How Card Issuers Can Leverage Big Data to Improve Cardholder Retention Efforts

Size: px
Start display at page:

Download "How Card Issuers Can Leverage Big Data to Improve Cardholder Retention Efforts"

Transcription

1 White Paper How Card Issuers Can Leverage Big Data to Improve Cardholder Retention Efforts By Rob Hudson The most valuable commodity I know of is information. - Gordon Gekko, main character in the film Wall Street (1987). Big data, generally defined as the collection and cross-referencing of large numbers and varieties of data sets has garnered enormous attention recently, as it allows organisations to identify patterns and categorise cardholders through a multitude of attributes and variables. The ability to collect and analyse mountains of consumer data, whether from social media or more traditional methods, is providing businesses with unprecedented levels of insight that can inform their decision making. Mobile technologies have greatly enhanced this data collection by giving organisations valuable information about individuals transactions, preferences and online interactions. According to IDC, the volume of data stored in 2012 was 2.7 zettabytes, 1 or 2.7 billion terabytes. Businesses across a wide range of industries now put big data at the centre of their operations. 2 Analysis of today s big data sets can reveal valuable and actionable insights, such as helping to identify cost-cutting measures, product improvements or customer retention strategies. Yet, despite these benefits, executives are unprepared for leveraging big data. A recent scorecard on big-data business challenges found that while 67 percent of executives say that the ability to draw intelligence from their data is a top priority for their organization, 29 percent give their organization a D or F in preparedness for a data deluge. 3 Maximise Lift from Big Data Now Card issuers are particularly well-poised to derive benefits from big data. Given the amount of customer transaction information they collect, they have a huge opportunity to use that data to better serve and retain their current cardholders and acquire new ones. Transaction data derived from customer activities like purchases, cash withdrawals, balance transfers or ATM withdrawals will provide a more complete picture of cardholder behaviour and, in turn, identify which cardholders are the most profitable. Graph A 8% How Would You Grade Your Organization s Preparation to Manage a Data Deluge? 32% 31% 25% 60% give their organization a C or below* A B C D F Source: From Overload to Impact: An Industry Scorecard on Big Data Business Challenges. 4%

2 However, many card issuers need to consider their current use of data and how to deploy a big-data initiative effectively in their organisations. They need strategies for acquiring, organising and analysing volumes of data so they can use it to improve their decision making. Card issuers do not need to purchase additional data, analytical tools or other products to glean useful customer and business intelligence. Rather, they can leverage existing internal resources, such as database administrators, market intelligence analysts and report writers, who can help them use their own data. In fact, card issuers can avoid significant investment by leveraging their in-house tools and resources such as existing data, skill sets and analytical platforms. This report introduces big data and provides a path for card issuers to leverage it. Next, it explains the potential applications of big data by card issuers and how payment and transaction data, when coupled with the right analytical platforms, can provide better insights into customer behaviours. Finally, the report lays out three best practices card issuers can deploy to capitalise on big data and support cardholder retention strategies. How Card Issuers Can Use Big Data to Address Specific Business Challenges Identifying and retaining the best cardholders remains a key challenge for card issuers, especially considering today s threat of decreased interchange fees. Because the cost of acquiring new cardholders remains very high over 80 per account in some markets it s imperative to efficiently and effectively target prospective cardholders when rolling out acquisition efforts such as balance-transfer promotions. How does a card issuer maximise the retention rate of balance-transfer cardholders rather than see them disappear once the balance-transfer offer expires? And how does it prevent the exodus of high-quality cardholders? Leveraging data is a key component of solving these challenges. Card issuers should adopt a cradle-to-grave approach that uses data to gain better insights about cardholders from the time they open an account to the time they close it. Once cardholders have been identified or segments created, it is essential that management strategies are in place for the various scenarios throughout the account life cycle. Would you subject your most valuable cardholders to the same retention strategy as your least valuable cardholders? Surely a different collection strategy should be adopted for distinct segments when a payment Using Big Data Effectively Collection of data Identify types and variety of available data. Analysis of data Identify customer segments. Decide how to approach these segments with specific offers and incentives, along with determining their preferred communication methods. Develop strategies for particular goals, such as cardholder retention. Deliver Contact cardholder segments with relevant messages and offers. Manage & Measure Identify and measure key performance indicators. Optimise results through refinement of programme. Consider testing the approach on a select subset of data, such as in a particular region or product. is missed for the first time. Alternatively, acquisition strategies should focus on acquiring new cardholders that fit the profile of the most desirable cardholders. An Introduction to Big Data: Volume, Variety and Velocity According to Gartner Inc., big data is defined as high volume, high velocity and/or high variety information assets that can be used to improve decision making and provide better insights. The amount of data available today has reached seemingly astronomic levels, thanks much to the fast growth of Internet and mobile usage. By early 2013, billion people worldwide regularly used the Internet. According to McKinsey, data are flooding in at rates never seen before, doubling every 18 months as a result of greater access to customer data from public, proprietary, and purchased sources, as well as new information gathered from Web communities. 5 The types of data collection have expanded beyond structured data, such as transaction histories and credit scores, and now encompass many 2

3 Characteristics Defining Big Data Volume Variety Velocity Volume of data stored in enterprise repositories have grown from megabytes and gigabytes to petabytes. E.g., volume of data processed by corporations grew significantly, e.g. Google processes 20 petabytes/day. By 2020, 420 billion electronic payments are expected to be generated. Financial Services Example: The number of credit cards in a market represents volumes of data in terms of customer details such as DOB, address and account details like APR rates, card expiration, etc. TSYS stores 7 petabytes of data. Data variety exploded from structured and legacy data stored in enterprise repositories to unstructured, semi-structured, audio, video, XML etc. Streaming data, stock quotes, social media, machine-to-machine, sensor data all drive increasing variety that needs to be processed and converted into information. Financial Services Example: A variety of sources open to card issuers include the basics like application processing collections and disputes. This can be augmented by click streams and Web analytics and social media data. Speed of data movement, pocessing and capture in and outside enterprise went up significantly. Model based business intelligence models typically take days for processing - compared to almost real-time analytics requirements of today using incoming stream of high-velocity data. Financial Services Example: E.g., ebay is addressing fraud from PayPal usage, by analyzing real-time 5 million ransactions each day. Sources: Gartner Inc. & TSYS untraditional sources, such as social media sites, Web server logs, real-time trading and blogs. 6 Facebook alone has approximately one billion users worldwide 7 and clearly collects enormous amounts of user data. Similarly, as the number of Internet-enabled smartphone users speeds toward one billion worldwide, mobile phones will provide for additional data collection and allow companies to create robust customer profiles. Social media data and the like is often held in an unstructured format unsuitable for storage in traditional relational databases. However, card issuers will first want to concentrate on utilising structured data, such as transaction data and credit histories, which can provide some of the best insights into customer preferences and other behaviours that directly affect a card issuer s key performance metrics. This ability to gather so much data and information gives companies a newfound opportunity to better understand their cardholders and glean potentially valuable insights into how to better serve them. However, the challenge is how to analyse and process that data quickly, accurately and securely. Some companies have mastered the usage of big data and made it profitable. It is estimated, for example, that Walmart collects more than 2.5 petabytes of data every hour from its customer transactions. A petabyte is one quadrillion bytes, or the equivalent of 20 million filing cabinets worth of text. 8 As a leader in leveraging big data, Walmart seeks to continually refine its usage. A recent article on MediaPost.com discusses the emphasis Walmart places on customer profiling: They know who their customers are, and they ve got tons of data from past purchases and online behavior to inform their efforts. Building on the idea of personalizing each individual s online experience, Walmart can easily improve each subsequent experience, something that may seem like it involves a significant level of complexity. But with the right infrastructure, it can be completely automated and dynamic. The key to accomplishing this is putting visitor profiles at the heart of each cross-channel experience. 9 When used correctly, big data s largest value is its ability to provide companies with actionable insights that can lead to smarter decision making. Indeed, a Harvard Business School study found that data-based decisions are more profitable: The more companies characterized themselves as data-driven, the better they performed on objective measures of financial and operational results. In particular, companies in the top third of their industry in the use of data-driven decision making were, on average, five percent more productive and six percent more profitable than their competitors. 8 Insights gleaned from the analysis of big data can inform smarter decisions. Recent research suggests that organisations are losing revenue due to insufficient data management, with 93 percent of executives believing their organisation is losing revenue as a result of not being able to fully leverage the 3

