How Much Personalization is Enough?
The key to next-level personalization is better understanding — and acting on — the customer’s wants, needs, and goals.
Do you think your personalization efforts are “enough?”
Jeriad Zoghby, global lead for personalization at Accenture, doesn’t necessarily think so.
“We did a poll survey last year to ask customers what they thought of digital experiences. One of the more interesting findings was that 40 percent of customers have abandoned a site because they were overwhelmed,” says Jeriad in his presentation at Adobe Summit 2018.
The culprit, he explained, was an overabundance of choice that, ultimately, drives the customer to abandon their journey. “Too many products, too many options — digital can be a very overwhelming thing because people feel the burden of choice.”
“We checked again this year and that number went from 40 to 45,” says Jeriad. This is not to say that experiences are getting worse, but instead that customer expectations are rising. “If you’re a retailer, you’re not being compared to other retailers. You’re being compared to a car service and a hotel brand and a video streaming service. What we considered best in class — those best experiences — are creating more separation from everybody else.”
Rethinking personalization from the customer perspective
Kevin Lindsay, director of product marketing for Adobe Experience Manager, sees another root cause behind this trend that requires we dig in and rethink personalization from the outside in.
“Personalization has been focused on greedy motivations,” he says. “We’ve been trying to squeeze just a little more out of the conversion funnel or get a little bit more into the cart.”
While this focus on KPIs is important, Kevin says, “We need to start aspiring to a higher level of personalization, where we create experiences that are personal and make customers want to engage with and immerse themselves in a brand.” This, he says, is essential to building the kind of personalization that differentiates a company from its competitors. “There’s so much more that we could do, and not just from the standpoint of squeezing more dollars out of consumers, but really living up to this dream of us creating experiences that are really awesome and really personal.”
Achieving the customer experience “R’s”
How do you achieve this next-level personalization in your customer experiences?
It all starts by capturing key data points, and using that data to accomplish the “four R’s” in the customer experience funnel:
- Recognize the customer
- Remember their preferences
- Recommend ways to improve their experience
- Relevant decision-making on the customer side
It’s a streamlined approach that puts the customer in the driver’s seat — and there are countless ways for a brand to integrate this process, from personalized shopping, to curating merchandise at scale, to providing advisory services. Here are some real-world examples:
Personalized shopping. Imagine a grocery store where a shopper can enter the potato chip aisle and via an app or in-store screen search for chips that are not only low in salt but also gluten-free.
This is a method of personalized shopping that Jeriad is currently testing at Whole Foods Market. It’s more than just an opportunity to show off super cool, futuristic tech. It’s a compelling shopping experience because the customer can own their personal preference, rather than rely on a machine to decide what their preferences are for them.
The goal, Jeriad says, is to take this massive physical store and curate a single shopper’s experience to their wants and needs. This puts the shopper in control of their experience. Originally, Jeriad had aimed to use the data to predict everything the customer could possibly want or need. Now, though, he’s more focused on a conversational framework — a system where customers can “talk” to Whole Foods and share what they’re looking for or doing. The data from those conversations can then be delivered to the back end for further analysis and personalization opportunities.
From here the retailer can extend the “conversation” with a variety of actions — such as recommending an alternative product or sharing a targeted recipe with the shopper. This type of two-way communication between the customer filtering their preferences at the point of decision and the technology taking the opportunity to listen pays off in better experiences and better data.
“That’s where the data and analytics comes in to be very powerful,” Jeriad says. “Whether it’s through a mobile app, through augmented reality, whatever, start building a way for customers to talk back and forth [with you].” It will create the ideal personalized shopping experience.
Curating merchandise at scale. While simple customer demographics have long been the default to deliver relevant products to customers, utilizing this surface-level approach can lead to disconnected experiences. Just because a customer lives in a cold climate, for example, doesn’t mean he necessarily wants or needs a winter jacket. Continuously showing him heavy coats over and over will likely drive him away from your brand experience — and your brand.
That said, getting too specific can also be alienating. If a customer purchases a new shirt, the retailer can note the sale and track the specifics — the type of shirt or number of buttons on the shirt, for example. This information is very specific but isn’t likely to be indicative of why the customer made the purchase — just because you purchased a shirt with six buttons doesn’t mean you’re necessarily interested only in six-button shirts.
However, if a retailer can track both demographic and specific behavioral and order details, and from there consider the purchase occasion and buying motivation, the company can deliver better, more relevant customer experiences. This level of data personalization helps brands create a curated service experience that meets the very specific needs of individual customers. For example, a retailer can curate clothing recommendations for a customer based on the type of event she searches for or posts about on social media, or even self-selected fabric preferences.
This process of tracking, understanding, and curating data according to individual customer preferences and motivations can start well before a customer lands on your website or arrives at the point of sale.
Jeriad recommends that brands curate their shopping experience, starting with their marketing communications, all the way through the customer clicking to buy, to create an end-to-end personalized journey utilizing preferences directly from the customer.
Delivering expert advisory services. Online shoppers are no doubt familiar with phrases like, “Frequently bought together,” “Sponsored products related to this item,” and “Customers who bought this item also bought…”
These are all clear-cut examples of a recommendation approach to personalization, anchored in customer searches, buying habits of similar customers, and what the seller wants you to want.
Unfortunately, it makes for an unreliable, hit-and-miss buying experience.
Jeriad sees a point in the near future where brands will transition from unreliable recommendations to AI-driven expert advisers. “Think of this as… your concierge,” he says. “This is the tailor, this is the financial adviser that cannot only answer the questions I have, and advise me, but tell me why it was important and even think of questions I didn’t know to ask.”
Such technology would then have the potential to provide five-star service and advice to every customer, whether buying groceries or couture. “I might not be able to get [Giorgio] Armani’s personal advice [on what to wear], but what if we could model his actual advice that could be made accessible to me?” Jeriad says.
To achieve this, brands would need to combine data and pattern recognition with rules-based algorithms. This could eventually lead to enhanced chatbots that deliver targeted, expert advice to every customer.
“The feeding of the engine is really going to be dependent on machine learning and AI,” says Kevin. “That will enable that transition from just a recommender system to an advice system.”
Putting the “person” in personalization
AI-powered shopping is exciting to brands and consumers alike. With this technology, the entire customer journey can be personalized, with advice and merchandise catered to a buyer’s preferences and behaviors. However, the journey is simply steps to the ultimate goal of making the customer experience a more human experience.
“The key to delivering these human experiences is the ability to express empathy and say, ‘We want to understand what it’s like to be in your shoes today,’” says Kevin. “That’s the very definition of empathy. And the way to do that is to understand the customer’s motivation, their context — everything that’s surrounding them at this moment — to give them the best experience.”