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Maximizing Profits in Financial Services with Analytics and AI
4 METHODS TO INCREASE PROFITS NOW In the fast-paced world of financial services, staying ahead of the curve is paramount. You don't have the luxury of time for protracted strategic adjustments. You can ignite your business' performance now by harnessing the transformative power of analytics and artificial intelligence (AI). These cutting-edge technologies hold the key to boosting revenue, slashing costs, and enhancing your clients' interactions.
Top Challenges in the Financial Services Industry
• Data Overload: Financial institutions are inundated with vast amounts of data. Effectively harnessing this data to derive meaningful insights and make informed decisions is a significant hurdle. • Customer Expectations: In the era of digital transformation, clients expect seamless, personalized experiences. Meeting these expectations while safeguarding data privacy is a complex balancing act.
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• Marketing Precision: Competition in financial services is fierce. Tailoring marketing efforts to specific customer segments, and individual customers, in real-time while also optimizing marketing spend is a constant challenge. • Data Security and Compliance: The financial industry grapples with stringent regulatory requirements and the constant threat of data breaches. Maintaining the highest levels of security while complying with evolving regulations is a top priority. Now, let's explore four methods that have enabled financial services businesses to drive substantial revenue gains, often within two quarters. These real-world examples not only demonstrate the effectiveness of analytics and AI, but also provide actionable insights that you can implement immediately to bolster profitability.
1. Business Intelligence Reducing Ad Spend 2. Experimentation Increasing Revenue Per Visitor 3. Conversion Rate Optimization Driving CLV 4. Machine Learning & AI Doubling Upsell & Cross-sell Revenue
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Maximizing Profits in Financial Services with Analytics and AI.
METHOD 1
BUSINESS INTELLIGENCE
REDUCING AD SPEND
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METHOD 1 : BUSINESS INTELLIGENCE
18% REDUCTION IN AD SPEND IN ONE QUARTER
CHALLENGE While spending millions of dollars each year across more than 20 third-party content hosts, this business realized it could make better data-driven budget decisions and optimize ROI by developing a centralized reporting platform of standardized metrics, data sets, and optimized business intelligence (BI) to compare performance and prioritize channel investments. SOLUTION 1. Collaborated with third parties to clean and standardize data sources for actual apples-to- apples comparison analysis. 2. Built data pipelines and alerts for smoother, cadenced data ingestion. 3. Created a singular data source in SQL that integrated all disparate data sources, aggregated on the most valuable KPIs. 4. Developed an intuitive, visual dashboard of standard metrics to report quick-read YoY analysis and competitive insights. RESULTS • Achieved revenue target with 18% less third-party ad spend in one quarter. • The business now leverages robust, real-time BI insights used daily by marketing teams to understand historical performance and make key data-driven budget decisions.
AD SPEND REDUCTION 18%
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METHOD 1 : BUSINESS INTELLIGENCE
LOWERING YOUR AD SPEND WITH BETTER INSIGHTS
Many companies start their analytics maturity and data science initiatives only to realize that their marketing teams could really benefit from better Business Intelligence (BI). To understand the difference between data science and BI, it’s important to note that BI measures what happened yesterday, while data science forecasts what will happen tomorrow. Without these foundational reports, analytics teams can struggle with complex ad hoc analyses or requests for reporting updates when they lack a strong foundation. To improve BI analysis, start by asking four key questions: • What are the most labor-intensive questions your team frequently asks to make key marketing decisions? • Who asks the questions and how do they apply the answers to accelerate business impact? • What are the key performance indicators (KPIs) you use to measure success? • Is the compiled data trustworthy and reliable? Once you’ve answered these questions, you’ll be able to determine which reports to automate first based on potential time savings. For example, creating an executive dashboard or a deep dive dashboard with various drill down options and filters can offer valuable insights for analysts. Additionally, a standardized dashboard can increase stakeholder confidence in the data. By investing in a Business Intelligence program, your team will be empowered to spend their time optimizing your business and lowering your ad spend, instead of compiling reports. Those daily, weekly, or near real-time optimizations add up to big wins over the course of a quarter.
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Maximizing Profits in Financial Services with Analytics and AI.