4 information they collect. On average, they estimate this lost opportunity to be 14 percent of annual revenue. 3 As companies look to increase revenue, they needn t look very far: There is a gap of 14 percent that can be closed by gleaning insights from existing internal data. Greatest Impacts with Initial Staged Approach to Implementing Big Data Before undertaking a big-data initiative, however, card issuers should first assess the existing data types they can access both internally and externally. For one thing, a focus on leveraging existing data will most likely not require an investment in new software and hardware. More importantly in the long run, as shown in Graph B, issuers can get the most significant return by taking advantage of the data and information to which they already have immediate access but are not leveraging to its fullest potential. For example, a card issuer likely has internal access to transaction data, call logs and general ledger information, and it may be able to externally source credit and fraud data, as well as local economic information such as real estate and unemployment data. Initially, a card issuer should evaluate which type of internal data is readily available and the insights that can be discerned from it. After that, it can build upon that internal information by sourcing data from outside the organisation. That approach can reduce the need for a card issuer to immediately buy the infrastructure and software needed to analyse data sourced from third parties. In other words, once issuers lay the foundation of the basics, then they can look to other types of data such as that derived from social media which holds lower marginal returns. Jumping to the refinement stage without mastering the basics will divert attention from where the more immediate and higher-impact opportunity lies. Jumping to the refinement stage without mastering the basics will divert attention from where the more immediate and higher-impact opportunity lies. Transactional data tends be the most valuable because it reflects actual customer behaviour. Overlaying transactional data with external data can help card Graph B Diminishing Marginal Returns by Depth of Data Data Optimisation Returns Region Post Code Geo-demographics Transactional Data Facebook Twitter issuers with retention efforts by helping them determine relevant offers specific to a distinct customer segment or even for individual cardholders. More specifically, the insights derived from the card issuer s customer data can help optimise new client offers, as well as support product cross-sells. Call centre data could provide insights into a customer s attitude toward the card issuer. Such information could reveal whether the card issuer is missing an opportunity for either a new product offering or refinement, which could increase card usage. Furthermore, call centre data could reveal customer preferences for the different customer service channels and identify which channels are more efficient or even which products require the most client contact. Ultimately, these insights increase the efficiency and effectiveness of both customer acquisition and retention efforts. Other, less-structured types of data, such as Facebook likes or Foursquare check-ins can also be used to fine-tune customer targeting but should not be an initial focus. Once issuers are ready to progress to more advanced stages and tactics, they can look to harvest data from external or non-traditional data sources, such as social media, call centre notes, online chats, geo-location logs and correspondence, gaining further insights into customer sentiments and behaviours. 4 Square Other Social Media Source: TSYS Indeed, some institutions are using Facebook to determine the likelihood of default for those without a credit history, for example. Marrying various structured and non-traditional types of data ultimately allows a card issuer to create a holistic picture of its cardholders. In fact, Facebook data already inform lending decisions at Kreditech, a Hamburg-based start-up that makes small 4

5 online loans in Germany, Poland and Spain. Applicants are asked to provide access for a limited time to their account on Facebook or another social network. 10 Before attempting to leverage big data, card issuers should first develop a test pilot programme using a smaller, more manageable data set. Upon launching a successful pilot, an organisation can proceed with a broader programme that brings in a range of data sources. For example, a card issuer might consider analysis across multiple data sets, such as contact centre communications, Web analytics, or alternative financial product-processing platforms, such as those for mortgages or current accounts. Looking at data through a new analytical lens can reveal new and valuable insights. A test, learn and optimise performance-oriented approach to data analysis has been successfully used by many of today s most reputable Web-based companies. Amazon.com, for example, experimented early on with webpage layouts and content displays in order to increase its sales and improve other key metrics. Big data has delivered returns at Tesco by improving promotions to ensure 30 percent fewer gaps on shelves, predicting the weather and behaviour to deliver 6 million less food wastage in the summer, 50million less stock in warehouses, optimising store operations to give 30 million less wastage. 11 Capital One continually seeks to refine its methods for segmenting credit card customers and for tailoring projects to individual risk profiles. According to Nigel Morris, a co-founder of Capital One, the company conducts more than 65,000 tests each year, experimenting with combinations of market segments and new products. 5 For many card issuers, the data they already have in their vaults is the most valuable, and now is the time to leverage it. For example, clickstream data, which logs how Web visitors navigate a site can be used to understand the effectiveness of a card issuer s online user interface. It can answer questions such as: What is the most sought-after content? How and when are visitors accessing the site? And, from which sites are they coming? A Harvard Business Review article says that data-driven strategies will become increasingly important in helping organisations of all types achieve competitive For many card issuers, the data they already have in their vaults is the most valuable, and now is the time to leverage it. differentiation. 12 For card issuers, leveraging their big data can help them meet their business or programme objectives, whether that means improving returns on investment, increasing cardholder acquisition or retention rates, identifying credit risk, or targeting the right offers (new products or cross-sell promotions) at the right cardholders at the right time. The following best practices take an in-depth look at customer retention, as it is a key contributor to a card issuer s long-term success. Best Practice #1: Identify and Analyse Characteristics and Behaviours of Existing Cardholders Card issuers undoubtedly hold some of the most complete and valuable consumer information available. Given their wealth of internal data, card issuers should focus on identifying and analysing characteristics and behaviours of both existing and prospective cardholders. This can be accomplished by using internal transaction data to identify cardholder purchase patterns. Transaction histories can provide banks with a robust customer profile, including an indication of the customer s approximate annual income, spending habits, online usage patterns and transaction types, along with how he or she typically makes payments, whether by debit, credit, electronic transfer, PayPal or cheques. All of the transaction data collected by card issuers is extremely valuable for predicting future customer behaviours and transactions. For example, a card issuer can analyse cardholder spending patterns, first by using Merchant Category Codes and then possibly at the merchant description level. This would enable the grouping of cardholders based around spending category types, whether electronics, childcare services or cosmetics. These types of groupings could help a card issuer identify cardholders with similar behaviours and transactions patterns, targeting relevant offers at them. 5

