Build Better Retail Loyalty Programs With NoSQL

Build Better Retail Loyalty Programs With NoSQL

Posted on August 04, 2015 0 Comments
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“For retailers who lack the capability of using information about their card-holding customers and turning this data into tailor-made, individual, shopper-specific propositions – loyalty systems are no more than an expensive gadget.” 1

Build Better Retail Loyalty Programs With NoSQL

In my last post, Reinventing Loyalty Programs to Win, we discussed the fact that most loyalty programs in retail fail because they lack vision or provide “blind rewards.” While these un-targeted coupon and reward dispensing efforts provide only marginal benefits to consumers, the practices lead to significant costs for retailers. In this concluding post of my seven-part series, we will continue to discuss what it takes to effectively transform your loyalty program from cost to revenue generator.

One prevailing myth in retail is that you need a loyalty program at all. If you have an EDLP (Everyday Low Price) merchandising strategy, e.g., Aldi or Wal-Mart, or a premium segment-focused strategy, e.g., Whole Foods or Trader Joes, a loyalty program may not be a strong point of differentiation. Unless you have the capabilities to leverage loyalty program data to build lasting – and profitable – relationships with consumers, it may be time to cut your loyalty program.

There are three keys to successful loyalty programs: strategy, leveraging data to drive your business model, and making this operational or live.

I. Loyalty program strategy – getting it right

Successful retailers like Nordstrom and Kroger define their entire business model around building long-term customer relationships and enhancing your lifetime customer value. In other words, their strategy revolves around executing the promise made by the loyalty program to consumers. Key elements required for this include:

A. Establishing core metrics and a measurable business value proposition.At its minimum threshold a loyalty program must have metrics in place that help measure and execute operationally to:

– Increase customer retention

– Reduce attrition

– Recruit new customers

– Encourage higher spending

– Reduce ineffective marketing

B. Personalization.Consumers want to be treated like human beings and responded to as individuals. Segment your consumer base at an individual level and offer unique promotions and rewards based on past transactions, consumer demographics, geographic locations, and lifetime value. Whether at an “app”-level or loyalty card number, to have relevance,  you must be able to tailor your offers to the needs of the individual consumer. Linking the program to non-point-based rewards, like health and wellness rewards, will actually help you gain further credibility with consumers.

Case: CVS personalized coupons to loyalty card members

CVS tracks consumer purchase transactions on their loyalty cards and sends them customized rewards and coupons via email. By clicking the “send to card” link in the email, the targeted coupon will automatically come up when you scan your card or enter your phone number at checkout. CVS also alerts you when there are markdowns on products you regularly purchase. 2

C. Aspirational and the need to belong. Your reward program must create an aspirational desire in consumers to reach the next spending threshold. This change in level must ideally result in a change in status and create a desire to spend to at least maintain status or move to the next level. Airline programs have been doing this forever – but with the exception of a few retail programs, e.g., Nordstrom, which offers customized rewards like personal shoppers and free tailoring by level, most retail programs are pretty much plain vanilla.

D. Execution. Perhaps the oldest and most respected trait of a good retailer is recognizing loyal customers and treating them accordingly. That’s what made your corner shop owner so special – he knew who you were. Today most retailers really struggle with this. They fail to do what American Express does so well with its Green, Gold, Platinum and Black Card Programs, such as:

– Enable store staff to not just recognize valuable customers but act as relationship agents

– Ensure consistency of delivery and experience for target customers. Simply put, your Executive Platinum consumers fly or shop with you for the “upgrade” in service. If you don’t provide it they will switch

E. Omnichannel. Consumers want a consistent relationship and response across all brand touch-points online or in-store. Nothing irritates consumers more than not being able to earn rewards points or discounts online because your online and in-store systems don’t talk to each other.

II. Leveraging data for insights: are you using a muddled stack of applications that don’t talk to each other?

So, why can’t retailers execute on loyalty programs? Simply answer – because the quality of data underlying most loyalty programs is terrible. Problems include:

A. Data quality and currency. Consumer loyalty data often sits in multiple, diverse databases that don’t necessarily talk to each other. Perhaps the biggest obstacle facing omnichannel today is that consumer data in-store sits in a different database than online data (which may also be owned by a separate e-commerce division).

B. Integrating loyalty data with other sources of data. To see the entire picture on consumers, you’ve got to integrate your loyalty data with other useful sources of consumer data, including demographic, locational, purchase/transactions, panel data, digital and social, and store level data. Unfortunately, most consumer data does not just sit in multiple data sources and stores across the enterprise – it is also highly un-structured.

