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

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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.

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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

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does for them.

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Yeah, I thought it'd out.

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