6 Graph C Driving Cardholder Response to Issuers Call to Action Design 3 Design 3 Use Analytics to segment and customise 2 4 Receive Responses Response Rates Use Analytics to segment 2 and customise Design 3 4 Use Analytics to segment and customise 2 6 Track Response Receive Rates Responses 5 Analyse Results 4 6 Track Response Receive Rates Responses 5 Analyse Results 1 Define Goals 5 Analyse Results Source: TSYS Effort Optimisation The Process Step 1- Define and establish goals for your gampaign. What measurable goal would you like to meet? For example, increased recency (last usage), frequency and monetary value, or perhaps increased cross-selling, improved customer loyalty, or additional wallet-share. Step 2- Analyse and segment existing customer database. Segment customers into similar groups and create control and test groups with differing offers, such as APR rates or redemption time lengths. Establish key customer behaviors for card usage and the preferred method of contact. The data and criteria available to segment are readily-accessible resources, facilitating easy-to-build predictive models. Step 3- Design the messaging and offerings for a variety of channels and deliver from any or all channels. These include real-time interactive voice response (IVR) or customer serice scripts, , SMS-text for mobile or traditional mail. Step 4- Receive and collect responses to offers and measure the ROI of campagin. Step 5- Analyse the results, contrasting and comparing the test and control groups. How did results compare to the goals defined for the campaign? You can modify offerings based on your analysis and expand the campaign to additional groups within each segment. Step 6- Track response rates of different segments. Compare the control group with baseline offer and test group with a different offer. For example, use convenience checks with 15% APR for the control group and give other sub-segments a lower APR. Best Practice #2: Using If/Then Scenarios and Testing for Retention Initiatives While some executives may rely on their gut instinct, making decisions based on hard facts and testing often proves more reliable. Using so-called if/then scenarios gives executives a strategic approach for testing, measuring and optimising programmes against a given set of business objectives, and can thereby improve key business performance metrics. Graph C depicts such a process, which begins by defining programme goals. For example, a card issuer may want to increase spending among the top 10 percent of its portfolio by 5 percent on average. Also, using analytics to segment based on cardholders transaction histories and expected behaviours allows Also, using analytics to segment based on cardholders transaction histories and expected behaviours allows for the development of calls-to-action that could boost retention while also reaching cardholders in their preferred communication channels. for the development of calls-to-action that could boost retention while also reaching cardholders in their preferred communication channels. Once a programme goes live, the tracking of customer responses allows the card issuer to refine and better 6

7 target its future offers and communications. The benefit of an if/then approach is twofold: First, it allows for greater customisation. If, for example, a card issuer segments existing cardholders based on their customer profiles, it could incentivise cardholders with fewer transactions to increase their transaction frequency by offering a rewards programme that provides greater rewards for spending more. Second, an if/then approach focuses on enhancing cardholder acquisition rates. If a card issuer uses a geo-demographic segmentation system that identifies new target groups based on postal codes, for example, acquisition efforts can target the most appropriate incentives or content at the right audiences. In other words, it helps provide relevant marketing offers to the right people. Data-driven insights can help card issuers provide more compelling offers to specific segments of existing cardholders, boosting loyalty and increasing the lifetime and overall value of the relationship. According to Tower Group, The goal is to understand how each person behaves and to price products and services accordingly to their needs. 14 Starbucks serves as a great hypothetical example of how a company could leverage transactional data to improve its customer loyalty efforts. Regular customers spend a certain amount per day or week on Starbucks beverages or food. Transactional data from Starbucks could be crossreferenced with more behavioural or emotion-based data, such as customers activities on social networks, in order to better predict those cardholders purchase patterns and, in turn, improve marketing and promotional offers to increase customer spending. Understanding cardholders patterns can help the company design programmes that will increase customer engagement. This might entail motivating a customer to redeem specific promotions, whether coupons generated at the point of sale or buying a Starbucks stored-value card. Ultimately, these initiatives could decrease checkout time or boost average ticket sales or frequency of store visits. Furthermore, the analysis of transaction data could potentially reveal valuable information, such as food and snack preferences at a specific time of day, preferred payment mechanism or other correlative factors. Here s a hypothetical example of how data can be used to better engage and retain cardholders: Susie, a 35-year-old professional, indicates via social media that she is looking to buy a new apartment in Paris. Susie s bank cross-references her social media profile with its account data and matches it with Susie s bank profile. By doing so, the bank knows that now would be a good time to present Susie with a timely and attractive mortgage offer. This intelligence could help boost revenue in numerous ways, whether by increasing cross-selling opportunities, improving point-of-sale offers or using location-based data from mobile and social media to provide more location-based promotions. According to Gartner, using data to create this sort of context-aware mobile programme is ultimately leading to richer user experiences, stronger customer loyalty and better business processes. 13 Best Practice #3: Use Data to Retain Cardholders In today s economic climate, strategies that support cardholder retention not just acquisition are critical. Data-driven insights can help card issuers provide more compelling offers to specific segments of existing cardholders, boosting loyalty and increasing the lifetime and overall value of the relationship. According to Tower Group, The goal is to understand how each person behaves and to price products and services accordingly to their needs. 15 Utilising the deeper knowledge about individual cardholders or segments allows card issuers to tailor offers to highly valuable customers who appear to be defecting or those with a lower frequency of card usage. In today s era of personalisation, brands use algorithms to present consumers with offers and services based on their unique interests. The Internet radio station Pandora, for example, allows listeners to enter a favourite artist, song or music genre. It then creates a personalised station and, through a song-rating system, plays music tailored to a user s past preferences. Amazon.com leverages transactional customer information, both on purchases and items placed in its virtual shopping cart, to serve up relevant and timely purchase suggestions. For financial institutions, this kind of personalisation involves using card- 7

8 holders past transactions, bill payment habits, credit records and other history to predict future purchase and card usage patterns. As discussed in a previous report, On-Demand Payment Cards and Personalization, 15 card issuers can improve cardholder retention and usage by presenting cardholders with the option to design and personalise their cards. Personalisation, the report notes, improves cardholder retention by 3 percent, increases transactions by 30 percent and increases card usage by 15 to 20 percent. While card personalisation is clearly an emotional appeal that drives results and increases customer satisfaction, on a broader level, it shows the power of better understanding cardholders and giving them what they want. Here s a hypothetical example of how data can be used to better engage and retain cardholders: Susie, a 35-year-old professional, indicates via social media that she is looking to buy a new apartment in Paris. Susie s bank cross-references her social media profile with its account data and matches it with Susie s bank profile. By doing so, the bank knows that now would be a good time to present Susie with a timely and attractive mortgage offer. Additionally, a card issuer may be interested to identify cardholders who buy frequently from specific types of stores say, bicycle shops or sporting goods stores. It could then target those cardholders with offers to enter and win sporting event tickets, sports-oriented rewards programmes or other marketing offers with an athletic theme. This type of data cross-referencing can clearly be used to cross-sell other types of products. For example, consumers increasingly use Facebook or Twitter to pose questions to their friends and families and gather opinions on purchase decisions: Should I buy an iphone or a Blackberry? What is the BMW driving experience really like? Is it worth the price tag? When cross-referenced with an individual s bank profile, this type of social media data can help card issuers discern which types of offers should be served up at a particular time whether an auto loan, a student loan or a new credit card product with a low-introductory APR or rewards programme. Conclusion: Unlocking the Value of Big Data Leveraging big data can improve the overall customer experience, drive loyalty, and ultimately boost a card issuer s incremental revenue through promotions and cross-sells. It allows for targeted offers that depend on the value and unique behaviours and situations of a particular customer or customer segment. Data and insight-driven offers will better reflect a customer s needs, attitudes and behaviours and, in turn, lead to a higher likelihood of cardholder retention, acquisition and offer acceptance. A Harvard Business Review article says it best: Data-driven decisions are better decisions. It s as simple as that. Using big data enables managers to decide on the basis of evidence rather than intuition. 8 That said, there is an important caveat: Most issuers will only enjoy small returns by leaping to immediately analysing unstructured data from emerging sources such as social media. Instead, issuers that concentrate initial efforts on their current resources and data to which they have immediate access will yield the most significant results. Once issuers have realised the vast majority of lift from such data analysis, they can then refine models to incorporate non-traditional sources and squeeze the marginal returns as they fine-tune their approach. 8

