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Enabling Effective Loyalty Engagement in Retail

Delivering Value through Personalization
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Key Highlights
Monetary attributes of loyalty programs have become table stakes as shoppers aspire for higher levels of engagement with their loyalty programs
Across customer segments, the top three reward point redemption preferences are discounts on purchases (82.6 percent), rebates or cashbacks (72.1 percent), and personalized rewards, excluding personalized products (71.3 percent)
While a significant majority of retailers are increasing their marketing spend on social media channels, program members want to be notified only once in a quarter through this channel. The most preferred channel for frequent communication is e-mail, whereas most customers prefer not to be contacted by telephone

Overview

The broad trends seen in retail - customers' preferences for omni-channel engagement, convenient and personalized shopping experiences and the growing value consciousness - are driving retailers towards building resilient customer relationships that go beyond standalone transactions. Rewards programs, initially designed as a way to ensure a shopper's return to a store, can help achieve this objective by offering brand-specific transactional and behavioral data that can be mined for differential insights.

The number of U.S. retail loyalty memberships is estimated to have grown to 3.8 Billion in 2016. However, the actual engagement of shoppers with their reward programs presents a different picture altogether.

Over 42 percent shoppers subscribe to more than two rewards programs, but only 28.5 percent have used any of their programs to earn or redeem points in the last six months. Low customer engagement with rewards points thus deprives retailers of unique insights and loyalty-building opportunities.

WNS DecisionPoint™ surveyed over 1500 U.S. retail shoppers to study the utilization and satisfaction levels of their rewards programs. Segmenting shoppers across demographics into categories based on their behaviors and preferences, this report presents actionable insights on enhancing customer engagement within retail rewards programs. Key findings include:

  • Shoppers consider monetary parameters such as ease of earning and redemption, rewards per dollar spent, and rebates/cashback to be table stakes as far as rewards programs are concerned. Our analysis helps retailers identify non-monetary drivers of satisfaction to achieve differential gains in engagement
  • The key to personalization in rewards programs is acknowledging differences in shopper's attitudes towards program subscription, rewards earning and redemption, as well as preferred channels of engagement. In-depth behavior comparison across six shopper categories offers retailers tangible starting points for re-designing their rewards programs
  • Customers' propensity to shop across retail categories vary. Retailers that leverage this broad trend to enhance the performance of their loyalty programs will be best positioned to engage better with their customers
  • Like online shopping, the mobile channel is a fast-growing preference for customers to interact with their rewards programs. Insights into their dissatisfactions with this channel as well as the digital outreach cadence of rewards programs offer corrective approaches

As retailers enter an era of extreme personalization of the shopping experience, the loyalty rewards program deserves to reclaim its place as an important tool and enabler of the same. Advanced technology and analytics can offer retailers unique insights to redefine their branded rewards programs for higher engagement and satisfaction levels.

Introduction: State Of Retail And Loyalty

Our recent report, The Writing in the Aisle: What the 2016 US Holiday Season Tells Us About the Future of Retail, reveals the extent to which customers' spending has shifted to online channels. While e-commerce has had a record year, in-store sales growth was modest amidst significant decline in Year-on-Year (YoY) traffic (Exhibit 1). This decline can be partly explained by the proliferation of online channels in general and mobile in particular, as customers can shop with a single click and acquire greater visibility into pricing. As a result, retailers have been forced to increase markdowns in the form of discounts and promotions to lure shoppers. This is evidenced by the 45 percent increase in YoY markdowns during the 2016 Thanksgiving Weekendi. However, the hyper promotional, hyper competitive environment is affecting retailers' margins as customers become more value conscious and the bargain hunting behavior seems to only increase further. Retailers would be well-served to develop and nurture a more resilient relationship with the customer which goes beyond this pure deal-seeking shopping dynamic.

Loyalty programs, by their very nature, are the key to fostering a sustainable relationship. The 2017 Loyalty Census reports that the number of loyalty memberships in the United States (U.S.) was 3.8 Billion in 2016, a 15 percent increase from 3.3 Billion in 2014 (Exhibit 2). However, organizations have not been able to fully accrue the potential benefits from their loyalty programs, as only 46 percent of reported members, on an average, are transacting regularly with their loyalty programsii.