METHOD 2 EXPERIMENTATION INCREASING REVENUE PER VISITOR
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METHOD 2 : EXPERIMENTATION
19% INCREASE IN REVENUE PER VISITOR (RPV)
CHALLENGE This business’ marketing team needed to increase the online sales of a product line typically purchased through more high-touch channels. Achieving this goal required a test-and-learn roadmap to identify strategies for successfully changing customer behavior. SOLUTION 1. Analyzed Conversion Rate Optimization (CRO) across the current ecommerce landscape. 2. Conducted customer behavior and segmentation research. 3. Facilitated proprietary ASK workshop. 4. Developed experimentation roadmap and a test-and-learn decision tree.
REVENUE PER VISITOR +19 %
RESULTS • 19% lift in revenue per visitor. • $78,000 per day revenue increase during peak purchase days.
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METHOD 2 : EXPERIMENTATION
INCREASING YOUR REVENUE PER VISITOR WITH TESTING
Successful enterprise companies from Microsoft to Intuit tout the advantages of an experimentation program, yet many businesses still rely on gut instinct for decision-making. Wouldn’t you rather know, quantifiably, that data-driven optimizations benefit the bottom line? A strong test-and-learn culture creates insight momentum and propels improved decisions for the future. A successful experimentation program increases your revenue, mitigates risk, and reveals actionable business insights. However, the perfect mix of experimentation factors is up to you based on what your marketing team aims to accomplish. How experimentation increases revenue There’s a reason A/B testing is synonymous with CRO in ecommerce. Primarily, it’s one of the simplest and most powerful techniques to guide and measure incremental changes on everything from feature flag design to checkout UX performance. How experimentation uncovers actionable business insights If your win rate is lower than expected, or your experiments produce diminishing results, you should think bigger. Take a step back from the basic playbook and put yourself in the mind of your consumer. It might take three or four incremental experiments to accomplish your goal, as each subsequent experiment uncovers insights that lead to increased success rates. Once your major goals are identified, you’ll need to determine which experimentation methods to implement. Industry studies discuss the merits of Bayesian vs. frequentist testing , sequential testing , multi-armed bandits , multivariate experiments , and many other techniques to optimize performance, but don’t underestimate the value of multivariate testing. It takes more planning, analysis and time than simple A/B testing, but you get richer data in the end.
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Maximizing Profits in Financial Services with Analytics and AI.
METHOD 3 CONVERSION RATE OPTIMIZATION (CRO) DRIVING CUSTOMER LIFETIME VALUE
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METHOD 3 : CONVERSION RATE OPTIMIZATION (CRO)
MULTIMILLION-DOLLAR CLV INCREASE IN TWO QUARTERS
CHALLENGE Underperforming ecommerce features created churn in this business’ funnel and increased friction along the customer journey, which complicated the customer buying process. SOLUTION 1. Leveraged pre-UI development analysis in conjunction with heatmap tools and Adobe Analytics to determine funnel churn rate and optimize areas of greatest friction. 2. Conducted A/B testing and analysis to gain actionable insights that led to the creation of a quarterly roadmap focused on reducing customer journey friction. 3. Implemented new functionality that enabled ROI calculation tied to tangible results.
REVENUE MM+
RESULTS • Form completions increased by 23% following a single test. • Within two quarters of UX optimizations, the business reported a multimillion-dollar increase in CLV.