9 Sources: 1 The Future of Technology and Payments. Visa. Edition 2. 2 Rosenbush, Steven and Michael Totty. How Big Data Is Changing the Whole Equation for Business. WSJ.com. March 8, Web. July <http://online.wsj.com/article/sb html?mod=wsj_hpp_sections_tech>. 3 From Overload to Impact: An Industry Scorecard on Big Data Business Challenges. Web. July <http://www.oracle.com/us/ industries/industry-scorecard html>. 4 Decision Management for the Masses. FICO.com Web. July <http://www.fico.com/en/firesourceslibrary/white_paper_decision_management_for_the_masses_2964wp_hr.pdf>. 5 Bughin, Jacques and Michael Chui, and James Manyika. Clouds, Big Data and Smart Assets: Ten Tech-enabled Business Trends to Watch. McKinsey Quarterly. August Web. July <http://www.mckinsey.com/insights/high_tech_telecoms_internet/clouds_ big_data_and_smart_assets_ten_tech-enabled_business_trends_to_watch>. 6 Meeting the Challenge of Big Data: Part One. Oracle. Web. July <https://www.google.com/search?q=meeting+the+challenge+ of+big+data%3a+part+one&oq=meeting+the+challenge+of+big+data%3a+part+one&aqs=chrome.0.69i57j69i62l3.247j0&source id=chrome&ie=utf-8>. 7 Number of Active Users at Facebook Over the Years. The Associated Press. Yahoo.com. May 1, Web. July <http://news.yahoo.com/number-active-users-facebook- over html>. 8 McAfee, Andrew and Erik Brynjolfsson. Big Data: The Management Revolution. Harvard Business Review. October Simpson, Mark. Amazon vs. Wal-mart: How Big Data Will Bridge the Gap. Marketing Daily. May 1, Web. July <http://www.mediapost.com/publications/article/198104/amazon-vs-wal-mart-how-big-data-will-bridge-the.html#ixzz2whkwv7ng>. 10 Lenders are Turning to Social Media to Assess Borrowers. Economist.com. February 9, Web. July <http://www.economist.com/news/finance-and-economics/ lenders-are-turning-social-media-assess-borrowers-stat-oil>. 11 Miller, Paul. Tesco Uses Data for More than Just Loyalty Cards. Cloudofdata.com. October Web. July <http://cloudofdata. com/2012/10/tesco-uses-data-for-more-than-just-loyalty-cards/>.barton, Dominic and David Court. Making Advanced Analytics Work for You. Harvard Business Review. October Dominic, Barton and David Court. Making Advanced Analytics Work for You. Harvard Business Review. October Pete Basiliere. Hype Cycle for Context-Aware Computing, Gartner. July 27, Seeing the Forest and the Trees: Calculating Customer Lifetime Value. TowerGroup. April Wolbert, George. On-Demand Payment Cards and Personalization. TSYS.com. October Web. July <http:///downloads/upload/on_demand_payment_cards_and_personalization_white_paper.pdf>. 9

10 About the Author: Rob Hudson Senior Director of Client Management, TSYS International Rob Hudson is senior director of Client Management for TSYS International. He is responsible for TSYS UK clients, their card processing performance and delivery against operational and financial objectives. A 25-year veteran of the payment card industry, Hudson has previously managed the full product portfolio across TSYS European business. Prior to his time at TSYS, Hudson held senior roles at HSBC, GE Capital and PricewaterhouseCoopers, and has played a key role in all card sectors including consumer and commercial issuing, merchant acquiring and debit. About TSYS At TSYS, (NYSE: TSS), we believe payments should revolve around people not the other way around. We call this belief People-Centered Payments Ṣ M By putting people at the center of every decision we make, with unmatched customer service and industry insight, TSYS is able to support financial institutions, businesses and governments in more than 80 countries. Offering merchant payment-acceptance solutions as well as services in credit, debit, prepaid, mobile, chip, healthcare and more, we make it possible for those in the global marketplace to conduct safe and secure electronic transactions with trust and convenience. TSYS headquarters are located in Columbus, Georgia, with local offices spread across the Americas, EMEA and Asia-Pacific. TSYS provides services to more than half of the top 20 international banks, is a Fortune 1000 company and was named one of the 2012 World s Most Ethical Companies by Ethisphere magazine. For more information, please visit us at. Contributors This report was prepared by TSYS. Contributors to this paper under the guidance of Rob Hudson include: Product Consultant, Richard Hamilton; Independent Writer, Carolyn Kopf Total System Services, Inc. All rights reserved worldwide. Total System Services, Inc., and TSYS are federally registered service marks of Total System Services, Inc., in the United States. Total System Services, Inc., and its affiliates own a number of service marks that are registered in the United States and in other countries. All other products and company names are trademarks of their respective companies. (08/2013)

TSYS Analytics Intellisuite SM

TSYS Analytics Intellisuite SM Solutions Overview put your data into action with TSYS Analytics Intellisuite SM Enjoy richer insight through advanced dashboards Create and predictively test business strategies Take action and drive

More information

Customer Engagement Solution

Customer Engagement Solution Solution Overview Customer Engagement Solution Improved One-to-One Marketing Channel Optimization Easy-to- Measure ROI Regulatory Compliance Simple End-to-End Solutions for Targeting and Executing the

More information

It s more than a payment. People - Centered Payments. it s the purchase that made their house a home. an overview of our global payment solutions

It s more than a payment. People - Centered Payments. it s the purchase that made their house a home. an overview of our global payment solutions an overview of our global payment solutions People - Centered Payments SM It s more than a payment. it s the purchase that made their house a home. www.tsy s. com people-centered payments Who We Are From

More information

Mobile Banking Apps Becoming Financially Involved

Mobile Banking Apps Becoming Financially Involved Research Paper Mobile Banking Apps Becoming Financially Involved By Joseph Majestic Mobile is one topic that continues to garner significant attention across the banking and payments industries. A quick

More information

How Big Is Big Data Adoption? Survey Results. Survey Results... 4. Big Data Company Strategy... 6

How Big Is Big Data Adoption? Survey Results. Survey Results... 4. Big Data Company Strategy... 6 Survey Results Table of Contents Survey Results... 4 Big Data Company Strategy... 6 Big Data Business Drivers and Benefits Received... 8 Big Data Integration... 10 Big Data Implementation Challenges...

More information

Transforming customer service with business analytics

Transforming customer service with business analytics IBM Software Business Analytics Customer Service Transforming customer service with business analytics 2 Transforming customer service with business analytics Contents 2 Overview 2 Customer service is

More information

Deploying Insights from Online Banking Analytics in Incremental Innovation

Deploying Insights from Online Banking Analytics in Incremental Innovation Universal Banking Solution System Integration Consulting Business Process Outsourcing The relevance of online analytics to banking In its 2010 report on the state of online banking in the United States,

More information

TSYS Managed Services. Reduce your fraud exposure and losses by utilizing Fraud Mitigation Services from

TSYS Managed Services. Reduce your fraud exposure and losses by utilizing Fraud Mitigation Services from Solutions Overview Full Suite of Managed Services for Mitigating Fraud Leverage our global visibility to identify and prevent fraud Select from a suite of services to meet your needs Reduce your fraud

More information

Doing Business With TSYS our approach to commerce and payments

Doing Business With TSYS our approach to commerce and payments Doing Business With TSYS our approach to commerce and payments www.tsys.com TSYS at a Glance our purpose is to Improve Lives and Businesses by Putting People at the Center of Payments. WHO WE ARE Company

More information

Sage CRM. Communicate, Collaborate, Compete with Sage CRM

Sage CRM. Communicate, Collaborate, Compete with Sage CRM Sage CRM Communicate, Collaborate, Compete with Sage CRM FEATURES AT-A-GLANCE FOR ALL USERS Easy to use with fresh look and feel Fully customisable interactive dashboard End-user personalisation of interface