WNS DecisionPoint™ administered a Loyalty Engagement Survey covering 1509 respondents to analyze current membership levels in loyalty programs. Based on our survey, we see this lack of engagement playing out in retail as well. Eliminating the outliers, 42.4 percent of respondents subscribe to more than two loyalty programs, while for activity, measured by whether the respondent has utilized the program to earn or redeem points in the last six months, activity drops to 28.7 percent (Exhibit 3). This highlights a key issue with loyalty programs in general and retailer loyalty programs in particular - most of them are undifferentiated and underutilizediii. This is not surprising, since a typical reward is mainly in the form of either discounts, promotions and points which are redeemed as rebates. Hence, customers tend to interact with the program in a purely transactional manner. It would be in the interest of retailers to re-invent their loyalty programs so as to promote regular engagement and give customers a reason to come back to the store or the site and shop again. The idea is to create more personalized programs that amalgamate customers' transactional, behavioral (lifestyle), and product preferences. Integrating these multiple dimensions allows a retailer to make intelligent recommendations that match the preferences of the program members. This can lead to a greater inclination to shop at the retailer as engagement levels improve. It is the program member's perception of a mutually beneficial relationship that drives customer loyalty in a sustainable manner and maximizes the full potential of loyalty programs.

Current State Of Retail Loyalty Programs

Given the gaps in effective engagement, it is imperative for retailers to gain deeper insights into shoppers' perceptions and preferences with respect to loyalty programs. Loyalty programs typically achieve this through the following major mechanisms: first, they create a formal relationship with the customers, reducing their price sensitivity in the process; and second, an effective channel is established to leverage a program member's transactional and behavioral data, allowing retailers to tailor offers that are targeted to a specific customeriv. To measure the efficacy of loyalty programs, WNS DecisionPoint™ has improvised on various loyalty measurement models and inculcated both transactional and attitudinal dimensions to determine shoppers' perceptionsv. Our analysis identifies the utilization rate1 as an indicator of transactional loyalty, while the proportion of respondents with positive advocacy2 is considered a proxy for attitudinal loyalty. Based on these two dimensions, category-wise performance benchmarks reveal the variability in loyalty perception (Exhibit 4).

Our analysis shows that utilization rate by retail categories is linked to the nature of shoppers' purchases. For example, food and grocery retail loyalty programs such as Kroger's Rewards, Loblaw's PC Plus, Meijer's mPerks, and Wegman's Shoppers Club have the highest utilization rate at 67.8 percent, as groceries are the most often purchased product category. As per the Food Marketing Institute (FMI), a trade association of food retailers in the U.S., food and grocery supermarkets continue to remain the most preferred format for shopping of grocery itemsvi. Similarly, loyalty programs of big- box general merchandise retailers such as Walmart's 3-2-1 Save and Target's REDCard have the second highest utilization rate at 44.1 percent. But our analysis suggests that this has little correlation with the shopper's positive sentiment about the loyalty program. The number of respondents with positive advocacy for a loyalty program was the highest for upscale apparel stores (42.1 percent) such as Nordstrom and Neiman Marcus, as well as specialty apparel retailers (39.8 percent) such as Gap. This mismatch highlights the need for retailers to take a deeper look into the effectiveness of their loyalty programs, as for any given retail category, the maximum proportion of positive advocates is less than half.

Improving the efficacy of a program begins with developing an understanding of the program members' perception of various attributes. To enable this, we asked shoppers as part of our Loyalty Engagement Survey to assess the level of importance they assigned to specific attributes of their retail loyalty program and how satisfied they were with the same. Loyalty program members across retail categories also indicated that they see certain attributes having a higher degree of influence on their overall satisfaction vis-a`-vis others.

