Customer Lifecycle Management How Infogix Helps Enterprises Manage Opportunity and Risk throughout the Customer Lifecycle Analytics can be a sustained competitive differentiator for any industry. Embedding analytics as a solution within business processes, creating ease-of-use and bridging the gap between users and quantitative statisticians can propel adoption. Big data opportunities are bestexploited with analytics. Gartner Group Introduction A customer-centric company is one that understands and embraces the value of its user base, and knows how to use customer information to drive increased customer satisfaction and increasing revenue. As the business analyst firm, Forrester, describes it, we are now living in the age of the customer. As enterprises move from early stage engagement into mature levels of their market lifecycles, robust data integrity and analytics become invaluable tools driving differentiation and delivering unique value. In market sectors like media and communications, financial services, retail and healthcare, identifying and managing best customers becomes a prime initiative to sustaining growth and a competitive advantage. Management consulting firm McKinsey & Company frames analytics this way: Analytics can be a sustained competitive differentiator for any industry. Embedding analytics as a solution within business processes, creating easeof-use and bridging the gap between users and quantitative statisticians can propel adoption. Big data opportunities are best-exploited with analytics. Infogix and Customer Lifecycle Management Infogix s position on effective customer lifecycle management is grounded in two segments that together provide an efficient and effective solution: Robust data integrity solutions provide the necessary validation and efficacy of enterprise data, while a dynamic analytics platform leverages clean, trustworthy data in real-time conditions. Companies that compete in mature markets rely on this combination of controls and analysis to provide a competitive advantage. Often their markets already evolved into a near zero-sum game where growth is slow and gaining new customers often comes through winning them away from other competitors. At the same time, these enterprises know that identifying your best customer is the key to profitability, since acquiring sub-prime customers has proven to be a less-than optimum market strategy. Best customers are reliable and predictable, and provide long-term fiscal stability for a balance sheet. And by studying their on-going behaviors, an enterprise is able to uncover key learnings that may signal either market trends or shifts in customer tastes. CAS-0028-TSYS
Stages in the Customer Lifecycle Infogix identifies these major stages and milestones in the customer lifecycle: Acquisition and Onboarding Upsell/Cross-sell Loyalty/Churn Management Collection Effectiveness Rescue Acquisition and Onboarding Acquisition and onboarding is one of the most important events in the customer lifecycle, and the time an enterprise is most at risk. It is important to get the right data integrity processes and controls in place so that acquisition and onboarding leads to solid customer growth. The products/services contracted at acquisition, the level of customer service the customer receives and the service expectations that are raised have a huge bearing on future profitability and customer loyalty. It is vital that prospects get the right offer for the right product at the right time at this crucial point in the process. While seizing the opportunity the customer brings, the enterprise must also manage the potential risk that acquiring a new customer can introduce. For example: With the advent of the Affordable Care Act (ACA), healthcare insurers now face a new competitive market. These enterprises are now relying on controls and analytics even more so than just two years ago due to the fundamental changes brought on by the ACA. The Infogix Customer Analytics Solution provides a platform that identifies risk and opportunity at acquisition and onboarding. Many times risk and opportunity can be identified using only an enterprise s own data, including the application for service. The first vital step is to know with whom you are dealing. When prospects apply for service, some of them modify their identities either innocently or on purpose. Obviously identifying fraud at time of acquisition is a great risk management tool, and goes directly to the bottom line. Comparing new prospects to existing subscriber datasets allows for quick identification of previous high-risk customers who are applying for new service. The Infogix Identity Analytics Solution definitively compares all variations of name, address, social security number and other attributes in a few seconds, to recognize high-risk applicants at the point of sale before providing a financial risk. Identity Analytics highlights returning bad debt customers for