More information

Celebrus for Telecommunications: Deepening customer intelligence with individual-level digital data

Celebrus for Telecommunications: Deepening customer intelligence with individual-level digital data SECTOR SOLUTIONS Celebrus for Telecommunications: Deepening customer intelligence with individual-level digital data p1 Introduction Today s Telecommunications sector is highly dynamic. Firstly the very

More information

Capitalizing on the power of big data for retail

Capitalizing on the power of big data for retail IBM Software Big Data Retail Capitalizing on the power of big data for retail Adopt new approaches to keep customers engaged, maintain a competitive edge and maximize profitability 2 Capitalizing on the

More information

Leveraging the Internet of Things in Marketing

Leveraging the Internet of Things in Marketing Leveraging the Internet of Things in Marketing Index 3 3 4 4 5 5 6 6 Introduction The Internet of Things outlook IoT and marketing Wearables: Reaching customers anywhere Location-based marketing RFID tags

More information

Social Business Intelligence For Retail Industry

Social Business Intelligence For Retail Industry Actionable Social Intelligence SOCIAL BUSINESS INTELLIGENCE FOR RETAIL INDUSTRY Leverage Voice of Customers, Competitors, and Competitor s Customers to Drive ROI Abstract Conversations on social media

More information

5 Big Data Use Cases to Understand Your Customer Journey CUSTOMER ANALYTICS EBOOK

5 Big Data Use Cases to Understand Your Customer Journey CUSTOMER ANALYTICS EBOOK 5 Big Data Use Cases to Understand Your Customer Journey CUSTOMER ANALYTICS EBOOK CUSTOMER JOURNEY Technology is radically transforming the customer journey. Today s customers are more empowered and connected

More information

Decisioning for Telecom Customer Intimacy. Experian Telecom Analytics

Decisioning for Telecom Customer Intimacy. Experian Telecom Analytics Decisioning for Telecom Customer Intimacy Experian Telecom Analytics Turning disruption into opportunity The traditional telecom business model is being disrupted by a variety of pressures from heightened

More information

BUY BIG DATA IN RETAIL

BUY BIG DATA IN RETAIL BUY BIG DATA IN RETAIL Table of contents What is Big Data?... How Data Science creates value in Retail... Best practices for Retail. Case studies... 3 7 11 1. Social listening... 2. Cross-selling... 3.

More information

LISTENING, INTERPRETING, AND ASKING BIG DATA MARKETING QUESTIONS

LISTENING, INTERPRETING, AND ASKING BIG DATA MARKETING QUESTIONS LISTENING, INTERPRETING, AND ASKING BIG DATA MARKETING QUESTIONS 1 LISTENING, INTERPRETING, AND ASKING BIG DATA MARKETING QUESTIONS IN A RECENT SURVEY BY MCKINSEY AND COMPANY, AS MANY AS 50% OF RESPONDENTS

More information

Exploiting the Single Customer View to maximise the value of customer relationships

Exploiting the Single Customer View to maximise the value of customer relationships Exploiting the Single Customer View to maximise the value of customer relationships October 2011 Contents 1. Executive summary 2. Introduction 3. What is a single customer view? 4. Obstacles to achieving

More information

Developing a Credit Card Strategy Leveraging Big Data

Developing a Credit Card Strategy Leveraging Big Data Elan Financial Services 2014 Developing a Credit Card Strategy Leveraging Big Data Big data presents great opportunity for targeting and incentivizing customers with valuble card offers. By Elan Financial

More information

Retail / E-commerce. Turning Big Data (and Little) Into Actionable Intelligence and Customer Profitability. Case Study ebook. Unlocking Profitability.

Retail / E-commerce. Turning Big Data (and Little) Into Actionable Intelligence and Customer Profitability. Case Study ebook. Unlocking Profitability. shop shop shop shop Retail / E-commerce Turning Big Data (and Little) Into Actionable Intelligence and Customer Profitability Part 3 in a series of 5 ebooks on intelligent customer engagement Case Study

More information

Engage your customers

Engage your customers Business white paper Engage your customers HP Autonomy s Customer Experience Management market offering Table of contents 3 Introduction 3 The customer experience includes every interaction 3 Leveraging

More information

connecting buyers and sellers

connecting buyers and sellers Europe Regional Overview connecting buyers and sellers An Overview of Our European Payment Services www.tsys.com Europe Regional Overview Our state-of-the-art European data centre, purpose-built in 2004,

More information

5 Steps to Creating a Successful Optimization Strategy

5 Steps to Creating a Successful Optimization Strategy 5 Steps to Creating a Successful Optimization Strategy Many companies are now recognizing that in a world of mobile devices and increasingly sophisticated online services, the creation of an excellent

More information

Insurance customer retention and growth

Insurance customer retention and growth IBM Software Group White Paper Insurance Insurance customer retention and growth Leveraging business analytics to retain existing customers and cross-sell and up-sell insurance policies 2 Insurance customer

More information

5 Tips for Growing Your Business with Social. Social Marketing in Action at T.H. March

5 Tips for Growing Your Business with Social. Social Marketing in Action at T.H. March 5 Tips for Growing Your Business with Social Social Marketing in Action at T.H. March Oracle Modern Best Practice for Social Creates Real Business Opportunities Social marketing has existed as we know

More information

Driving Results with. Dynamic Creative Optimization

Driving Results with. Dynamic Creative Optimization Driving Results with Dynamic Creative Optimization Introduction In the world of digital advertising, reaching people is no longer the number one problem brands face when they plan a campaign. Ad networks

More information

BIG DATA FUNDAMENTALS

BIG DATA FUNDAMENTALS BIG DATA FUNDAMENTALS Timeframe Minimum of 30 hours Use the concepts of volume, velocity, variety, veracity and value to define big data Learning outcomes Critically evaluate the need for big data management

More information

Social Business Analytics

Social Business Analytics IBM Software Business Analytics Social Analytics Social Business Analytics Gaining business value from social media 2 Social Business Analytics Contents 2 Overview 3 Analytics as a competitive advantage

More information

Taking A Proactive Approach To Loyalty & Retention

Taking A Proactive Approach To Loyalty & Retention THE STATE OF Customer Analytics Taking A Proactive Approach To Loyalty & Retention By Kerry Doyle An Exclusive Research Report UBM TechWeb research conducted an online study of 339 marketing professionals

More information

Big Data. Fast Forward. Putting data to productive use

Big Data. Fast Forward. Putting data to productive use Big Data Putting data to productive use Fast Forward What is big data, and why should you care? Get familiar with big data terminology, technologies, and techniques. Getting started with big data to realize

More information

Case Study: Closing The Loop

Case Study: Closing The Loop Case Study: Closing The Loop Connect digital marketing data and offline sales data to get true ROI with this cost-effective approach to Customer Intelligence. As digital marketing techniques and technologies

More information

DEVELOP INSIGHT DRIVEN CUSTOMER EXPERIENCES USING BIG DATA AND ADAVANCED ANALYTICS

DEVELOP INSIGHT DRIVEN CUSTOMER EXPERIENCES USING BIG DATA AND ADAVANCED ANALYTICS DEVELOP INSIGHT DRIVEN CUSTOMER EXPERIENCES USING BIG DATA AND ADAVANCED ANALYTICS by Dave Nash and Mazen Ghalayini; Contributions by Valentin Grasparil This whitepaper is the second in a 3-part series

More information

Decisyon/Engage. Connecting you to the voice of the market. Contacts. www.decisyon.com

Decisyon/Engage. Connecting you to the voice of the market. Contacts. www.decisyon.com Connecting you to the voice of the market Contacts www.decisyon.com Corporate Headquarters 795 Folsom Street, 1st Floor San Francisco, CA 94107 1 844-329-3972 European Office Viale P. L. Nervi Directional

More information

Big Data: How can it enhance your strategy?