C. Limitations of traditional relational database management systems (RDBMSs). Retail systems largely utilize RDBMSs first developed in the 1970s and driven by Oracle, IBM DB2 and Microsoft. RDBMSs were just not designed for data complexity, rapid scale, and the easy integration of both structured and un-structured data. Using SQL (Structured Query Language) as the programming language for managing the data, in a RDBMS, structure is actually the primary difficulty with using type of database to store and manage content. Because in order for RDBMS to perform well, the data must first be mapped with a pre-defined schema, or set of constraints, that defines how it is structured and organized for analysis. Unfortunately, for industry users of RDBMS, loyalty data is not just vast and variable, it is also largely unstructured and does not fit neatly into the rigid rows and columns of this type of tabular system.

III. Your data needs to be operational or “live”

Most analytics today is done on batch data that may be over 24 hours old – if you’re lucky. Other sources of data, like syndicated data used to track sales, can be several weeks old. This is a problem because today’s consumers need to be responded to individually and live at the point of purchase in-store or online. Take the case of Jen Dough and Joanne Deogh, both 30 years old and living in the same apartment building. Joanne is single while Jen is a married, new mother. If your loyalty database was not updated to capture Jen’s unique new status as a parent, these women are not likely to be offered personalized, differentiated promotions at the point of purchase – and you are not likely to succeed in your marketing efforts.

The NoSQL Value Proposition for Loyalty Programs

These data disconnects have created a need for a more flexible and scalable database that can easily manage the complexity and scale of data associated with your loyalty program. Traditional mainframe or RDBMSs lack the flexibility and scalability to handle the volume, velocity, and variability of data inherent to a consumer loyalty program. NoSQL (Not Only Structured Query Language) technology represents a transformational change in data management. Instead of needing to get the schema just right before doing anything else, NoSQL advocates loading up the data first and then seeing where the problems lie. This problem-oriented approach focuses on how the data will be used (queried) rather than how the data must be structured to fit within a traditional RDBMS. Radical, huh?

Why Build Your Loyalty Program on MarkLogic? 

In a nutshell, MarkLogic offers some key differentiators for your loyalty program database, including:

  • The Only Enterprise NoSQL DatabaseFirstly, and perhaps most importantly, we’re talking about consumer loyalty data in your database. The retail industry has been plagued by recent data breaches at Target, TJ Maxx and many other retailers. This weakness stems from the inability to handle huge volumes of data while ensuring transaction integrity and security. Most open-source vendors fail at just this crucial requirement. MarkLogic’s platform was designed to be enterprise-ready from day one – which means that it has the government-grade security, high availability, disaster recovery and transactional consistency you need for your mission-critical consumer applications.
  • A Superior Operational Data WarehouseAn effective loyalty program calls for real-time, operational capabilities. You need to recognize and respond correctly and accurately to Jane Doe the moment she enters your brick-and-mortar or online store. Making the right product and promotional recommendations to her is what will close the deal. Simply put – your data warehouse must be transactional and operational to enable websites, e-commerce and in-store applications while at the same time enabling analytics and storage of terabytes – maybe even petabytes – of data. MarkLogic was the only NoSQL database appointed to Gartner Leaders Quadrant for Operational Database Management Systems. Also, in the 2014 Gartner Report: Critical Capabilities for Data Warehouse Database Management Systems, MarkLogic came out ahead of all other vendors in the customer rating for Operational Data Warehouses.
  • Application Services for Consumer AnalyticsFor a loyalty program to yield results you’ll need to build the right applications on top of the data. MarkLogic’s integrated HTTP server has full-featured Java and REST APIs, among many others, to make managing data and building two and three-tiered applications easy. This empowers your developers to develop faster by using the language they know.

To summarize, if you’re considering re-inventing your retail loyalty program to its best advantage, be sure to build it on an agile, powerful and secure data platform you can trust to meet your data requirements today and tomorrow – MarkLogic.

Please be sure to read my other articles in this series:

1. Big Data, Little Insight: Challenges for the Retail and Consumer Industries

2. Removing Roadblocks to Omnichannel 360 in Retail

3. Consumer 360: Reaching Each Consumer With a One-in-a-Billion Message

4. Retailers: Are You Meeting the Needs of Digital Consumers

5. Why do Retailers Miss Out on E-Commerce Opportunities?

6. Reinventing Your Retail Loyalty Program to Win

7. Build Better Retail Loyalty Programs With NoSQL

Sources:1. Forbes Magazine, Harvard Business School, Working Knowledge Paper 20142.

Donald Soares

View all posts from Donald Soares on the Progress blog. Connect with us about all things application development and deployment, data integration and digital business.


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