Retail's Best Brand Loyalty Program (By Valentyn Kropov, SoftServe; excerpted from RETAIL IT)
Customers exchange personal information expecting a high return on involvement. The onus is therefore on brands to use gathered data to discover what customers value, and to then deliver authentic, personalized experiences and rewards to the customer throughout the buyer’s journey. True customer intimacy comes from engaging in a sustainable and mutually valuable relationship.
Brands Run on Loyalty—And Data
Establishing loyalty programs drives increased interaction, establishes trust, develops relationships, and creates a space for conversation. It also provides a means of collecting high quality data. This dialogue results in the creation of both personas and preferences per customer.
To create a successful loyalty program, a business needs to not only collect data, but to analyze it. Buyer behavior should then be cross-referenced with demographic data to fully understand the customer. A strong personalization strategy delivers not just what customers want but addresses their preferences for how and why.
Giving Quality to Get Quality Data
Sophisticated technologies use artificial intelligence and machine learning to glean top insights from customers, creating more nuanced profiles and deliver higher quality, higher value rewards. Simply put, the better the ability for brands to provide quality benefits, the better the information (and loyalty) they can expect from customers.
Whether optimizing an existing loyalty program or creating a new one, businesses should look at the following areas:
System Complexity
High value loyalty programs require systems capable of analyzing Big Data. Without quality data to inform personalization, loyalty programs are destined to live in generic mediocrity. Meeting the customer where and when she is in the buyer’s journey and delivering what she needs or wants requires leveraging their data with artificial intelligence and machine learning. This allows businesses to not only find the correlations between recommendations and purchases (e.g. recommending socks post-shoe purchase) but allows them to do so in a fraction of the time it would take to do manually. AI and ML also unlock hidden insights by analyzing Big Data over time to unveil trends and behaviors never before considered.
The type of data collected is also somewhat dependent on whether the loyalty program is web-based or card-based. Web-based loyalty management software will capture data about website behavior, or purchase details when the brand is mentioned on social media. Card-based systems gather a narrower set of data, such as buying behavior and demographics, though some retailers invest in gathering augmented data through loyalty software. A combination of these two systems will not only give members more interaction options but offer businesses more data points for the clearest picture of customers—both individually and overall—to offer better value.
Omnichannel
Omnichannel integration is emerging as an essential component in loyalty program implementation. It is not enough to track purchases in-store and online. For true customer intimacy, retailers must understand behavior and purchase patterns across all touch points and address these insights within their loyalty programs. Executing omni-channel loyalty can be a streamlined mobile point of sale process, an interactive online experience that boosts customer engagement, or incentives to visit brick-and-mortar for a tactile experience.
Ease of Use
Customer experience is synonymous with brand. If a loyalty program is too difficult to navigate or too complex to understand, the brand will be seen as out-of-touch or obsolete, and customers will take their loyalty—and their dollars—elsewhere. Ease of use is therefore a primary component of effective loyalty programs. Creating an engaging and highly relevant experience starts with design thinking. This methodology focuses on the customer—developing a deep understanding of their mindset, walking through each step of their journey, and building the program to meet needs as they arise. Once a program is conceptualized, quick prototyping and testing ensures the experience—and the brand—delivers value.
Trending Components for Better Engagement
Today’s on-demand customer expects more for his or her attention. Let’s take a look at some of the hottest trends for 2019:
Mobile Wallets
Integrating mobile wallets into loyalty apps is the next big step for retailers. The mobile wallet feature on the Starbucks app is a prime example of this in action—customers put money into their app accounts and are able to pay with codes displayed on a phone.
For the retailer, this not only means increased revenue and loyalty, but also data. The digital wallet can collect multiple data points at the time of purchase, from the customer, the time, the place, the product, the value, and so much more. This information can then feed into different personalization points that fuel the loyalty program and make it more robust and ultimately, successful.
Mobile wallets also enable several other perks for both consumers and retailers, including:
Better customer experience – Mobile wallets put convenience at the forefront of the customer experience. Paying through a smartphone boosts better payment management, personalized offers, and alerts from the retailer. Digital wallets are surprisingly easy to maintain and compatible with most e-commerce sites.
Lower costs – Mobile wallets send personalized promotions to target customers directly, after they have already interacted with the brand. As such, the brand saves money by refraining from introductory offers and meeting the customer more directly with what she wants.
Increased security – Protecting transactions and financial information is paramount for any financial function, and digital wallets are strongly supported with layers of extra security to keep transactions safe. Data is encrypted so that account information is protected, and mobile wallets require authorization, either through a PIN or a fingerprint.
Blockchain
Blockchain has evolved beyond finance applications—and loyalty programs have significant room to grow using this technology. A structure that stacks data (block-by-block) for transparency, blockchain is virtually immutable, extremely difficult to hack, and acts as a distributed ledger for transactions. Key benefits include:
Increased accuracy – Blockchain technology provides an immutable database that monitors and archives each transactional record. This not only keeps data secure but protects it from tampering and fraud. Retailers that can manage customer data securely and transparently establish better trust and longevity with customers.
Increased flexibility – Blockchain points can be cashed out from retailers that opt to use it. Enterprises also can use blockchain across different chains for flexible rewards that transfer from individual shop to individual shop, providing better value for customers.
Cryptocurrency – Blockchain allows retailers to reward customers with cryptocurrency—whether their own (proprietary) or a cryptocurrency recognized in the market (e.g. Bitcoin). For instance, rewarding customers with increments of cryptocurrency can be seen by the customer as more valuable than simply earning points. Cryptocurrency can then be either cashed out or stored in a mobile wallet. And since cryptocurrency has value that cashes out, shoppers are encouraged to purchase more to get more “cash back” in.
Artificial Intelligence
Artificial intelligence (AI) is critical to a successful loyalty program. AI powers personalization by taking data, analyzing it for actionable insights, and then meeting those needs. Let’s take a look at some examples of AI in the market.
Sephora
Sephora’s Beauty Insider program is a gold-star loyalty program: it keeps customers engaged, uses a tiered system to encourage multiple purchases, and leverages sophisticated technology that allows the brand to speak to its customers’ needs and desires.
A few years ago, Sephora created its own innovation lab to explore AI and its potential role in the business. The lab incorporated natural language processing, machine learning, and computer vision to address online and in-store purchases. In doing so, Sephora created multiple touchpoints for gathering data through features their customers seek out— delivering value to both the customer and the business.
Sephora’s Beauty Insider program runs on data. From customer purchases to opt-ins from Sephora’s various apps, the program gives members one point to match every dollar spent. These points are redeemable for Sephora’s many products, in a range of different prices. The Beauty Insider’s tiered system allows those more interested in white-glove treatment to pay a fee for more intimate personalization and higher-level experiences. Points are redeemable both online and in-store for a seamless omni-channel experience, and tracked through the brand’s integrated systems across mobile, online, and in-store. Sephora also offers additional personalized perks for their most loyal customers—based on the data from their purchases and interaction with the brand at every level.
Starbucks
Starbucks was one of the first retailers to offer mobile payment through the Starbucks app—a revolutionary idea when it launched in 2011. Running the program, My Starbucks Rewards, through the Starbucks app makes usage incredibly easy. To earn loyalty points, customers must add cash to their accounts and then order or pay with the Starbucks app. By combining payment and mobile data, customer transactions offer up a significant amount of data points surrounding customer preferences and behavior.
Preferred drink orders, customer lifetime value, favorite locations, and more can all be analyzed through the app. This tells the business about its customers, empowering Starbucks with actionable insights to reach each customer directly with better benefits and more direct communication.
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