Big Data: How can it enhance your strategy? 7 Big Data: How can it enhance your strategy? Practice Area: IT Strategy Topic Area: Big Data Connecting the data dots for better strategic decisions Data is essential for organisations looking for answers

More information

Predicting & Preventing Banking Customer Churn by Unlocking Big Data

Predicting & Preventing Banking Customer Churn by Unlocking Big Data Predicting & Preventing Banking Customer Churn by Unlocking Big Data Making Sense of Big Data http://www.ngdata.com Predicting & Preventing Banking Customer Churn by Unlocking Big Data 1 Predicting & Preventing

More information

FIVE INDUSTRIES. Where Big Data Is Making a Difference

FIVE INDUSTRIES. Where Big Data Is Making a Difference FIVE INDUSTRIES Where Big Data Is Making a Difference To understand how Big Data can transform businesses, we have to understand its nature. Although there are numerous definitions of Big Data, many will

More information

Drive action at each stage of the customer life cycle OUTPUT SOLUTIONS FIT FOR THE ENTIRE CUSTOMER LIFE CYCLE

Drive action at each stage of the customer life cycle OUTPUT SOLUTIONS FIT FOR THE ENTIRE CUSTOMER LIFE CYCLE Solutions Overview OUTPUT SOLUTIONS FIT FOR THE ENTIRE CUSTOMER LIFE CYCLE Enhace one-to-one marketing Manage complexity Reduce costs Drive action at each stage of the customer life cycle with personalized

More information

OPTIMISING THE MULTI-CHANNEL AGENT DESKTOP: EMPOWER YOUR CUSTOMERS AND FRONTLINE EMPLOYEES

OPTIMISING THE MULTI-CHANNEL AGENT DESKTOP: EMPOWER YOUR CUSTOMERS AND FRONTLINE EMPLOYEES OPTIMISING THE MULTI-CHANNEL AGENT DESKTOP: EMPOWER YOUR CUSTOMERS AND FRONTLINE EMPLOYEES 2010 RightNow Technologies. All rights reserved. RightNow and RightNow logo are trademarks of RightNow Technologies

More information

Inside the Mobile Wallet: What It Means for Merchants and Card Issuers

Inside the Mobile Wallet: What It Means for Merchants and Card Issuers Inside the Mobile Wallet: What It Means for Merchants and Card Issuers Welcome to the age of Universal Commerce commerce that is integrated, personalized, secure, open, and smart. The lines between in-store

More information

BANKING ON WILL BIG DATA TRANSFORM THE CUSTOMER EXPERIENCE? A Retail Banking perspective

BANKING ON WILL BIG DATA TRANSFORM THE CUSTOMER EXPERIENCE? A Retail Banking perspective BANKING ON WILL BIG DATA TRANSFORM THE CUSTOMER EXPERIENCE? A Retail Banking perspective Big data provides an opportunity to deliver exceptional customer experiences and competitive advantage in an industry

More information

The Power of Personalizing the Customer Experience

The Power of Personalizing the Customer Experience The Power of Personalizing the Customer Experience Creating a Relevant Customer Experience from Real-Time, Cross-Channel Interaction WHITE PAPER SAS White Paper Table of Contents The Marketplace Today....1

More information

Driving Results with. Dynamic Creative

Driving Results with. Dynamic Creative Driving Results with Dynamic Creative Introduction In the world of digital advertising, reaching people is no longer the number one problem brands face when they plan a campaign. Ad networks and servers,

More information

CUSTOMER ENGAGEMENT 2014. Rosetta Consulting s Customer Engagement Survey Part 1: The Marketer s Perspective

CUSTOMER ENGAGEMENT 2014. Rosetta Consulting s Customer Engagement Survey Part 1: The Marketer s Perspective CUSTOMER ENGAGEMENT 2014 Rosetta Consulting s Customer Engagement Survey Part 1: The Marketer s Perspective WELCOME TO THE EMPOWERED AGE Welcome to the first in a series of three white papers on Customer

More information

The Big Deal about Big Data. Mike Skinner, CPA CISA CITP HORNE LLP

The Big Deal about Big Data. Mike Skinner, CPA CISA CITP HORNE LLP The Big Deal about Big Data Mike Skinner, CPA CISA CITP HORNE LLP Mike Skinner, CPA CISA CITP Senior Manager, IT Assurance & Risk Services HORNE LLP Focus areas: IT security & risk assessment IT governance,

More information

Predicting & Preventing Banking Customer Churn by Unlocking Big Data

Predicting & Preventing Banking Customer Churn by Unlocking Big Data Predicting & Preventing Banking Customer Churn by Unlocking Big Data Customer Churn: A Key Performance Indicator for Banks In 2012, 50% of customers, globally, either changed their banks or were planning

More information

Visa Consulting and Analytics

Visa Consulting and Analytics Visa Consulting and Analytics Issuer Acquirer Retailer Analytics and Information services: Issuer menu Issuers - Visa data driven insights We are in a unique position to inform our clients about performance

More information

6/10/2015. Chapter Nine Overview. Learning Outcomes. Opening Case: Twitter: A Social CRM Tool

6/10/2015. Chapter Nine Overview. Learning Outcomes. Opening Case: Twitter: A Social CRM Tool Opening Case: Twitter: A Social CRM Tool McGraw-Hill-Ryerson 2015 The McGraw-Hill Companies, All Rights Reserved Chapter Nine Overview SECTION 9.1 CRM FUNDAMENTALS Introduction Using Information to Drive

More information

www.green4solutions.com UNDERSTAND YOUR CUSTOMERS, GROW LOYALTY AND MAXIMISE REVENUES.

www.green4solutions.com UNDERSTAND YOUR CUSTOMERS, GROW LOYALTY AND MAXIMISE REVENUES. www.green4solutions.com UNDERSTAND YOUR CUSTOMERS, GROW LOYALTY AND MAXIMISE REVENUES. ABOUT GREEN 4 SOLUTIONS Customer Relationship Management experts for sport and leisure. Green 4 use knowledge, experience

More information

BIG DATA I N B A N K I N G

BIG DATA I N B A N K I N G $ BIG DATA IN BANKING Table of contents What is Big Data?... How data science creates value in Banking... Best practices for Banking. Case studies... 3 7 10 1. Fraud detection... 2. Contact center efficiency

More information

Creating Lasting Value With A Point-of-Sale Cash Program

Creating Lasting Value With A Point-of-Sale Cash Program Creating Lasting Value With A Point-of-Sale Cash Program Key insights of Discover Network Cash Over usage to build merchant loyalty and create differentiation A Discover Network White Paper for Merchants

More information

Current Challenges. Predictive Analytics: Answering the Age-Old Question, What Should We Do Next?