banks still have vast, largely untapped potential at their fingertips: their existing customer base. Banks can enhance their revenues while maximizing the value of this base using next-generation one-to-one banking similar to the customer lifecycle management approach now being applied by leading telcos. In-depth analysis of each customer s profile and preferences using state-of-the-art data mining techniques can yield very positive results surprisingly fast. Banks have seen with this methodology a shift from fewer than two products per client to over six. Others have been able to increase profitability in their retail branch network by some 20% by combining tailor-made pricing and cross-selling initiatives. McKinsey & Co. Driving Customer Growth with Customer Value Maximization: How Banks Should Go Beyond CRM special treatment enabling you to collect against past debts (as allowed by law) and manage higher risk customers correctly from the beginning. Identity Analytics also recognizes returning good customers positioning you to maximize profitability and loyalty. Infogix PropensityScoring takes the historical analysis further by predicting the customer/subscriber s ability to pay, desire to buy or introduce risk and their propensity to churn. Infogix Propensity Scoring can be used in real-time, at the point of sale. Infogix is able to provide a go-or-no-go decision within seconds after input of prospects data. That means you can control the amount of risk you introduce to your customer base in real-time, while capitalizing on the opportunity presented. Finally, technology analyst firm, Forrester, believes propensity models are a key to understanding your customer set. Understand future behavior through propensity models. Use advanced predictive techniques, coupled with the existing historical knowledge of customers, to build propensity models that help marketers predict the likelihood that a customer will respond to an offer or message and convert. For example, Telenor Group, a Norwegian-based mobile operator, built several churn and propensity models to model customer behavior, thereby reducing churn by 1.8% and improving overall campaign ROI. Upsell/Cross-Sell Knowing the propensity score of each customer throughout their lifecycle ensures the ability to maximize lifetime value. Customer behavior is not static; it changes over time, influenced by the customer s personal situation, by their experiences with the enterprise and its competitors, and by changing market conditions and product innovations. Scoring for Propensity to Buy, Pay and Introduce Risk Highlights When customers are most likely to buy new products and services, this score indicates which offer is most likely to persuade them, whether they will be able to pay for the service over time, and whether they are trying to circumvent the integrity of the network. Propensity to Buy is a highly predictive analytics engine that allows an enterprise to score any customers appetite for products and services at any point in the lifecycle. It also is able to predict customers future needs, based on their history and current usage and trends. This analysis allows you to be one step ahead of your customers needs. It is a key driver of increased average revenue per user (ARPU) and overall profitability. Propensity to Pay evaluates the likelihood that the customer will pay for services over time. With these solutions, companies can begin to maximize lifetime value from the moment of first contact with the customer.
A metric such as Propensity to Pay is very important in order for a company to determine whether or not a customer meets critical metrics and can be a more profitable customer. Loyalty/Churn Management Management consulting firm, Boston Consulting Group believes that The old adage What get measured gets done is fine as far as it goes. But what if you re measuring doesn t provide the full picture? Companies that focus on measuring only core product-related elements can end up losing customers without understanding why. Failing to focus on the full customer experience gets increasingly costly as products mature. On-going marketing efforts are important activities in developing customer loyalty. Once gained, customer loyalty is a golden asset that pays long-term dividends. Understanding your customer means building loyalty is more than just data gathering. Regardless of industry, loyalty and aggressively reducing churn are prime objectives. Especially as service penetration reaches saturation, In the case of cellular providers, identifying those subscribers who are at greatest risk of churn is an important predictive exercise that can keep customers in the fold. Things such as new product or model improvements in phones can be a big driver for customers to churn. And in financial services, new types of credit programs can lure customers to make a change. Understanding what actions would be sufficient to retain them, while comparing the cost of savings of those customers to their future profit potential can be the difference between growth or contraction. Saving the right customers has enormous value, while saving customers who will not produce future margins can be very expensive. The Infogix Churn Management Solution integrates the Propensity to Churn score for each individual customer based on retention risk, at a specific time and under any given set conditions. It is used to identify subscribers whose loyalty is at risk. It also highlights which conditions can be changed by an enterprise to significantly lower the risk. By also analyzing the propensity of the customer to buy things and pay for them in the future, an enterprise is easily able to see whether the cost of retention exceeds future returns. It can selectively address those customers, for whom protective actions will produce a positive return on investment (ROI), automatically formulating an appropriate offer for each customer at risk. For health insurers, this may mean creating specific outreach programs to engage members.
