How SentiSum helps brands leverage their customer conversation data to increase retention.
Sharad Khandelwal
|
Co-founder & CEO
of
SentiSum
Sharad Khandelwal
Episode Summary
Today on the show we have Sharad Khandelwal, co-founder and CEO at SentiSum.
In this episode, we talked about what motivated Sharad to build SentiSum, how brands leverage their customer conversation data to help increase retention, and how many customer conversations companies have to have before a platform like Sentisum really makes a difference.
We also discussed the different challenges organizations face when it comes to utilizing customer support data, how the market has evolved, and we then briefly chatted about how frustrating customer support bots can be, and their differences with automations.
Mentioned Resources
Transcription
Andrew Michael: Hey, Sharad. Welcome to the show.
[00:01:31] Sharad Khandelwal: Hey, Andrew. Thanks for having me.
[00:01:33] Andrew Michael: It's great to have you for the listeners. Sharad is the co-founder and CEO at SentiSum the customer analytics software that turned support conversations, customer reviews, and surveys into actionable insights. Uh, Sharad started out his career as a software engineer and later move to Merrill Lynch to work on equities.
Algorithmic trading from there Sharad served as an associate director at RBC capital markets. So. My first question for you, Sharad is like, what's the [00:02:00] connection. If any, with your background, what motivated you to start SentiSum?
[00:02:04] Sharad Khandelwal: Yeah. I mean, I think, uh, obviously the tech connection 'cause, uh, uh, I studied computer science.
I studied machine learning and then kind of, I, uh, I have been doing software development for almost 15 years. So that was the first connection that kind of gave me the confidence that technology. Exists to solve such a problem. And obviously you, as a founder can know, like, it becomes much easier if you are a tech co-founder, you can create the first version of the products.
I think I would say that's the kind of first connection. Yeah. And then second connection was because I was working mostly in corporates. It kind of made me realize like, like the, like the problems you were talking about Andrew before, there's a problem of silos problem of growing data, but not being able to kind of leverage all that data.
So all that led to kind of, uh, founding SentiSum.
[00:02:54] Andrew Michael: Very nice. Yeah. Uh, and definitely as well, like I can relate to the, like having that [00:03:00] technical expertise I, myself as well. I think the first time around that I did my first startup. I didn't have them, uh, the techniques teas, and like, I, I forced myself to learn and it's definitely a valuable skill.
Like no matter if you even don't end up using it, once you build the company and start growing the team, like having a really, really good solid foundation from a technical background. Especially when you're building a technology business, it's like for me, it's it's fundamentals. Uh, so absolutely very cool.
Um, so tell us a little bit about SentiSum. Like I gave a brief intro to what it is, but maybe like it's better to hear from you. Like what are you doing high up in customers?
[00:03:37] Sharad Khandelwal: Yeah. So SentiSum is all about helping brands, leverage your customer conversation data, and especially the customer support data.
So we as a kind of team at Sandy's, and what we believe in is that customer support data is gold, mine of insights, but very few companies are leveraging it either. Lack of awareness or, uh, [00:04:00] other reason being they want to leverage it, but it's so difficult because of the manual nature. So that's where we come in.
Our AI. Automates the reading analysis and reporting of all these conversations. So if let's say, if you are customer support leader in real-time, you can understand why customers are contacting you. What are the top reasons for contact? And if you are basically looking after children, you can understand what are the reasons that lead to customers churning.
So, so yeah, that's like the kind of space we operate in, mostly working with B2C companies in different sectors, like e-commerce, uh, travel. And we said we have started working with companies in also in the product or tech space.
[00:04:42] Andrew Michael: Very nice Yeah, I think like that, when you mentioned as well, like travel and e-commerce space, when, in the context of retention, like, what is the thought process?
Is that like repeat buyers, like bringing customers back in that nature or.
[00:04:57] Sharad Khandelwal: Yeah. So let's, if you, if you are kind of, [00:05:00] uh, if your travel has changed significantly since last year, because of COVID, but given the normal circumstance, you would be quite keen to know why customers are not kind of booking regular holidays or why they are kind of going to competitors or why they are not happy, why they are complaining and any.
Depends. If it's a subscription business with a non-subscription, if it's a subscription business, you would, you would, again, like to know why, why customers have kind of cancel their subscription. So if you're, let's say a kind of a meal kit to the recipe box company, or basically delivering shaving kits, you would like to know why customers have kind of canceled.
