Shilpa Verma & Judith Platz 13 min

S2E3: How to Empower Support Operations with AI, Pt. One


In this episode of "15 Minutes with Judi," Judi Platz interviews Shilpa Verma, an expert in AI and support operations. Shilpa shares insights into how AI is revolutionizing support, her strategies for enhancing customer experiences, and empowering teams in the evolving landscape. She also reflects on her career journey and offers valuable advice for driving success in customer operations.



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Hello, everyone.

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Thank you for joining 15 minutes with Judy.

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Today, I'm so honored to have Shilpa Verma with us.

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And for those of you that haven't met Shilpa,

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she is someone you want to meet.

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Shilpa is a powerhouse female executive in the support operation space.

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Shilpa, you have had some amazing companies in your background.

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You have Salesforce, LinkedIn, Palo Alto,

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most recently Z-scaler.

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Do you want to tell us a little bit about your career?

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Yeah, absolutely.

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And I think I'll add a little bit of a personal twist

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with kind of my experience through those companies,

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and what I learned, and what I took away.

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So I started working for Salesforce.

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Actually, a little known fact, I have a master's in AI.

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And my first job out of college was actually a developer,

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professional services engineer,

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project manager, all rolled into one for a small AI company.

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So that's kind of where I started.

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And then there was this phrase called SAS

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that came up from 2008.

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And you know, long story short, I started working for Salesforce

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long before Salesforce was a phenomenon.

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So through Salesforce, I learned a lot about customer success,

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support, engineering interface.

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I did a lot of different roles there.

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But my experience there was, oh my gosh,

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it was like a phenomenon.

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It was a wildfire right now.

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Looking back, we realized that aspect about it.

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After that, I had my first four in support operations

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for Palo Alto Networks.

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And I think this is really where I found my passion.

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I love solving problems with automation systems, data.

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You know, I just, I really, really like that field of work.

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And so that's where support operations began for me.

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LinkedIn was actually, like an interesting story.

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I actually read a post from Jeff Wiener.

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A lot of us know of him and have heard him speak

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for on LinkedIn.

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And he was talking about the company culture

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he's aspiring to set up.

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And I just applied cold turkey, didn't know anybody.

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And got picked up for product operations role,

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which is different.

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But I think the salient thing about that

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is learned a lot about people leadership there.

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Huge learning experience.

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LinkedIn is world class when it comes to their L&D

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and just conscientiously setting up a people culture.

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So loved that when back to Salesforce for a little bit,

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to try my hand at the chief of staff role.

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And then when back to my roots and my real passion,

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I just support operations for Zscaler.

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And you know, so here we are.

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My last year has really been marked by AI and support.

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And that's really what really lights me up to talk about that.

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And so yeah, that's kind of a short brief

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of history of my professional career.

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- Thank you.

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Short brief, but very impactful.

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That's amazing, Shoka.

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So let's stay on the AI theme for just a little bit.

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We talk about AI and what it's going to do

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to the workforce.

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We talk about AI and the impacts that it's having

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everywhere in the world.

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But you also mentioned a couple of times,

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building teams and conscious leadership and such.

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What right now, would you say to a leader

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who's kind of doing the dance

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between his or her employee experience and AI?

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And what are the things that a leader should be considering

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today, not only to enhance that employee experience,

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but also the customer experience?

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What would you say?

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If you could tell him anything?

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- I think that's such a great question.

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I really have three tips for support leaders

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or operations leaders were thinking about stepping foot

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into AI.

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So one is AI is here to stay AI has been around for a while,

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but the big splash that we're seeing with gendered AI

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has also materially moved very well.

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So if you're thinking about it,

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do take the first leap.

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Three important things from my perspective.

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Number one is if you can use a conventional programming

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or declarative programming method to solve for a business

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problem, then please do that.

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AI is probably not a good solution.

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So pick your problem carefully.

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The second thing is make sure that you're able to give AI

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the data that it requires to solve the problem.

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For example, if you're doing case summarization

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and your agents are now putting good case notes,

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likely the outcome, no matter how powerful your AI

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isn't going to be something that you want.

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The third most important thing from my perspective

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is be ready for what happens in case your AI doesn't work.

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And what I mean by that is something

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like predictive escalation, right?

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If the AI doesn't work, you may have too many cases

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that the mechanism predicts that would escalate.

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And if the other side of it, it predicts to few,

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you may actually miss some important customer escalations.

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It's very important to willingly know on what side

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you're going to err so that your processes and the human fail

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saves can actually kick in something like generative AI.

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You may not want to give a direct customer facing answer

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for a security problem or network configuration

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or something that's really make or break for a business.

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You may want to preface that with letting

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the customer know that it's AI or having an engineer cross check.

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So those are my three principles

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that I would want to share with everybody

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as you start thinking into your first forever AI.

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And as with everything, AI is going to need care and feeding

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and data cleansing.

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So please collaborate with your data science teams,

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whether you're buying a vendor software

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or you decide to build your own,

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that is going to be very, very important.

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How is the customer experience going to change?

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Let's talk a little bit about that.

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I think that the jobs to be done for the customers

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are going to remain the same, right?

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They're looking for an answer,

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for knowledge looking to solve a case.

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AI will make the process of finding that faster and quicker.

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And customers are going to know invariably

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if you choose to use AI.

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So I'll share three tips on how you can orchestrate your website,

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your UI, your customer facing tools and self-service

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to make that experience a little bit more palatable.

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Because I do think it becomes more about the user experience

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for a customer, rather than materially changing their outcomes.

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For the internal experience,

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I think employee experience,

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they will experience a change in what they're spending time on.

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We hope that we can automate things like not

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taking summarization, categorization of cases,

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and many, many more things.