Program Attributes: Major Pain-Points And Drivers Of Satisfaction

Retailers are mistaken if they think focusing only on financial rewards will lead to greater brand affinity from customers. In Exhibit 5, we have taken the 13 key structural characteristics of loyalty programs and plotted the average importance as well as satisfaction scores for 1303 respondents (who subscribe to at least one retail loyalty program). Monetary attributes such as ease of redemption, ease of earning points, redemption value per point, rebates/cashbacks, and points earned per dollar spent are assigned the highest importance by shoppers. But as indicated by their high satisfaction scores, further focus on these is unlikely to yield much differentiation to the retailers. To identify the potential differentiators, WNS DecisionPoint™ looked at the combination of Importance and Satisfaction (IS) assigned to these attributes and highlight those with high importance but low satisfaction scores. Our IS analysis3 provides a more comprehensive and granular view of shoppers' perception towards loyalty program components. Based on the ranks derived from these IS scores, it is evident that shoppers aspire for higher levels of engagement with their loyalty programs which go beyond mere transactional interactions.

Respondents in our survey not only demand that their loyalty program reward them in a unique way but also expect the rewards to be customizable. To be able to deliver these benefits in line with the program member's expectations, leveraging insights from data has to be the central tenet of a retailer's loyalty strategy. And data should encompass not just purchase behavior metrics of the program members but their perception about the retail brand and the extent of advocacy exhibited as well. Based on a deeper understanding of constantly evolving customer expectations, retailers can deliver offers and communications that are targeted as well as relevant. This leads to more effective personalization. As a result, loyalty program members shop more frequently with the retailer and create value through incremental sales - a case in point being Walgreens, which sees 70 percent of total sales contributed by members of its loyalty program, Balance Rewardsvii.

Given this need for personalization, retailers who make coalition programs a key tenet of their strategy stand a greater chance of staying relevant as it enables a broader ecosystem of shopper engagementviii. This allows program members to not only earn points faster but also puts them in charge of their own personalization with more options to redeem awards as per their preferences. For example, members of Plenti, a coalition loyalty program operated by American Express (AmEx), can earn/redeem their points across sixteen brands such as Macy's, American Express, Rite Aid, Exxon Mobil, AT&T, Enterprise Rent-A-Car, Chili's and Expedia. Given this broad coverage, the program has become rapidly popular and now ~40 million customers are using itix.

Despite this evolution in the loyalty paradigm, retailers will have to still deliver on some basic aspects of the shopping experience. Loyalty program members expect higher priority service as compared to other customers. Our analysis sees this perception manifesting itself across in-store and online channels in a variety of forms. In the WNS Retail Holiday Survey, we highlighted that long waiting queues and slow speed of checkout are the top two inhibitors of in-store shopping. Retailers such as Walgreens have taken their cue from these in-store deterrents and integrated their loyalty program app with Apple and Android Pay. This allows program members to expedite the process of checkout much faster using dedicated Equinox payment terminalsx. To maintain consistency across online channels, many retailers such as Bed Bath & Beyond, Restoration Hardware amongst others are offering free shipping on online orders for test versions of their new loyalty programs. By charging an upfront membership fee, they are simultaneously leveraging the lock- in effect of members and ensuring balance between customer centricity and delivery economicsxi.

Loyalty Program Satisfaction: Determinants And Areas Of Improvement

Our survey identifies the significant scope retailers have to make improvements in loyalty programs, as only 23.6 percent of members are very satisfied with their most utilized program. In order to do so, retailers need to identify the key determinants of satisfaction. WNS DecisionPoint™ used a linear regression model to identify attributes having the highest level of significance in determining the overall satisfaction of program members:

  • Recognition as a valued customer
  • Ease of earning points
  • Ease of redeeming points
  • Customization of rewards to suit needs
  • Unique rewards
  • Broader ecosystem of alliances (e.g. airlines, hotels etc.)
  • Rebates/cashbacks
  • Real-time promotions based on past transactional records

Our analysis highlights that monetary features of a loyalty program such as ease of earning and redeeming points, rebates and cashbacks should serve as foundational attributes for retailers to improve related Customer Satisfaction (CSAT) scores (Exhibit 6). However, the proliferation of omnichannel ecosystem and shoppers' ability to stay constantly connected through mobile phones means that retailers should address attributes in the personalized (non- monetary) category to ensure their programs are the best in classxii.

In this context, retailers also need to identify the key improvement areas with respect to their loyalty programs. Our analysis points to two broad improvement areas for retailers: the utilitarian and the structural. Low relevance of promotions and fewer options to accrue/redeem points pertain to the utilitarian aspect, while the need to uncomplicate the structure of their loyalty programs and extend the expiry duration of loyalty points for consumers relate to the structural aspect.

One Program Does Not Fit All: Segments And Characteristics

WNS DecisionPoint™ compared retail loyalty programs across different categories and found they have the same structure - a frequency reward component, i.e. points earned per dollar spent by the program member, and a tier component, where users are segmented into tiers based on their shopping frequency. The rewards allocated to the program subscriber as well as the privileges vary for different tiers (see Appendix 1 to 7 for details).

Sine the programs have an undifferentiated structure in terms of demographics and preference, the rewards pushed to the program member in a given tier are the same. Thus, a 24-year-old Millennial working in Silicon Valley and a 73-year-old Baby Boomer who has retired will receive identical rewards. The current technology ecosystem, coupled with analytical advancements, allows for faster real-time data processing as well as outcomes with a significantly higher level of accuracy and relevance. This gives retailers the scope to move beyond plain vanilla rewards for loyalty programs and build a differentiated perception, which in turn would lift engagement levels.

Our analysis looks at the aforementioned structural attributes of loyalty programs and classifies the respondent set in our survey into distinct segments. It needs to be noted that the degree of importance assigned to these attributes, both monetary and non-monetary, shows significant variability across segments, as seen in Exhibit 7. In addition to these behavioral traits, we have also analyzed the segments based on their generational mix, channel preferences, program membership and activity levels. Specific archetypes were then assigned to these segments based on their distinguishing features.

In-store point-miners prefer to primarily shop inside stores, allocating 69 percent of their planned shopping budget (significantly higher compared to other segments). This inclination to shop in-store can be attributed to the presence of Seniors and Baby Boomers, who make up 60 percent of this archetype. The older the customer, the more likely is he/she to be a mono-channel in-store shopper. As we can see in Exhibit 7, there is near-exclusive importance attached to attributes concerning earning and redemption of points, i.e. highest points per dollar spent, ease of earning points, ease of redeeming points and redemption value per point. They deem non-monetary attributes to be almost irrelevant, as indicated by the importance assigned. This value maximization from a points perspective is also reflected in the program subscription and engagement levels of this cohort. While program membership per person is the highest across all segments (4.1), in-store point- miners tend to transact selectively with these programs, as indicated by 2.2 programs actively used per person. This cohort has indicated that they monitor their points balance most frequently amongst the different attributes of the loyalty program (Exhibit 8) and feel that their loyalty programs can pique their interest if the retailer increases the expiry period of the points and provides them with more options to earn and redeem them. A redemption centric card member is similar to the in-store point-miner in that both emphasize exclusively on the monetary aspect of their loyalty programs with an additional specific focus on redemption attributes, i.e. redemption value per point and rebates/cashbacks (Exhibit 7). This cohort consists mainly of Millennials and Gen Xers (70 percent). As seen in Exhibit 8, their planned budget allocation across different shopping channels is in line with average expectations. Given the emphasis on redemption, this cohort looks out for upcoming promotions as well as offers to maximize the value of the points that they are looking to redeem. The disparity between count of programs subscribed and actively used per person is much lower

Our analysis reveals that this cohort feels their loyalty programs can improve in multiple areas - simpler program structure, more options to accrue and redeem points, and promotions more relevant to them - indicating a higher level of overall dissatisfaction with the program (the second lowest proportion of respondents satisfied4 with their program, 66.7 percent). Experience seekers are a group of digitally engaged loyalty program members consisting primarily of a younger generational mix. Millennials and Gen Xers make up approximately 80 percent of this cohort. As the name suggests, this segment values a differentiating experience with a very high level of importance assigned to attributes related to personalization (Exhibit 7). More than two-thirds of this segment reported using the retailer's mobile app frequently to measure the performance of their loyalty programs.

Mobile/smart phones and tablets are regular purchase channels, as indicated by 19 percent spend allocation. This indicates a much higher level of mobile adoption and engagement compared to other archetypes. Given their continuous engagement across digital channels, this segment has very high expectations from their retail loyalty programs. The expectation matrix in Exhibit 8 indicates that they feel their retail loyalty program can provide them a better experience in all six areas despite the high levels of overall satisfaction. Unsurprisingly, more than half the respondents (51 percent) in this segment indicated that they track upcoming promotions and offers most regularly and demand personalization across multiple touchpoints. Therefore, while members of this segment subscribe to 3.9 programs on an average, they are actively using only 2.3 programs which meet their expectations from an experience perspective.

