Today’s retail environment is challenging from almost any perspective because of price pressure from discounters, market disruption from online players, and increased price transparency for shoppers. Traditional differentiation approaches in retail—such as a unique selection or strategic pricing and promotions—are not as effective as they once were, as competitors can easily imitate them. But differentiation is still possible through personalized approaches in which retailers create unique experiences tailored to individual customers.
Highly personalized customer experiences, when offered to millions of individual customers by using proprietary data, are difficult for competitors to imitate. When executed well, such experiences enable businesses not only to differentiate themselves but also to gain a sustainable competitive advantage. Moreover, our research has shown that personalized experiences drive up both customer loyalty and the top line.
Meeting customers’ expectations for a personalized experience
Thanks to online pioneers, such as Amazon, customers have grown to expect and desire personalized experiences: a survey of 1,000 US adults by Epsilon and GBH Insights found that the vast majority of respondents (80 percent) want personalization from retailers.
Personalization can even be called a “hygiene factor”: customers take it for granted, but if a retailer gets it wrong, customers may depart for a competitor.
Personalization, once limited mainly to targeted offers, now extends to the entire customer experience. This means that customers want personalization throughout their interactions with a retailer—with multiple, personalized touchpoints that enable them to allocate their time and money according to their preferences. In the best personalized experiences, retailers make the customer part of the dialogue and leverage data to create one-to-one personalization. Customers receive offers that are targeted not just at customers like them, with brands targeting at the segment level with broad-based offers, but at them as individuals, with products, offers, and communications that are uniquely relevant to them.
Understanding how personalization pays off
Given customers’ expectations, retailers must respond to the demand for personalized experiences not only to differentiate themselves but just to survive. When done right, though, personalization allows retailers to do more than merely survive: it enables them to thrive. Personalization at scale (in which companies have personal interactions with all or a large segment of their customers) often delivers a 1 to 2 percent lift in total sales for grocery companies and an even higher lift for other retailers, typically by driving up loyalty and share-of-wallet among already-loyal customers (for whom data are more abundant and response rates are higher). These programs can also reduce marketing and sales costs by around 10 to 20 percent.
Not only that, successful personalization programs yield more engaged customers and drive up the top line. In general, a positive customer experience is hugely meaningful to a retailer’s success: it yields 20 percent higher customer-satisfaction rates, a 10 to 15 percent boost in sales-conversion rates, and an increase in employee engagement of 20 to 30 percent. Customer-experience leaders in the retail space (retailers with consistently high customer-satisfaction scores) have provided their shareholders with returns that are three times higher than the returns generated by retailers with low customer-satisfaction scores.
To maximize the results of a personalization program, we recommend focusing initially on the most loyal customers, as programs targeting regular shoppers yield a return on investment three times higher than that of mass promotions. Moreover, building data on the most loyal customers sets off a virtuous cycle by generating ever-more-relevant data and higher response rates that further boost data quality.
Learning from success stories
Retailers across many different categories have managed to implement personalization at scale effectively and have significant success to show for the effort. Of course, Amazon has been a pioneer in this field, but other companies—including grocery companies, which make up for what they lack in e-commerce data with loyalty data from their physical stores—have moved into the top tier in recent years with successful personalization programs of their own.
Personalization pioneer: Amazon
As the ruler of large, pure-play, online retailers, Amazon has used sophisticated analytics to shape its personalization efforts. Over time, Amazon has expanded its personalization program to show customers products that are often purchased with the item they are viewing, display items that can be bundled with products in a customer’s cart, and recommend additional products in the e-mails it sends to confirm transactions.
Amazon continues to raise the personalization bar with ever-more-granular, -innovative offerings to individual customers. For example, Amazon Prime Wardrobe has recently launched a personal shopping service exclusively for Prime members. Customers complete a survey about their styles and fit preferences, and a team of stylists provides personalized recommendations from more than half a million items across brands. Amazon will probably continue to lead innovation in personalization, but other, smaller retailers—with far less sophisticated systems—are setting new standards, too.
Dynamic personalization: European grocer
A large European grocery company has successfully moved from one-size-fits-all marketing to personalized experiences. This shift began with research based on the retailer’s macrosegmentation; the retailer was then able to drill down a level further to create smaller segments based on location, time of day, and other specifics. From there, the grocer built a new transaction engine so it could institute business rules. For example, the engine does not offer discounts to regular shoppers who buy coffee or lunch at the store every day. Instead, it routes discounts toward other segments and users of the grocer’s smartphone app, who receive offers as they pass by the store.
The rich data from this grocer’s transaction engine, personalization engine, mobile app, and other tools have allowed the company to track sales across its entire network of locations—enabling the grocer to optimize for weather, day of the week, time of day, and similar data points that greatly enhance the effectiveness of promotions.