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And they should be spending a lot more time

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on finding a resolution for the trickier problems,

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things that require reproduction,

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things that are a lot more complicated to solve,

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because you'll be saving them effort

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in all the other walks of life.

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I do think that all of our internal employees

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are going to need to learn how to interact with AI.

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And they're also going to need to understand

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where AI works and where AI doesn't

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and how to interpret some of the results that come back from AI.

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So I think that's AI is a trend that's here to stay.

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And we all need to kind of start to understand

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a little bit about different types of AI.

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There's a lot of free learning courses

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that bigger companies like Google, Amazon,

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a lot of good stuff out there on getting yourself

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educated about AI.

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I have been at TSA and benchmarked hundreds

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and hundreds and hundreds of organizations.

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One of the things that was always fascinating to me

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and I would ask a specific question on the benchmark,

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the percentage of people in the support organization

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that were dedicated to support operations.

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And it was always, and I'll just share

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that it was always a very low number.

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It was surprisingly low for these amazing support orgs.

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Now I know there were some shared services out there

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in such two, but for support operations,

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tell me your experience in the last, let's say 10, 15 years.

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Is it getting a resurgence?

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Are people starting to pay more attention now?

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What's your feeling on that?

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Because it's always amazing to me

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that we look around for people to do all of these amazing things

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and we don't have enough.

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And yet if we staff to support operations team effectively,

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you know, how much more could we do?

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So tell me about that.

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What a great segue to talk about something

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that's so near and dear to my heart.

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And you've been on the TSI stage for such a long time, Judy.

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So you probably have the data and the numbers

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and benchmarking way better than I do.

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But just from having talked to industry leaders

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and where things are going, I do think that

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whether you call it support operations

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or your office of transformation

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or you have somebody that you call a chief of staff,

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at the end of the day, it's really all the person

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or the team that's helping a leader convert

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their strategy into an execution and actual impact.

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So I think that leaders may choose to call it something

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that different what I will ask everybody to do

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is think about it and really it is an operations role.

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Everything that you do is an operations role

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if it's codifying a process or making a workflow easy

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or introducing an automation or laying down

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the programmatic infrastructure for customer success,

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for example, that actually is operations as well.

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So I do see leaders investing more, Judy.

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I think that teams are getting split up

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and being called different things.

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But at the end of the day, I think whether it's enablement

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or it's a transformation office or innovation,

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I do think that there is investment in support operations.

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And what I want to challenge everybody to think about

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is with AI, all of us are going to be more

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thinking through how to train and prompt a system.

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So everybody's job is going to become

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a little bit support operations.

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Anyhow, something to think about there.

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Shopa, that's really, that's a great way to look at it.

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That, I mean, you see my reaction.

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Perfect.

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We used to say that about anything that was customer

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experience, right?

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Everybody was involved in customer experience.

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But if you think in your line right there,

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that everybody is support operations,

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especially as you're interacting with AI, brilliant.

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Love it.

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Absolutely love it.

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Thank you.

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Let's talk about something you and I have

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chatted about in the past, support and success

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and the coming together and the separating

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and the coming together.

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What are you thinking about that, especially

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as we talk about again, operations

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and shared operations teams, right?

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Sometimes between both.

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What do you think about the cross-functional teams

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between support and success?

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And what are you seeing as you talk to people?

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Yeah, it's such a fascinating thing.

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I think we've both been at companies that have gone both ways,

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like they've had customer success, they've had support,

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they've had time.

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And then these teams have merged and these teams

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have come apart again.

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I do think that, again, I'm not going to say one

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or the right way or the other, but I'll kind of share

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what I think about it right now, just given the scenario.

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And the companies that I've worked for, right?

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I think that the customer success function is important.

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You just nailed it when you said everybody's customer success,

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everybody's customer experience.

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We are here to make the customer successful.

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Now, the only thing that remains to be seen

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is what is the skill set that everybody's

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bringing to the table and what is everybody's responsibility

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great.

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So what I'm seeing more of as a trend

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is that the go-to-market teams are holding more of the new deals,

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the new customers, the new logos, but then also the QBRs,

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the renewals process, all of that sort of stuff.

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And the CSM role is turning more technical.

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So this is just something that I've

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seen at my last three companies, again,

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like people who don't agree with me, please don't hit on me.

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This is just kind of what I'm thinking and seeing.

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It is a lot about unlocking value with a technical skill set.

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And of course, that person needs to have a good head on their shoulders.

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They need to understand stakeholder management,

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influencing de-escalation of situations, right?

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But I think that CSM really do need

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to understand the product deeply and understand

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where the value comes from to be able to remove obstacles

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to adoption and success for the customer.

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So I'm not going to say a name, this function, one or the other.

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I'm just seeing a resurgence of more technical CSMs.

12:08

Now it's a great point.

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And I think that we as an industry,

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we spend years not intentionally, but accidentally

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confusing customers because we would go to market, depending

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on which company you're with, you would go to market with a tam.

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And a company, A, a tam did this, and that company B, a tam did this.

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Or CSM's.

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CSM does this.

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A CSM does that at a different company, right?

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And I think it is what works for any company.

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What is unique about your company?

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But just be really real.

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And even if you think, well, at CSM, I don't need to define it.

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Yes, you do.

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Tell the customer clearly what that role is to you

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and what it'll be to them.

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Call it a CSM, call it a tam, call it an SDM.

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I mean, we could go on with the acronyms for a while.

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But just make sure the customer knows what to expect

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from that individual in their role.

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And I think that right there is helpful.

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Because I do think we take too much for granted

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that why when it comes to those things, that's it.

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I think you could have said it any better.

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I mean, letting the customer know what each rule in the company

13:13

does for them.

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Yeah, I thought it'd out.

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