The old adage What gets measured gets done is fine as far as it goes. But what if you re measuring doesn t provide the full picture? Companies that focus on measuring only core product-related elements can end up losing customers without understand why. Failing to focus on the full customer experience grows increasingly costly as products mature. Boston Consulting Group Winning by Understanding the Full Customer Experience In highly competitive markets, churn is one of the most prevalent threats to growth. Not understanding your customer s propensity to churn leads to a competitive disadvantage that can rear its head for fiscal quarters on end. For financial services companies, Propensity to Pay can be a key attribute to minimizing bad debt risk. Knowing the customer s ability to pay enables credit limits to be managed in a way that reflects the overall economics of each customer, real-time to take into account changing situations. Customers propensity to pay will vary based on brand loyalty, perceived product value and interactions with the company, as well as on personal and external circumstances which are out of the company s control but can change dramatically over time. Assessing propensity to pay throughout the customer lifecycle enables an enterprise the ability to adjust credit and collection policies in real-time to maximize ROI. Collection Effectiveness Propensity to Pay is used with customers who have been discontinued for bad debt, as well as for current customers/subscribers. Knowing each customer s propensity to pay allows collection departments the ability to focus their collection efforts on accounts which will eventually pay and save money and resources by giving up early on former subscribers who are appropriately treated a lost cause. This simple approach reduces expenses and increases collections and paybacks. Because the propensity scoring can be tested under different scenarios, payment terms can be customized at scale for each debtor in a way that maximizes ROI. Financial services firms know this innately and have used this extensively in the recent recession. Separating good customers who have been going through a difficult stretch (i.e. layoff) versus customers who will soon be in bankruptcy is important. Rescue Subscribers who have bad debt often find it difficult to get credit from competitors; but they almost always still have a need for insurance, credit cards or a cell phone. With Infogix modeling tools, such as Propensity to Buy and Propensity to Pay, the best customers can be targeted for rescue and reinstatement. Offers can be structured that are attractive to the customers, while permitting meticulously careful management of outstanding credit. In healthcare for instance, the ACA requires consumers to purchase insurance or face penalties. Because of the volatility of both the economy and changing company policies, individual consumers could switch healthcare providers
Understand future behavior through propensity models. Use advanced predictive techniques, coupled with the existing historical knowledge of customers, to build propensity models that help marketers predict the likelihood that a customer will respond to an offer or message and convert. For example, Telenor Group, a Norwegian-based mobile operator, has built several churn and propensity models to model customer behavior, thereby reducing churn by 1.8% and improving overall campaign ROI. annually. Having critical knowledge of a customer s current and past activity (both medical and financial) can be crucial to understanding if that customer is a good candidate for rescue. Given the high cost of acquiring new subscribers, these rescue activities can be a very attractive investment. Properly managed, rescued subscribers can become profitable and loyal customers. Conclusion As the world accelerates its recovery from the great recession, more and more enterprises understand the purpose and the need for reliable data controls combined with robust analytics. Infogix offers multiple solutions for a wide variety of enterprises that want to understand their customers as best they can. This age of the customer is just beginning and the ability of an enterprise to harvest the incredible amount of transactional and historical data is what will define who wins and who loses. Infogix has helped companies in multiple industries, around the world, manage and analyze this invaluable customer asset. Infogix. Better data. Better results. Forrester How Analytics Drives Customer Lifecycle Management Infogix Entperise Data Analysis Platform can save you time and money Visit www.infogix.com or call 1.630.649.6800 (US, Canada, and International), +44 1242 674 137 (UK and Europe). twitter.com/infogix facebook.com/infogix linkedin.com/company/infogix plus.google.com/+infogix Copyright 2016 Infogix, Inc. All rights reserved. Company, product, brand, and mark names and logos herein are the property of their respective owners. For a list of Infogix trademarks, visit: www.infogix.com/legal