Current Challenges. Predictive Analytics: Answering the Age-Old Question, What Should We Do Next? Predictive Analytics: Answering the Age-Old Question, What Should We Do Next? Current Challenges As organizations strive to meet today s most pressing challenges, they are increasingly shifting to data-driven

More information

Customer Experience Management

Customer Experience Management Customer Experience Management 10 tips for the successful development and execution of Chris Bland Research Director SPA Future Thinking Introduction, sometimes referred to as Customer Feedback Programmes,

More information

Segmentation strategies for retailers

Segmentation strategies for retailers Segmentation strategies for retailers Leverage customer insights to drive profitable growth As retailers compete to drive foot traffic and grow share-of-wallet, what varies is how well each retailer understands

More information

Management Information and big data in Insurance

Management Information and big data in Insurance Management Information and big data in Insurance New drivers to create business opportunities Fabrice Ciais DUBLIN 24 th April 2013 2013 Towers Watson. All rights reserved. CONTENTS Contents Introductions

More information

BIG Data. An Introductory Overview. IT & Business Management Solutions

BIG Data. An Introductory Overview. IT & Business Management Solutions BIG Data An Introductory Overview IT & Business Management Solutions What is Big Data? Having been a dominating industry buzzword for the past few years, there is no contesting that Big Data is attracting

More information

Agenda Overview for Digital Commerce, 2015

Agenda Overview for Digital Commerce, 2015 G00270685 Agenda Overview for Digital Commerce, 2015 Published: 18 December 2014 Analyst(s): Jennifer Polk Marketing is making a greater impact on, and taking more responsibility for, digital commerce.

More information

At a recent industry conference, global

At a recent industry conference, global Harnessing Big Data to Improve Customer Service By Marty Tibbitts The goal is to apply analytics methods that move beyond customer satisfaction to nurturing customer loyalty by more deeply understanding

More information

Survey Says: Consumers Want Live Help

Survey Says: Consumers Want Live Help Session Abstracts Optimization Services Track Survey Says: Consumers Want Live Help October 22 nd, 11:00 am Eastern ATG recently surveyed more than 1,000 Internet users who research, apply for, and buy

More information

Leveraging Big Data and Customer Relationships. How Banks Can Benefit from the Mobile Wallet Opportunity

Leveraging Big Data and Customer Relationships. How Banks Can Benefit from the Mobile Wallet Opportunity Leveraging Big Data and Customer Relationships How Banks Can Benefit from the Mobile Wallet Opportunity Leveraging Big Data and Customer Relationships: How Banks Can Benefit from the Mobile Wallet Opportunity

More information

BUILDING LIFETIME VALUE WITH SEGMENTATION

BUILDING LIFETIME VALUE WITH SEGMENTATION PRESENTS DATA DRIVEN BRAND MARKETING PART ONE YOUR DEFINITIVE GUIDE TO BUILDING LIFETIME VALUE WITH SEGMENTATION WHAT YOU D KNOW IF WE COULD TALK TO YOU Proving the Value of Marketing 1 2 3 4 5 6 SEE YOUR

More information

The Top 10 Optimization Best Practices for Financial Services

The Top 10 Optimization Best Practices for Financial Services ebook: The Top 10 Optimization Best Practices for Financial Services a publication from Introduction Better Engage and Convert Website Visitors Financial services companies are facing a new challenge:

More information

Getting the most out of big data

Getting the most out of big data IBM Software White Paper Financial Services Getting the most out of big data How banks can gain fresh customer insight with new big data capabilities 2 Getting the most out of big data Banks thrive on

More information

Raising the Bar of Customer Loyalty Programs

Raising the Bar of Customer Loyalty Programs Raising the Bar of Customer Loyalty Programs Identifying Your Best Customers and Driving Their Most Profitable Behavior by Carlos Dunlap, Vice President, Strategic Services, Maritz Loyalty Marketing A

More information

Customer Lifecycle Management How Infogix Helps Enterprises Manage Opportunity and Risk throughout the Customer Lifecycle

Customer Lifecycle Management How Infogix Helps Enterprises Manage Opportunity and Risk throughout the Customer Lifecycle 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

More information

Adobe Analytics Premium Customer 360

Adobe Analytics Premium Customer 360 Adobe Analytics Premium: Customer 360 1 Adobe Analytics Premium Customer 360 Adobe Analytics 2 Adobe Analytics Premium: Customer 360 Adobe Analytics Premium: Customer 360 3 Get a holistic view of your

More information

A Comprehensive Data Management Platform Powers 360 Analytics. Centrally Analyze Audience, Campaign, and Performance Data

A Comprehensive Data Management Platform Powers 360 Analytics. Centrally Analyze Audience, Campaign, and Performance Data A Comprehensive Data Management Platform Powers 360 Analytics Centrally Analyze Audience, Campaign, and Performance Data 1 How can you analyze all of your disparate first-party and third-party audience,

More information

A CHASE PAYMENTECH WHITEPAPER. Building customer loyalty in a multi-channel world Creating an optimised approach for e-tailers

A CHASE PAYMENTECH WHITEPAPER. Building customer loyalty in a multi-channel world Creating an optimised approach for e-tailers A CHASE PAYMENTECH WHITEPAPER Building customer loyalty in a multi-channel world Creating an optimised approach for e-tailers Table Of Contents Changing shopping habits... 3 The multi-channel journey...

More information

Five Strategies to Build a Successful Email Marketing Campaign

Five Strategies to Build a Successful Email Marketing Campaign Five Strategies to Build a Successful Email Marketing Campaign David Daniels, CEO & Co-Founder - The Relevancy Group, LLC Christopher Nash, Senior Business Optimization Consultant Sitecore Reminders for

More information

TSYS Managed Services. Improve customer service, reduce costs and strengthen customer relationships through. Leverage best-in-class customer service

TSYS Managed Services. Improve customer service, reduce costs and strengthen customer relationships through. Leverage best-in-class customer service Solutions Overview Contact Center and Servicing Solutions Cost-effective, customized strategies Leverage best-in-class customer service Global, multi-lingual service models Improve customer service, reduce

More information

Past, present, and future Analytics at Loyalty NZ. V. Morder SUNZ 2014

Past, present, and future Analytics at Loyalty NZ. V. Morder SUNZ 2014 Past, present, and future Analytics at Loyalty NZ V. Morder SUNZ 2014 Contents Visions The undisputed customer loyalty experts To create, maintain and motivate loyal customers for our Participants Win

More information

Overcoming basket abandonment through effective implementation of real-time communications services.

Overcoming basket abandonment through effective implementation of real-time communications services. Overcoming basket abandonment through effective implementation of real-time communications services. The benefits of real-time customer engagement For the vast majority of online retailers, converting

More information

Improving customer relationships

Improving customer relationships White paper Customer Engagement Improving customer relationships How top companies maximize lifetime value through effective customer engagement Page 2 Customer experiences help drive long-term profits.

More information

> Cognizant Analytics for Banking & Financial Services Firms

> Cognizant Analytics for Banking & Financial Services Firms > Cognizant for Banking & Financial Services Firms Actionable insights help banks and financial services firms in digital transformation Challenges facing the industry Economic turmoil, demanding customers,

More information

The Future of Customer Engagement. Rusty Warner, Vice President Product Marketing Alterian

The Future of Customer Engagement. Rusty Warner, Vice President Product Marketing Alterian The Future of Customer Engagement Rusty Warner, Vice President Product Marketing Alterian The Future of Customer Engagement Where Is Marketing Headed? How Do We Get There? Who Is Doing it Right? What Happens

More information

FIS Active Analytics Suite. Delivering Segmentation-driven Digital Marketing, Merchant Offers

FIS Active Analytics Suite. Delivering Segmentation-driven Digital Marketing, Merchant Offers FIS Active Analytics Suite Delivering Segmentation-driven Digital Marketing, Merchant Offers Price Optimization and Risk Management Performance Analysis The FIS Active Analytics Suite helps financial institutions

More information

Banking On A Customer-Centric Approach To Data

Banking On A Customer-Centric Approach To Data Banking On A Customer-Centric Approach To Data Putting Content into Context to Enhance Customer Lifetime Value No matter which company they interact with, consumers today have far greater expectations

