Keeping up with the competition was once a central issue that kept business-to-consumer (B2C) leaders awake at night. Not anymore. Now, the primary challenge retailers and brands face is keeping up with their own customers.
As technology evolves and consumers have unprecedented choice at their fingertips, their expectations aren’t confined to geographic, industry, or channel boundaries. Instead of comparing your customer experience to that of your competitors, today’s consumers are comparing it to the best customer experience they receive from anywhere at all.
That means they’re comparing you to experience leaders such as Amazon and Spotify — companies that harness exceptional customer experiences as a key brand differentiator. For example, Amazon’s short delivery windows set customer expectations for immediacy, even as it spans devices and locations to make its services accessible at all times.
What these platform-based companies also do is pay particularly close attention to customers’ needs as individuals. They collect and analyze data from them at every interaction so that they can deliver both online and in-person experiences that are fast, cost-effective, transparent, and above all, personalized.
In short, the basic building blocks of customer engagement have changed. In this new, wider playing field for retailers and brands, customers value emotional connections — and companies that aren’t focused solely on the moment of transaction. How a business responds to customers, and how it makes them feel, is key to cultivating brand love. In fact, 80% of customers say the experience a company provides is as important as its products and services.
So when it comes to locking in customer loyalty, what should B2C companies be doing now to keep up with their customers’ expectations and lead with experience?
The first step is to understand that what people really want from a personalized experience is to feel recognized and understood as an individual.
Research shows that consumers often feel overwhelmed by the endless choices they’re offered when shopping online. This can take a toll on decision-making. When consumers feel confronted by too many options, many irrelevant, they’re more likely to abandon the purchase and feel less satisfied.
To ensure this doesn’t happen, companies must move beyond the outdated personalization strategy of simply trying to predict which product a consumer might want to buy. Instead, the key is to determine why people choose a product. Are they a brand fanatic? Do they have unique needs for allergies or accessibility? Do they like buying a new sweater every winter, or pistachio-flavored ice cream every Saturday night?
True personalization succeeds when companies cater to the individual, making it easier for them to consume what they want, how and when they want it. If customers feel recognized in this way, and receive relevant recommendations, they are far more likely to make a purchase. In fact, 84% of customers say being treated like a person, not a number, is very important to winning their business.
As a second step, companies need a sound data management strategy. Meeting customers’ standards for personalized engagement starts with companies continuously capturing customer data in real time, then making this intelligence actionable. The process might involve installing sensors around a store, monitoring point-of-sale systems, analyzing web traffic to understand what items garner the most clicks, and more.
However, transforming this data into actionable insights and personalized experiences can be a real challenge for retailers and brands if they are not able to integrate their data sources effectively. Recent research shows that marketers rate real-time engagement as both their top priority and their top challenge.
A piecemeal approach to data management where specific capabilities are bolted on to solve channel-specific problems can result in data getting lost between systems, with valuable customer intelligence slipping between the cracks.
By contrast, if a company can integrate platforms so data sources are unified across the entire customer journey, they can avoid data gaps and blind spots and gain a more complete picture of individual customer’s desires.
With such an approach in place, companies can deploy artificial intelligence (AI) tools to deliver more personalized, contextualized, and precise customer experiences.
In today’s increasingly competitive environment where customer expectations continue to rise, we’re seeing leading retailers focus their attention not just on the check-out process, but also on the check-in — that is, what really matters at every stage of a customer’s interaction with a brand.
While there are many ‘moments that matter’ across any such interaction, certain moments are likely to have a more significant impact than others on a customer’s level of brand happiness. Accenture research highlights four of these: resolving a service or technical question; paying a bill; upgrading or changing a service or a device, and resolving a billing question or issue.
By focusing time and energy to provide a flexible, dynamic and personalized experience at such times, businesses can be more confident that they’ll gain their customers’ loyalty.
To further improve their capabilities as an experience leader, companies must ensure they deliver a consistent, continuous, omni-channel experience. Take the example of European men’s fashion brand Suitsupply, which has created a free-flowing experience for its customers, whether they are in-store or online.
If a customer wants to buy a suit online, they can use video chat to contact a stylist in one of Suitsupply’s customer service centers who will guide them through the measurements process. Aided by customer data (such as personal profile and browsing history) and smart learning systems, the stylist can also offer recommendations for complementary products. Alterations can be made at a Suitsupply storefront — or if there isn't one close by, the stylist can recommend a local tailor.
Suitsupply responds to customers in moments that matter with tailored recommendations, offers, and value-add services, based on data. Learn from their example by consolidating all the data gleaned from your customer interactions, then using AI-powered tools to process and deploy targeted solutions.
Providing a consistent cross-channel experience in this way is a key part of delivering on the personalization promise.
However, even as powerful AI-enabled tools enable companies to gain a thorough understanding of their unique needs and expectations based on rich data, digital trust is at a deficit. Sixty percent of the respondents in Edelman’s 2018 survey, for instance, say they don’t trust social media platforms to behave responsibly with user data.
This increasing distrust is a serious problem because if consumers choose to withhold their data from organizations, everyone loses. Gaining customer trust is critical — and to do so, businesses must deliver value. Research shows that customers are comfortable with companies using information about them in exchange for personalized engagement. They are also more willing to engage in a data-value exchange when companies demonstrate transparency and a commitment to protecting their data.
Businesses must therefore take the lead in educating customers about how they protect information, why they should be trusted with it, and what value the customer will receive in exchange for providing it. By crafting consumer-facing policies that emphasize a ‘democratization’ of data, where consumers have the same control over their data as the company does, businesses can differentiate themselves through a reputation for strong data privacy practices.
Building trust in this way is a vital part of delivering the one‑to‑one services and experiences customers are coming to expect, and that AI and other technologies can make possible.
Rob Garf is Vice-President of Industry Strategy and Insights for Retail at Salesforce. David Brown is Managing Director of Accenture Interactive.