Channel agnostic point-seekers, as seen in Exhibit 7, have a behavioral emphasis on the monetary aspects of loyalty programs, i.e. ease of earning points, ease of redeeming points, and redemption value per point. While this behavioral pattern may seem similar to that of in-store point-miners, the spend allocation breakdown highlights their channel agnostic nature (Exhibit 8). Additionally, the generational mix is concentrated towards Baby Boomers (37 percent) and Gen Xers (33 percent). Given their channel agnostic nature, they are not too concerned about the expiry period of loyalty reward points; however, they expect retailers to provide them with more options to accrue or redeem points. Our analysis of satisfaction levels for this segment reveals that even though the proportion of satisfied respondents is the second highest at 73.6 percent, the proportion of very satisfied respondents is the second lowest at 21.2 percent.

Consummate demanders consist primarily of older Millennials and Gen X (69 percent). As we can see in Exhibit 7, this segment is the most demanding and assigns a high level of importance to almost all loyalty program attributes across monetary and non-monetary categories. Analysis of budget allocation across channels depicts a significantly higher focus on mobile (16 percent) as compared to other cohorts. However, the distribution of planned spend is even across online desktop and in-store channels, indicating a comprehensive multichannel approach to shopping. This multichannel focus results in constant engagement with the retailer's loyalty program and shapes expectations of members. They feel promotions can be more relevant with greater options to accrue/redeem points. But despite the high levels of expectations across all six attributes as visible in Exhibit 8, 77.2 percent of respondents in this segment are satisfied with their retail loyalty programs' performance. This is linked to their behavioral trait of only choosing the best programs and fully utilizing the ones they subscribe to. Average program membership per respondent is 3.8 while they transact regularly with only 3.1 of them.

Retailers that are keen to increase customer retention and lifetime loyalty must strive to provide their program members a seamless and engaging experience across channels as this segment is economically affluent, with more than half the respondents having an annual income in excess of USD 75,000. This affluence is visible in their status-conscious behavior, as a significantly higher 12 percent of respondents indicate that they frequently check their specific program tier.

Casual subscribers exhibit a high level of indifference to almost all attributes related to loyalty programs. Consisting primarily of older Baby Boomers and Seniors (69 percent), they display very low levels of program engagement and transact with only 1.9 loyalty programs on average, while subscribing to 2.9 loyalty programs. This low level of engagement is an indicator of their low program expectations across all attributes. Despite this, the proportion of satisfied respondents is the lowest across all the segments indicating a level of discontentment with their retail loyalty programs.

Points Accrual Strategy By Segments

In view of the different segments of loyalty program subscribers, retailers would do well to appreciate that these groups also vary in their approach to points accrual, redemptions and their personalization preferences. WNS DecisionPoint™ analyzed respondents' perceptions with respect to points accrual, initial trigger to join a retailer's loyalty program, mode of achieving the highest status in a program, and availability of various options to earn points across channels. Accrual Patterns follow a Broad Trend, with Minor Variations Exhibit 9 outlines the preferential rankings of various approaches to points accrual by individual archetypes. This provides retailers key insights on points accumulation. While minor variations do exist between groups, frequent, low value purchases is the most common approach to accrue points across segments. Additionally, the next three most preferred approaches to points accrual, i.e. promotions, using a co- branded credit card, and planned, large ticket purchases are common across all the archetypes of program subscribers, but the order varies by segments. Hence, retailers who focus on improving program engagement experience in these four key areas can address significant concerns their loyalty program subscribers have with respect to points accumulation. Our findings highlight the emergence of co-branded credit cards in the loyalty ecosystem given the win-win scenario for all the stakeholdersxiii. Shoppers' preference is tied to the fact that the use of a co-branded credit card allows them to earn discounts and cashbacks on purchases and simultaneously accumulate reward points even for purchases made outside the retailer's ecosystem. To earn optimal rewards, shoppers often modify their shopping cart and increase their net purchase leading to incremental revenue for the retailers.