More information

Publish and Measure Phases

Publish and Measure Phases CHAPTER 7 Publish and Measure Phases 7. Measure 6. Publish 1. Plan 8. Optimize 2. Assess GOVERN 5. Build 4. Design 3. Define Anyone who has written anything or aspires to be writer knows that the word

More information

BIG DATA & ANALYTICS ACQUIRE, GROW & RETAIN CUSTOMERS: The Business Imperative for INSIDESSS. December 2013. Introduction Page 2

BIG DATA & ANALYTICS ACQUIRE, GROW & RETAIN CUSTOMERS: The Business Imperative for INSIDESSS. December 2013. Introduction Page 2 ACQUIRE, GROW & RETAIN CUSTOMERS: The Business Imperative for BIG DATA & ANALYTICS INSIDESSS Introduction Page 2 The Four Benefits Page 3 Make Your Business Big Data & Analytics Driven Page 4 Acquire Page

More information

Agenda Overview for Marketing Management, 2015

Agenda Overview for Marketing Management, 2015 G00270720 Agenda Overview for Marketing Management, 2015 Published: 18 December 2014 Analyst(s): Richard Fouts Increased participation in strategic business decisions and an evolving organization put new

More information

Driving Outstanding Post-Implementation Performance with Optimisation Services Transform Your Business With Salmon Ecommerce Services

Driving Outstanding Post-Implementation Performance with Optimisation Services Transform Your Business With Salmon Ecommerce Services Driving Outstanding Post-Implementation Performance with Optimisation Services Transform Your Business With Salmon Ecommerce Services www.salmon.com 1 DRIVING OUTSTANDING ECOMMERCE PERFORMANCE Over 25

More information

8 CRITICAL METRICS FOR MEASURING APP USER ENGAGEMENT

8 CRITICAL METRICS FOR MEASURING APP USER ENGAGEMENT 8 CRITICAL METRICS FOR MEASURING APP USER ENGAGEMENT Contents Measuring the Success of Your Mobile App...01 1. Users...04 2. Session Length...07 3. Session Interval...12 4. Time in App...15 5. Acquisitions...18

More information

Data Products and Services. The one-stop-shop for all your business-to-consumer data requirements

Data Products and Services. The one-stop-shop for all your business-to-consumer data requirements Data Products and Services The one-stop-shop for all your business-to-consumer data requirements Put data and insight back at the heart of your marketing Knowing who to target, when, via what channel and

More information

Deeper Customer Engagement Through Gamification and Gift Cards

Deeper Customer Engagement Through Gamification and Gift Cards Deeper Customer Engagement Through Gamification and Gift Cards By: Bret M. Esslinger Solution Consultant Richard D. Combs Solution Consultant 2013 First Data Corporation. All trademarks, service marks

More information

LOYALTY PROGRAMS: BUILDING CUSTOMER LOYALTY TO BUILD PROFITS

LOYALTY PROGRAMS: BUILDING CUSTOMER LOYALTY TO BUILD PROFITS LOYALTY PROGRAMS: BUILDING CUSTOMER LOYALTY TO BUILD PROFITS Loyalty is one of the great engines of business success. Frederick F. Reicheld, author of The Loyalty Effect Today s successful businesses recognize

More information

Grabbing Value from Big Data: The New Game Changer for Financial Services

Grabbing Value from Big Data: The New Game Changer for Financial Services Financial Services Grabbing Value from Big Data: The New Game Changer for Financial Services How financial services companies can harness the innovative power of big data 2 Grabbing Value from Big Data:

More information

Why is BIG Data Important?

Why is BIG Data Important? Why is BIG Data Important? March 2012 1 Why is BIG Data Important? A Navint Partners White Paper May 2012 Why is BIG Data Important? March 2012 2 What is Big Data? Big data is a term that refers to data

More information

Africa Regional Overview. An Overview of Our African Payment Services. www.tsys.com

Africa Regional Overview. An Overview of Our African Payment Services. www.tsys.com Africa Regional Overview connecting buyers and sellers An Overview of Our African Payment Services www.tsys.com Africa Regional Overview TSYS WORLDWIDE. Delivering expertise to 400 clients in 80 countries,

More information

Customer loyalty is hard to come by: Technology is the answer

Customer loyalty is hard to come by: Technology is the answer Customer loyalty is hard to come by: Technology is the answer CARD LINKED MARKETING Gone are the days when a customer would stay with the same bank for 20+ years, taking out mortgages, loans and making

More information

WHAT YOU D KNOW IF WE COULD TALK TO YOU

WHAT YOU D KNOW IF WE COULD TALK TO YOU PRESENTS DATA DRIVEN BRAND MARKETING PART TWO YOUR DEFINITIVE GUIDE TO FINDING THE CHANNELS THAT DRIVE THE BEST RESPONSE WHAT YOU D KNOW IF WE COULD TALK TO YOU 1. Building Value on Existing Segmentations

More information

Postgraduate Diploma in Digital Marketing. Awarded by University of California Irvine Extension

Postgraduate Diploma in Digital Marketing. Awarded by University of California Irvine Extension Postgraduate Diploma in Digital Marketing Awarded by University of California Irvine Extension 2 Accelerate your Career Improve Your Career Options with a Professional Postgraduate Diploma University of

More information

Torquex Customer Engagement Analytics. End to End View of Customer Interactions and Operational Insights

Torquex Customer Engagement Analytics. End to End View of Customer Interactions and Operational Insights Torquex Customer Engagement Analytics End to End View of Customer Interactions and Operational Insights Rob Witthoft Torquex {Pty) Ltd 10/1/2015 Torquex Customer Engagement Analytics Torquex Customer Engagement

More information

Generate More Sales & Maximize Your ROI!

Generate More Sales & Maximize Your ROI! Generate More Sales & Maximize Your ROI! AUTOMOTIVE MARKETING ebook 1 Generate More Sales & Maximize Your ROI! BY DREW PALMER FIND ME ON TWITTER @PALMERADAGENCY FIND ME ON LINKEDIN Drew Palmer has been

More information

4 Retail Marketing Challenges. (and how to rise above them)

4 Retail Marketing Challenges. (and how to rise above them) 4 Retail Marketing Challenges (and how to rise above them) 4 Retail Marketing Challenges Many retailers find themselves in a precarious position as they look to acquire and foster relationships with consumers.

More information

Telecommunications, Media, and Technology. Leveraging big data to optimize digital marketing

Telecommunications, Media, and Technology. Leveraging big data to optimize digital marketing Telecommunications, Media, and Technology Leveraging big data to optimize digital marketing Leveraging big data to optimize digital marketing 3 Leveraging big data to optimize digital marketing Given

More information

Adobe Campaign Guide to Loyalty Marketing in a Digital World

Adobe Campaign Guide to Loyalty Marketing in a Digital World Adobe Campaign Guide to Loyalty Marketing in a Digital World Increasing Customer Engagement and Lifetime Value 2013/2014 Table of contents 02 Introduction to Loyalty Marketing in a Digital World 04 Making

More information

A financial software company

A financial software company A financial software company Projecting USD10 million revenue lift with the IBM Netezza data warehouse appliance Overview The need A financial software company sought to analyze customer engagements to

More information

ANALYTICS: SHAPING THE RIGHT CUSTOMER EXPERIENCE

ANALYTICS: SHAPING THE RIGHT CUSTOMER EXPERIENCE EMV Technology: Deploying Soon in the U.S. ANALYTICS: SHAPING THE RIGHT CUSTOMER EXPERIENCE 2010 Mercator Advisory Group, Inc. Clock Tower Place, Suite 420 Maynard, MA 01754 phone: 1(781) 419-1700 e-mail:

More information