Omnichannel experience: Sephora
Sephora, an international beauty-products retailer, offers personalized experiences that are truly omnichannel in their presentation to consumers. The company’s digital channels—particularly its mobile app—encourage customers to book in-store makeovers and fashion consultations. The app’s “in-store companion” feature enables users to find a store, check to see if an item is in stock, and book a reservation. When customers choose to have their makeup done in stores, they receive a log-in for the app so that the makeup artist can input each product she or he used into the customer’s personal profile. The app also allows customers to virtually try on products and to receive recommendations based on their personal beauty traits. When customers visit a Sephora store, they can use the app to find the products they have virtually sampled.
All of Sephora’s customer communications—no matter the platform—display the customer’s loyalty points. Sales associates can see these point totals, too, and can access a customer’s profile in store. The profile includes data on the customer’s in-store purchases, online browsing and purchasing patterns, and interactions with in-store salespeople.
Sephora’s program is notable for another reason, too: it clearly demonstrates the effectiveness of focusing on the most loyal customers. The company’s tiered loyalty program, Beauty Insider, offers its highest-level members early access to new products, invitations to exclusive events, free custom beauty services, and more. All members receive customized recommendations based on profiles they fill out online. Their profile details—such as first name, buying habits, and quiz responses—are deployed across channels. Store associates can access a customer’s profile in the store and track items that were sampled, making it easy for customers to find and buy those items on the website or app. Every communication from the brand, on every platform, displays the customer’s loyalty points, and offers are synchronized across platforms.
The results of Sephora’s personalization efforts have been striking. The loyalty program now has around 25 million members. In 2018, members accounted for 80 percent of Sephora’s total transactions.
And for the third year in a row, with a score of 79 out of a possible 100, Sephora has claimed the top slot in Sailthru’s Retail Personalization Index.
In-store personalization: Nike
Not to be outdone in the personalization game is Nike, one of the largest athletic-footwear and athleisure companies in the world. Nike has taken personalization all the way to the individual product by allowing customers to configure their own clothes and shoes. The company recently launched a 3-D sneaker-customization platform that allows shoppers to generate real-time, shareable snapshots of finished footwear.
Personalization extends to Nike’s physical locations, too. Nike’s flagship store in New York City offers a compelling omnichannel shopping experience driven by membership in NikePlus, the company’s personalized loyalty program. Members receive personalized, exclusive benefits, such as access to Nike Speed Shop, which offers a data-driven, locally tailored assortment of “NYC favorites.” Members can also reserve items to be stored in pickup lockers and retrieve them by scanning their NikePlus member pass. With Nike Shop the Look, members can use QR-code-scanning to determine the availability of their preferred sizes and colors and to request delivery to their selected pickup location or dressing room. Using Instant Checkout, members can skip the cash-register line and check out directly from their own stored-payment device. Other benefits include access to Nike Expert Studio, where members can book personal, one-on-one appointments with Nike experts, and the opportunity to book appointments with Nike by You, where members can view a selection of silhouettes that are uniquely fitted to their specifications.
The necessary changes require a significant shift in the mindsets of employees so that they become comfortable with the experiments personalization requires.
Identifying common challenges for retailers
Given the success stories, it is little surprise that, in a Periscope by McKinsey survey of retailers attending World Retail Congress 2017, 95 percent of retail CEOs say personalizing the customer experience is a strategic priority for their companies. But that same survey showed that only 23 percent of consumers believe that retailers are doing a good job in their personalization efforts. What is behind this disparity?
First of all, most retailers are still in the early stages of their personalization efforts. Our research indicates that only 15 percent of retailers have fully implemented personalization strategies. More than 80 percent are still defining a personalization strategy or have begun pilot initiatives. The remaining retailers have decided to deprioritize personalization for now, for various reasons.
Retailers seem to be facing four main tactical challenges in getting personalization off the ground:
- Data management. More than two-thirds of survey respondents (67 percent) indicate that their greatest personalization challenge is the gathering, integration, and synthesis of customer data.
- Data analytics. Acquiring and maintaining in-house expertise in analytics and data science are proving to be major concerns for 48 percent of surveyed retailers.
- Alignment of retail organizations across functions. For many retailers, siloed processes and organizational models prevent the efficient and prompt sharing of customer data and promotion decisions (for example, difficulty in aligning the marketing and merchandizing teams). Of the survey group, 43 percent say these silos “make life difficult,” and 25 percent report that such silos make it difficult to get vendor funding—as well as buy-in—from suppliers for personalized offerings (especially in the grocery category). In many cases, these sorts of changes require a significant shift in the mindsets of employees so that they become comfortable with the test-and-learn and fast-fail experiments that personalization requires.
- Tools and technology enablement. Of the survey participants, 67 percent admit that they did not have the correct tools in place to execute personalization at scale. An additional 41 percent say finding the right solution partner was a struggle.
