Elevating customer experience with three essential data-driven keys

3 keys to success: Using data to build empathy, drive personalization, and enable scale

1. Empathy: Building deep and lasting relationships through emotion-based engagement

At the heart of every great experience is emotion. Customers want to feel like the brand knows who they are and understands their needs. This relevance is how the brand becomes an irreplaceable part of the customer’s life – not simply because of the products or services they offer but because the brand evokes a feeling within the user.

Take, for example, travel. The most successful airlines aren’t selling flights – they are building memories. The same is true of fashion: Clothing brands don’t just produce shirts and pants; they help people shape their image and live with confidence. Leading consumer products companies don’t pump out pantry staples, they offer ways for people to live healthy, sustainable lives.

Understanding the needs and desires of your customers to forge this emotional connection requires a combination of enterprise data (customer insights owned by the brand) and experience data (insights developed through a combination of third-party sources) to pinpoint the issues that matter and the moments when they matter most.

At the same time, it’s important to remember that feelings can be fleeting. What matters today may not resonate tomorrow. This means that companies also must continually design, refine, and optimize journeys to deliver a CX that aligns with the consumer’s changing worldview. While the brand promise and CX vision should remain stable, the channels, messages, timing, and tone are all subject to change based on the consumer’s emotional state and the events happening around them. This is why it’s so important to not only have a clear sense of what matters to each customer, but the ability to quickly act on new, timely insights when they will resonate most.

2. Personalization: Leveraging actionable data and measurement to connect on an individual level

Emotions are personal. So, if a brand wants to elicit an emotional response from a consumer, then they need to take a personalized approach, identifying when, where, how, and why to interact with each person at a given moment.

For example, some quick-serve restaurants are experimenting with using geolocation data – in combination with enterprise and experience data – to text message offers to people when they are in or near a physical location. Whether that text message is a valuable interaction or annoying interruption depends on how well the brand knows that particular customer and the degree to which they personalize the offer. By factoring in both enterprise data (favorite menu items, purchase history, ordering history) and experience data (time of day, trending menu items, motivations as a person), the brand can send hyper-personalized offers, tailoring each message so that it makes sense to the individual, be it a quick lunch option or a low-calorie snack before cycling class.

Brands could also take it a step further and proactively fill the need for customers. For example, if the QSR knows that a customer orders a specialty coffee every weekday morning on their way to work, but their geolocational data shows that the person is running behind schedule one day, then the brand can send a text asking if they’d like to place their usual order. On the other hand, when the brand sees that a person who normally visits a city location every weekday is on holiday, the company might send them a mid-day offer instead, urging them to pick up an afternoon treat from the local franchise on the way home from the beach.  

Hyper-personalization requires speed and agility to ensure the offer is timely and relevant. Companies should also assess performance continuously and track the impact of those offers on the business. This is critical to identifying which efforts should be scaled and which should be adapted or set aside.

3. Scalability: Using the customer technology platform to connect and scale

To offer personalized, emotion-based experiences at scale, companies need to take a platform approach. There are two separate, but equally important pieces at play: 1. An engagement platform, such as Salesforce; 2. A data platform, such as MuleSoft, to serve as the integration layer.

While Salesforce is an incredibly powerful tool, it must be powered by clean, accurate, timely, and complete data from across the business in order to unlock its full value. MuleSoft provides that critical integration layer, drawing data from other systems, including the ERP, and allowing companies to create a single way of interacting with the customer across sales, service, marketing, and commerce.

These two elements, when combined, provide the platform with scalability, allowing companies to maintain high levels of personalization even as they increase the volume of interactions. 

Finding value at the intersection of empathy, personalization, and scalability

While each of the three above elements is important to the overall success of the business, they only generate the most value for both the business and the customer when they intersect.

For example, a personalized interaction will often drive an emotional connection. But if there is no platform in place to enable companies to personalize at scale, then the value of those efforts will be limited, no matter how accurate the data and relevant the interactions may be.

Likewise, companies that have a robust integration layer may be drawing data from across the business, but if teams are using large customer segments to define their campaigns and send messages en masse, then these elements will lack the personalization – and, by extension, the emotional connection – to create real impact.

If you’re interested in finding out more, I’d love to explore with you how companies can unlock the value of their data in Salesforce with Capgemini. Drop me a message using the options below.