How the 1st customer-facing employee @ Loom predicts the future of CX [2/2]

Susana was early at not 1 but 2 rocketships (Airbnb & Loom). At Loom, she built their customer experience (CX) team from scratch. These days, she advises founders on building CX functions.

This is the second of a two-part post with Susana, author of signed ✍️, a newsletter focused on CX (opportunities, leader interviews, hiring tips and industry trends).

In part 1, we discussed when and why founders should make their first CX hire and Susana’s framework for CX teams. This post discusses 10x employees, thoughts on future hiring, and the cold email to Brian Chesky that got Susana hired at Airbnb.

10x CX employees, and thoughts on future hiring

If AI will raise the bar for CX, what of the 10x CX employees?

Susana highlights traits like empathy and being passionate about helping solve customer problems as the key. She also mentions the importance of being a continuous learner and teacher. The latter might have you scratching your head.

Susana explains:

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By teacher, I mean seeing an issue, confirming it as a trend and providing those insights to decision-makers with recommendations. Saying, “I’ve seen a customer trend, affecting Y% of users and moving CSAT by Z points. Here’s the documentation and write-up”. They are teachers to decision-makers about their customers. Notice how much value that adds compared to someone simply describing CSAT movements.

During our conversation, Susana repeatedly emphasized metrics as the key to a great CX hire. She also discussed how this hire would effectively advocate for the customer when prioritizing a product’s roadmap.

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Instead of simply requesting a feature, it’s better to say: “Here’s a request and the data to back it up based on user feedback”. This focus on data allows CX teams to work effectively within their teams and cross-functionally. It allows them to influence others whilst representing the customer. AI changes the tools, but the ability to influence will continue to make the difference between good and great.

Susana uses her expertise to advise startups on hiring in CX and notes an interesting trend:

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I’m speaking to startups that are changing the type of CX person they hire. They’re finding that most candidates are not yet following the trend. They’re stuck in the old way of doing things. With AI, there will be new skill requirements; it’s not enough to say you can do busy work. That will be minimised over time. CX hires must become more comfortable with analytics, understanding data, and improving processes.

This points to a similar trend across functions: the worker that scales themselves.

It’s not about eliminating humans. It's about using AI to eliminate tedious work and using the extra time to focus on delivering delight.

In CX, that means supporting customers on the front line and effectively representing them to internal teams. Being comfortable with data is the key to representing customers at scale, a skill Susana developed at Airbnb.

The cold email that got Susana hired at Airbnb

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I was a 20-year-old in college with no idea what I wanted to do, but I admired Airbnb and saw they were hiring in CX. I applied online but didn’t hear back. So, I did some research and found that Brian Chesky was a RISD alumni (one of the first art and design schools in the US). I designed a resume, knowing this was a potential way to stand out. Brian responded. That resume got me a first-round interview, and ultimately, I was hired!

Brian Chesky responding to Susana’s email.

Susana would use the same tactic to secure her role at Loom. If there’s one thing to learn from this experience, a single email can be the difference to getting that dream job, customer, mentor, etc.

But it takes time and patience to uncover what someone cares about —even more time to craft an email that speaks to that. In Susana’s case, it’s been time well spent.

Wrap up

It dawns on me that Susana's skill in sending cold emails is also the skill she uses to run CX teams: empathy.

She puts herself in her counterpart’s shoes and figures out what delightful looks like. She then meticulously works back from that to ensure she stands out.

In a world where AI promises to eliminate so much of the work we dislike and find tedious, I’m hoping it leads us to focus on delivering delight. The empathy required to get there is something I predict (hope?) remains the focus of humans.