So that's like our product can help you understand what happened actually.
[00:05:42] Andrew Michael: Cool. Yeah. And I absolutely agree as well. Like the customer support is a gold mine of data and it's very often like under utilized. Uh, no, like in my experience as well, typically when it comes to product developments, they're one of the last places.
People turn to in the organization. And typically you always have people in support, [00:06:00] fighting for things to get fixed and for things to be updated, the only time I've seen like engineers and product teams really understand the pain is when they actually do the support themselves and they have to answer the tickets and they have to repeat it.
And it's like, well, instead of me answering. Group ticket five times. I'm just going to go and fix this bug or whatever I like. Um, so how, how is the product then helping feed these insights back into these teams? Like how do your customers use Senti some, um, maybe talk us through like a success case that you've had with.
[00:06:31] Sharad Khandelwal: Yeah, absolutely. So first let's, let's kind of touch on the challenges you just mentioned. First thing is because support teams are so busy, right? They cannot be talking to other teams in the business and saying, Hey, this is what we have been kind of hearing that they try to there that are putting process in place, but still it's not enough.
Right. Second is the very nature of so support. It's mostly qualitative data and it's high volume game, depending on the size and scale of the company. So how do you. Uh, kind of [00:07:00] quantify everything and make it accessible to everyone. Again, Andrew, you test on this. Most organizations work in a siloed way.
Marketing would be dealing with their own version of customer journey, their own data KPI support their own operations, right? So the challenges we are trying to solve, that's where we kind of come in as a tech platform. What we do is first of all, we aggregate all the sources, whether it's your email, live, chat, your NPS surveys, your social or voice calls, everything gets aggregated.
So that. That leads up to you having a single source of truth. And the second is a platform analyzes every conversation to uncover. What were the reasons why customers are contacting you? What makes them happy? What makes them unhappy? Right. So this leads to a kind of a real-time view of what's happening across the entire end to end customer journey.
Right. You know, more dealing with different taxonomies, different KPIs, different versions. Everyone in the company can have one view from a customer perspective. [00:08:00] And it's, it's, it's kind of real time, right? As things happen, you can understand what's happening. What are the trends? What's the trending issues, unlike traditional way, where you may be doing some ad hoc analysis.
And by the time you do it's too late. And if you're relying on surveys again, it's by the time you uncovered anything from the servers, it's too late. So that's, I would say it's kind of that key minute one. It is aggregates everything, analyze everything and gives you a simple, real time.
Yep.
[00:08:26] Andrew Michael: And let's talk about as well then.
And I think we chatted just briefly about this before the shows, like in terms of the volumes and size of customers that you're dealing with, like, um, for this to become valuable and useful, you would need to have a significant amount of data coming through into your support channels and then so forth.
So what are the typical customers that you working with look like
[00:08:47] Sharad Khandelwal: yeah. So I think we have customers ranging yeah. From getting few hundred tickets a day to few thousand tickets. So on a monthly basis, it can be a few thousand to even a hundred thousand kind of tickets. So that's the range of [00:09:00] customers we work with.
And to be honest, there is no one magic number. I can say. If you have more than these tickets, uh, you, you need such technology. It's all about your business. It's I think how we answered the. If you think you are not able to leverage your data and you're struggling to read every conversation, you need some kind of automation.
The first place always should be. You started manually. Your team should reading every support ticket, noting down the reasons and sharing it. But if you think you're not able to scale, that's when you need a, some kind of automation or technology or a platform like sentence.
[00:09:32] Andrew Michael: Yep. Um, and then, so you have quite a broad spectrum of customers.
Then I can imagine, like, uh, it's MBAs to larger size companies, um, when it comes to sort of understanding the market that you're working in and understanding the challenges to go through. So I think like, um, how do you see the markets today and how do you see it evolving over time when it comes to sort of taking advantage of this qualitative data and really using it to inform decision.[00:10:00]
[00:10:00] Sharad Khandelwal: Yeah. I mean, it's a very good question. And to be honest, we have seen quite a significant change in the last four or five years since we started working in this space. Right. Uh, as a startup, our biggest struggle initially, I would say for the first three, four years was market awareness. