based on understanding of their individual buying habits. While it’s supported by big data analysis of merchant records, financial services firms can also incorporate unstructured data from their customers' social media profiles in order to create a fuller picture of the customers' needs through customer sentiment analysis. Once those needs are understood, big data analysis can create a credit risk assessment in order to decide whether or not to go ahead with a transaction.
- Customer Segmentation Banks have been under pressure to change from product-centric to customer-centric businesses. One way to achieve that transformation is to better understand their customers through segmentation. Big data enables them to group customers into distinct segments, which are defined by data sets that may include customer demographics, daily transactions, interactions with online and telephone customer service systems, and external data, such as the value of their homes. Promotions and marketing campaigns are then targeted to customers according to their segments. Personalized Marketing One step beyond segment-based marketing is personalized marketing, which targets customers based on understanding of their individual buying habits. While it’s supported by big data analysis of merchant records, financial services firms can also incorporate unstructured data from their customers' social media profiles in order to create a fuller picture of the customers' needs through customer sentiment analysis. Once those needs are understood, big data analysis can create a credit risk assessment in order to decide whether or not to go ahead with a transaction.