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METHOD 3 : CONVERSION RATE OPTIMIZATION (CRO)
INCREASING YOUR CUSTOMER LIFETIME VALUE WITH CRO
Conversion Rate Optimization (CRO) essentially results from a focused, applied methodology for improving your website’s sales performance. While various techniques are used to identify data-driven hypotheses, CRO is typically proven through A/B testing that quantifies the conversion rate improvement with scientific validity. It’s an iterative process of small wins that build momentum over time. Let’s say your website converts at 3% per 100,000 daily visitors—that’s 3,000 conversions per day. If we increase that rate to 5% (3% + 1.05 = 3.15%) you’re up to 3,150 conversions per day! If you’re like most enterprises, you can run dozens of these optimizations per week to make multiple incremental improvements. These wins gradually add up, as was the case in the above example—a multimillion-dollar increase in CLV in just two quarters. How do You Build Hypotheses that Lead to Increased Conversions? 1. Start by analyzing the customer journey. How many average clicks to purchase? Where do you lose the most customers in the funnel? 2. Consider best practices across devices and channels. Where are current practices outdated or not meeting customer expectations? 3. Review heatmap data of your most visted pages. Are there clicks on static images? Is distracting content confusing the customer? Is the only call-to-action (CTA) at the bottom of a long page that requires excessive scrolling? 4 . Prioritize optimization of entry-pages, traffic, and above-the-fold experiences. Where do you see potential for the greatest impact? Once you understand these key areas, you’ll implement more impactful solutions. It’s critical to know which pages and site areas attract the most visitors, and which underperform. If you identify bounce or cart abandonment issues, prioritize your testing initiatives around those areas. That’s when you’ll quickly see incremental improvements and increased revenue.
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Maximizing Profits in Financial Services with Analytics and AI.
METHOD 4 MACHINE LEARNING & AI DOUBLING UPSELL & CROSS-SELL REVENUE
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METHOD 4 : MACHINE LEARNING & AI
3X UPSELL + 2X CROSS-SELL INCREASES REVENUE IN 6 MONTHS
CHALLENGE This business recognized that its overly complex ecommerce marketplace created decision fatigue on the customer journey, requiring a new approach to connect customers with the products they need—when and where they choose to purchase. Specifically, the team wanted to use AI and machine learning to help customers find the right add-on products for increased upsell and cross-sell revenue. SOLUTION 1. Deployed purchase propensity machine learning models to identify audience segments most-likely to purchase specific products, including proprietary “build- instead-of-buy” machine learning models. 2. Conducted a market basket analysis—a data mining technique that analyzes customer behavior to identify links between products purchased in sequence to increase opportunity strength for cross-sell and upsell conversions. 3. Leveraged the right AI and machine learning models to more quickly connect buyers with the products they needed, in addition to the most associated add-on products.
UPSELL 325 %
CROSS-SELL 200 %
RESULTS • Upsell conversions tripled revenue in six months. • Cross-sell conversions doubled revenue in the same timeframe.
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METHOD 4 : MACHINE LEARNING & AI
LEVERAGING AI TO INCREASE UPSELLS AND CROSS-SELLS There’s much that can be taken away from this example, and it IS possible to implement this work in a single quarter. You can make quick wins with data science if you have a clean data set and enough data to develop machine learning models. In terms of the current economic climate, operationalizing an entire machine learning program is a proactive approach to recession-proofing your business for the long-term. The blog post “Analytics & Data Science During a Recession: Maximizing Revenue in Hard Times,” by Scott Sanders, Ph.D., a leading data scientist, makes the point that marketers are wasting unnecessary time and resources fine-tuning predictive forecasts when they should focus on leveraging machine learning models to optimize marketing investments.
Prioritize these machine learning models to improve purchase propensity: 1. Market Basket Analysis 2. Upsell Propensity 3. Cross-Sell Propensity 4. Feature Recommendation 5. Conversion Propensity
As demonstrated in this example, AI and machine learning will determine if it’s more profitable to recommend an upsell or cross-sell to a customer, and if your strategy should aim for basket size or basket frequency. You’ll also gain insights about which products to recommend during the checkout process and what to recommend during follow-up visits. The feature recommendation model is a dynamic option for its many valuable applications. If you sell a variety of products with varying features, this model can determine which features are most important to your customers. In addition, these insights lead to more personalized experiences by highlighting those features or showcasing similar products.
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Finish 2023 with Big, Quick Wins
It’s time to capitalize on the value of your data with advanced analytics and AI. Our team can evaluate your current efforts and recommend the quickest path to revenue growth and marketing optimization. If you want a partner who stays ahead of digital marketing innovations, understands the financial services industry, and competes to win for you, let’s talk.
SCHEDULE A CONSULTATION Find a time using our online scheduler. We’ll bring a small team of experts well-versed in your stack and collaborate to come up with an immediate revenue-driving plan.
CONTACT
Tom Gillum 603.498.7919 tom.gillum@concordusa.com concordusa.com
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