Equal opportunities exist to earn points across channels but shoppers demand more. A majority of respondents report that their retail loyalty program allows them to earn equal points across channels for a given transaction. However, the actual proportion of respondents agreeing with the above varies between 44.1 and 57.2 percent (Exhibit 10). A significant percentage of respondents in our survey feel that on making a purchase via online channels, they earn no or less points vis-a`-vis in- store channels. Synchronization of incentives and rewards across channels encourage program members to engage with the retailer across a variety of touchpoints. On the contrary, if program members perceive that different channels deliver dissimilar experiences, they will decide to engage only partially with the retailer and display transactional loyalty to maximize their points balance.

Points Redemption Strategy By Segments

Contrary to points accrual, loyalty program members show major differences in their behavioral traits with respect to redemption of points and quantum of rewards for a particular transaction. Promotional offers and achieving a target points balance are the most common redemption triggers. Promotional offers are ubiquitous as one of the top two triggers to redeem points across all program member archetypes. However, the overall redemption behavior for each archetype is unique, as highlighted in Exhibit 11.

  • In-store point-miners prefer to make planned redemptions on achieving a target number of points in a given period (26.9 percent) or through promotional events (25.8 percent).
  • Both redemption centric card members and experience seekers prefer promotions but with differing intent. For a redemption centric card member, promotional events act as a key trigger to redeem points, but only after achieving a minimum threshold of reward points. An experience seeker prefers promotions given the relevant nature of the trigger.
  • Channel agnostic point-seekers have a significantly higher focus on redeeming after achieving a minimum threshold of points, while consummate demanders are most diverse in their redemption approach.

Higher proportion of program members feel redemption options are not equally available across channels. Less than half the program members in our respondent set believe that their program provides equal opportunities to redeem across channels, varying between 28.4 percent (experience seekers) and 42.5 percent (in-store point-miners). In fact, a majority of respondents in two program member archetypes, i.e. experience seekers and casual subscribers indicated that they have more options to redeem in-store than online. This difference in program members' perceptions regarding points accrual and redemption establishes a key conclusion - while program members have a broadly similar approach to accumulation of points, it is the redemption where significant variability exists in terms of preference. Retailers that are able to meet these differentiated expectations stand a greater chance to engage their program members more effectively and build lasting relationships that add more value for both stakeholdersxiv.

Engagement Enhancement Roadmap For Retailers

Retailers with mature loyalty programs and a sophisticated data analytics ecosystem can take a 360-degree approach to enhance personalization and consequently engagement levels. However, as established earlier, the main challenge lies around redemption of rewards given the variability in program members' choices. WNS DecisionPoint™ sees this redemption challenge as related to two specific issues. First, most customers in general and loyalty program members in particular shop across a variety of retail categories. Our analysis shows shoppers exhibiting specific buying patterns across retail categories. A majority of shoppers indicate that one of the four anchor categories, i.e. big-box retail, department stores, off-price and wholesale clubs or food and grocery retail is their first preference while making a purchase. For each of these anchor categories, shoppers indicated their second preference, i.e. the category of retailer they will visit next. Exhibit 13 documents these category propensity patterns based on the preferences of our survey respondents. For example, customers who shop at a big-box retailer have a significantly high propensity to shop at food and grocery retailers as well and vice- versa. We see this scenario as a function of overlap in assortments between these two categories as big-box retailers have widened their assortment to include groceries and perishables in addition to consumer-packaged goodsxv. This overlap in assortment has become so conspicuous that big-box retailers, such as Walmart, consider grocery to be a key driver of in-store traffic and traditional grocery retailers, such as Whole Foods, as direct competition. Similarly, shoppers who frequently visit a traditional department store often look out for complementary assortments in off-price and apparel retail, as they seek differential price points.