These challenges are further complicated by the fact that many retailers still operate under a hybrid, “bricks and clicks” strategy, making it even more difficult to implement the right levels of personalization in stores and online. Retailers with an omnichannel setup, however, have their own challenges, particularly in structuring offers and executing across communication touchpoints.
Overcoming the obstacles
All is not lost, however. As our previous case examples show, retailers across the spectrum have managed to create truly personalized experiences for both the online world and brick-and-mortar channels. The results for both the affected customers and the financial results are impressive. So how do these retailers do this?
There is no single winning recipe, as the breadth of our case examples shows. In our experience, though, an effective personalization operating model has four prongs: a data foundation, decisioning, design, and distribution (exhibit). Within this model are eight core elements.
First, all of these retailers have started small. They begin by testing and learning while building the necessary capabilities and multidimensional intelligence on customers over time. Data management is crucial here: getting the right data is much more important than gathering every last scrap of data. The customer database needs to be multidimensional, but it does not have to provide a 360-degree view of customers. Successful retailers start by gathering the most important data before scaling up to a broader understanding of each individual customer.
A detailed customer segmentation and analysis is the next common element. With the right data management and analytics in place, retailers can identify customers’ value triggers and then score and rank customers to facilitate effective targeting and personalization.
Developing a playbook of responses to certain triggers—such as abandoning a shopping cart and browsing of items that belong to a larger collection—is the third element. The goal here is to build a library of offers, with a few hundred as a good starting point. Some companies eventually build a large library of content that they can put together into a personalized magazine for customers. The right mix of triggers results in open and click-through rates that outperform those of traditional mass marketing.
The fourth element is a robust decisioning engine (campaign coordination) that plans experiences across multiple channels and reduces the risk of sending conflicting messages. It also allows retailers to drive the value created by each touchpoint and to maximize that value across the multichannel lineup.
An agile cross-functional team is the fifth element. A team room should be staffed by a cross-functional team—the engineers, merchandising professionals, and marketing experts should all be in one room. The team’s work should include weekly deployments implemented with a test-and-learn spirit more commonly found in the internet software betas of Google and other web giants. The goal of this cross-functional room is to break down organizational silos and to have mixed teams working together to increase pace and quality.
The sixth element of a successful personalization effort is securing the right talents, capabilities, and culture to staff the team. The leadership needs to set the right example at the outset, but from there, the program will touch everyone from the HR team to the marketing and merchandising staffs. The right mix of data scientists and marketing-technology experts is also necessary.
The right technology enablement can be complex to implement, but it forms the core—and the seventh element—of a successful personalization effort. Getting the various systems to work together and pull in the same direction can form the commercial heart of an organization. Most retailers are not maximizing the value that their existing technology platforms can offer, so unifying the systems will squeeze more value from them along the way. Building a more flexible platform on top of legacy systems is often beneficial, too.
Finally, retailers should undertake this effort with a test-and-learn approach. There is no need to build a vast, multivariable database as the first step. As the exhibit notes, do not wait for perfection. Instead, start small. Pick a straightforward experience that will generate a positive impact and start with that. Test the efficacy of that idea, generate useful metrics, and then expand to a second idea. Repeat. As the resulting impact is quantified, and the insights generated by experiments are funneled back to the team, the loop will be closed on the analytics powering each deployment.
In some retail sectors (the grocery sector, for example), collaboration with suppliers is important. The goal here is to build a mutually beneficial partnership with the supplier. To do so, shift funding from mass promotions to personalized experiences and give vendors full transparency into how their products perform. Additionally, provide each vendor with a point person who manages its relationship with the retail network. This person will quickly become a strategic partner who helps better align the retailer and supplier.
All eight elements humming in unison will form an effective personalized-experience engine that differentiates the retailer, increases share of wallet among the most loyal customers, and ultimately boosts the retailer’s top and bottom lines.
Given the potential impact of personalization, it makes sense that retailers would be eager to begin their personalization efforts. But how can they do that thoughtfully?
The first step is to define a short list of high-impact use cases that are relevant to the consumer but not too complex to execute against. A skilled cross-functional team can then be assembled to construct an integrated database for those use cases. The team should make sure that the data are both highly available and targeted while also considering the needs of future programs (including high-impact use cases). This database does not need to be perfect. Rather, it should be built through iteration, testing, and learning.
To begin building a personalization program—and to fuel its effective execution—retailers should create a cross-functional team to test and learn from experiments. Analytics and technology professionals will be critical to the program, especially when scaling it up. Finding the right external partner to help develop the personalization program is important, too, and will help accelerate the retailer’s progress toward results: a more personalized experience, greater customer loyalty, marked differentiation, increased wallet share, and substantially better top and bottom lines.