What Sets Them Apart: How Industry Leaders Connect with Customers

Michael Jordan has a famous quote, “To be the best, you have to learn from the best.” 

Talk to any expert in their field, and they’ll share how they got to where they are today by learning from others. I’ve heard countless C-level executives say it’s not about being the smartest person in the room, but surrounding yourself with the smartest people. 

In hosting the podcast, Good Data, Better Marketing, I’ve been fortunate to gain so much wisdom from people who are phenomenal in their fields– whether it’s scaling business operations from the ground up, or creating one of the most recognizable brand personalities in retail.  

Below, I’ve highlighted a few takeaways from conversations I’ve had with Marketing, Customer Experience, and Data leaders, to share the lessons they’ve learned throughout their careers. 

1. Anthropologie: Connect data and emotion

Anthropologie is known for their in-store ambiance – from elaborate window installations to the finer details of their interior design. 

For Elizabeth Pries, the Chief Marketing Officer at Anthropologie, being able to create a connecting thread between these two touchpoints is crucial. As she said, “How can we take that same emotional connection people find with the brand when they come into the store, and bring that over to the digital space?” 

Of course, it will never be a one-to-one translation. Online, you can’t feel the fabric of the clothing or smell the fragrance of a candle. But you can still have an experience that’s wonderful and unique. One thing that Anthropologie does is use ratings and reviews to help write product copy with more nuance and a customer-centric perspective. 

Another example is how Anthropologie leverages data on items that are commonly bought together. By sharing this knowledge with in-store stylists, they can better recommend head-to-toe looks for individual shoppers, or know which items would be best showcased throughout the store on mannequins.  

In short, they’re using online data to inform offline experiences, and vice versa. 

As Preis said, “All those data points are very actionable elements that we can use in our marketing programming. But the bigger challenge for marketers today is understanding and reading the data, and then synthesizing it so it becomes actionable for others. That is where the real value comes in. It's almost like one can learn to read and write, but that doesn't mean they can write poetry.”

For Anthropologie, this combination of analytics and empathy is what enriches the customer experience, and makes their brand so distinct. 

2. AppFolio: Remember the only constant is change

The most fundamental step in your data strategy also happens to be the most complicated: aggregating all your data into a single system. 

Guneet Singh, Vice President of Customer Experience and Care at AppFolio, knows this well. Building data pipelines between different systems is no small feat, but it’s the basic work companies must do. This is what allows you to answer essential questions about the customer experience (like, why are people reaching out to customer support? What patterns point to friction in the user experience?) 

As Guneet explained, understanding the customer experience is not a historical question, but, “a question that should be in front of your screen every morning.” That means empowering every team with up-to-date, unified data and analytics to understand the ever-evolving nature of customer journeys. 

And while change is inevitable, businesses need to understand the value of timeliness in their day-to-day operations. We know we’re working with a moving target, so it’s how quickly we adapt and respond that matters. 

Here’s where AI can help. AI is able to mine incredible amounts of data in incredibly short periods of time. AppFolio is using AI in this way to, “level the playing field for knowledge,” with their customer support agents. By using AI-powered bots, customer support can rapidly retrieve the information they’re looking for to problem-solve as quickly as possible – which can mean a world of difference when it comes to customer satisfaction. 

Of course, human validation is paramount to ensure the AI tools are as helpful as possible. Companies should regularly go back to the drawing board and ask if they’re still applying AI in the most strategic ways, especially as the product evolves and becomes more complex. 

This sentiment, of leveraging AI with human insight and intuition, is something shared by several guests on the podcast, such as Glenn Vanderlinden of Human37. 

3. Human37: Adapt in real time

We don’t need to be reminded of the instantaneous nature of today’s world. Attention spans are getting shorter, and survey after survey tells us that immediacy is a key part of the customer experience. So, how do you take advantage of the opportunities that exist moment to moment? 

Human37 – an agency focused on customer data strategy – is doing just that by focusing on real-time data activation.  One example of this is with their client in the sports event industry. They offer a mobile app to customers that includes a digital wallet. Using real-time data, they can see if there will be leftover food at an event, and they’re able to send a notification to users via their app to receive a discount on food purchases.  

“At the same time, we're doing two things. One, we're making sure that we don't waste food. Two, it allows us to experiment with couponing. Can we activate people to try new things?” says Glenn Vanderlinden, Co-founder and Lead Solution Architect at Human37.

Another real-time use case that Human37 is implementing is onboarding customers onto the ticket resale market for sports events. For example, if a user has season tickets but hasn’t shown up to a game for a specific amount of time, the app can show them how to resell their tickets. This prevents the event organizer from losing out on extra profits from merchandise or concessions while the user gets to make some money.

While Vanderlinden believes such use cases open doors to AI applications, he warns against moving too fast without having the foundations in place. By skipping that step, organizations risk using the wrong data to engage their customers and missing the mark on their campaigns. “And since it’s AI and automated, you’re doing it wrong at scale.”

Connecting customer data

If there’s one thing I’ve learned from these conversations, it’s that it’s not as cut-and-dried as having the data and then knowing exactly what to do with it. 

Even though AI is promising to revolutionize the way we work (and the speed at which we do it), you still need to draw on your experiences and empathy as a human being to make a connection with customers. Data can certainly lead you in the right direction, as long as  you’re able to thoughtfully analyze it. 

To browse more conversations with Marketing and Analytics leaders, take a look at our Good Data, Better Marketing podcast.