Second, seldom does a loyalty program member look at a particular type of reward in isolation (Exhibit 14). Therefore, while a majority of program members assume discounts, rebates and cashbacks to be table stakes, creating meaningful distinction requires offering more than generic deals. In fact, personalization is an omnipresent theme across various redemption options but there is noticeable difference in how program members want this experience to be delivered to them. The program members' preferences of various redemption options can be tiered into three levels. These tiers are based on the proportion of respondents who indicated a particular redemption as the most preferred. The top tier consists of monetary rewards such as discounts on purchases (82.6 percent), rebates or cashbacks (72.1 percent), and personalized rewards, excluding personalized products (71.3 percent). Only 50.4 percent and 47.9 percent of program members prefer free shipping and free/complimentary products respectively. As stated before, program members look at a particular redemption option in conjunction with various other redemption as well as personalization options. Based on psychographic data of loyalty program members, we have identified propensity to prefer subsequent personalization options for a given redemption preference. The relevance of personalization is highlighted by the fact that for three different types of redemption options, i.e. cashbacks, complimentary products and frequent flyer points, propensity for personalization is 71 percent. Therefore, if program members prefer either one of these redemption options, they have a high likelihood of expecting some level of personalization based on their past transactions. The confidence score of personalization options is conditional probability of a particular personalization option to be preferred given the program member has already decided the redemption option(s). As seen in Exhibit 14, the confidence scores of personalization options are tied to individual redemption preferences. While our analysis is specific to respondents in our Loyalty Engagement Survey, it provides retailers with a basic template to analyze the redemption preferences of their loyalty program members and how they can personalize the experience. For example, if a retail loyalty program member prefers rebates or cashbacks, there is significant propensity to expect free shipping as well. Retailers can cater to this expectation by providing program members with free shipping in case they are willing to make a threshold level of increment in their cart value. Additionally, such program members (who chose rebates or cashbacks) will also desire that option to be tailored according to their preferred categories/product baskets and the rebates be tied to exclusive events with members-only access.

The category propensities identified earlier have two parallel implications for a retailer, both related to the uptick seen in coalition programs. For retailers, it makes sense to adopt a strategy based on behavioral targeting. It enables them to identify and predict other retail categories their program members shop more frequently at. Hence, they can build an effective coalition loyalty program by establishing tie-ups with retailers that belong to those high propensity categories. At a more strategic level, it provides retailers with key insights with respect to program design. For instance, if they have a narrow assortment of categories, they would do well to focus on alliances and partnerships to leverage correlations in shopping patterns.

Improving Digital Engagement: Key Issues And Communication Cadence

The 2016 U.S. Holiday season saw e-commerce continue to make strides as it grew 17 percent YoY, versus 2.2 percent for in-store sales. In particular, m-commerce exhibited exponential growth, 44 percent YoY. This is primarily being driven by the speed and convenience of mobile shopping, as screen specifications improve and smartphone ownership grows. As per eMarketer, 78.7 percent of mobile phone users in North America owned a smartphone in 2016, forecasted to go up to 82.7 percent in 2020xvi. This has major implications for retailers. Three quarters of the loyalty program members in a recent Colloquy study prefer their smartphone as a point of accessxvii. Therefore, program members expect retailers to provide them with a mobile interface so that they can access details of their loyalty programs. However, 41.8 percent of loyalty program members who use a retail mobile app frequently expressed their dissatisfaction with the digital channel (Exhibit 15). The smartphone ecosystem, coupled with the data from loyalty program subscribers, provides retailers with a significant scope to both personalize offerings as well as resolve the issues outlined in Exhibit 15. However, low comfort levels of shoppers to share personal information presents a key roadblock for retailers to harness this dataxviii. We observed that concerns of shoppers are linked to six specific factors. We recommend specific action steps in Exhibit 16 that lead to greater predisposition amongst customers to share data, irrespective of whether they subscribe to a loyalty program or otherwise. Most significantly, customers expect retailers to communicate the value they will gain as well as the specific actions undertaken based on the data they share. While privacy incidents have been well documented, our analysis identifies that customers' concerns regarding the same are centered around specific issues - sharing data with third parties, assurance of having complete control over the information they want to share, and steps taken to safeguard information. Given the proliferation of data breaches, concerns over information security remain for customersxix. Retailers need to enhance their data security infrastructure and provide customers the option to control the level of information shared. This implies a need for retailers to tweak their mobile apps so that customers can customize privacy settings.

While the steps outlined in our report help retailers improve their existing and planned loyalty programs, maximizing the reach of the same necessitates a well-synchronized promotion strategy. Retailers employ various channels such as e-mails, direct mailers, social media amongst others to promote their loyalty programs to members and non- members alike, but we do not see them recognizing the differential nature of these channels from content as well as frequency perspective. This can become a major operational pain-point for retailers given a rapidly evolving omnichannel retail ecosystem. For example, loyalty program content for e-mail and mobile channels will vary due to the difference in dimensions between the two device categories. While e-mails will have more detailed content with a link to access the program online, content for mobile channels needs to be more concise, requiring retailers to ensure the website is mobile optimized with a link for downloading the app given the constraints related to data bandwidth. Our analysis of program communication channels delivers a few expected results as well as certain insights which retailers can leverage to enhance their promotion strategy. Most notably, while a significant majority of retailers are increasing their marketing spend on social media channels, program members want to be notified only once in a quarter through this channel.

Conclusion

Once a key differentiator, loyalty programs have become more or less table stakes in the retail ecosystem as evidenced by the increase in total membership but a noticeable fall in activity levels. Retailers that are able to leverage advancements in technology and analytics will be best positioned to re-differentiate their programs and achieve higher levels of engagement. They will have to provide their program members a differentiated experience across multiple touchpoints as physical and digital channels converge. With evolving customer expectations, the operational challenges to do so will become even more pronounced. The same digital revolution which brings challenges creates opportunities as well. Advancements in analytics and rewards delivery solutions are leading to new frontiers in personalization. As the retail sector shifts more and more towards online channels, customers will have more options to shop from at the click of a button. In this scenario, loyalty programs act as a key differentiator by driving higher levels of engagement. Retailers that stay ahead of the curve and deliver customized benefits to their program members will be best positioned to stay relevant.

Appendix

References:
i. Why Holiday Marketing Sparkled a Little Less Brightly in 2016, Retail Dive, January 2017.
ii. U.S. Customer Loyalty Program Memberships Reach Double Digit Growth at 3.8 Billion, 2017 Colloquy Loyalty Census Reports, Colloquy, June 2017.
iii. The Journey from Price to Value, From Prospects to Customers, Colloquy, February 2017.
iv. Loyalty Programs: Valuing "The Retention and Data Factory" , UBS, July 2016.
v. Customer Loyalty: Toward an Integrated Conceptual Framework, Dick, Alan S., and Kunal Basu, Journal of the Academy of Marketing Science, December 1994.
vi. U.S. Grocery Shopping Trends, 2016, FMI, August 2016.
vii. How Personalization is Driving Increased Loyalty for Walgreens, Total Retail, January 2017.
viii. For U.S. Retailers, Coalition Loyalty Programs Gaining Steam, Colloquy, September 2016.
ix. Plenti Coalition Loyalty Program Strikes Chord with Shoppers, Loyalty 360, December 2016.
x. Walgreens Integrates Rewards Program into Android Pay, Retail Dive, February 2017.
xi. Bed Bath & Beyond Pilots New Loyalty Program, PYMNTS, December 2016.
xii. What's the Point of Points? Debating the Future of Loyalty Programs, Loyalty Academy, May 2017.
xiii. Retail Stores with Credit Card Loyalty Incentives, The Balance, April 2017.
xiv. To Have a Killer Loyalty Program, Retailers Need to Think Big, eMarketer, September 2016.
xv. Target Unveils $7B Plan to Overhaul Stores, Retail Dive, March 2017.
xvi. Mobile Phone, Smartphone Usage Varies Globally, eMarketer, November 2016.
xvii. Want to Build Customer Loyalty? Smartphones are the Secret Weapon, Colloquy, March 2017.
xviii. Predicts 2017: Marketers, Expect the Unexpected, Gartner, November 2016.
xix. Four Keys to Cyber Security: Protecting Restaurants and Retailers From Data Breaches, Chain Store Age, March 2017.

 

 

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The Writing in the Aisle: What the 2016 US Holiday Season Tells Us About the Future of Retail
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The Writing in the Aisle: What the 2016 US Holiday Season Tells Us About th..

The Race to Omni-channel Heats Up as Shopper Dollars Return

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2016 US retail holiday season report
Reports

2016 US retail holiday season report

Stores matter, but omni-channel rules

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Winning the omni-channel retail race
Reports

Winning the omni-channel retail race

The true value of omni-channel retail

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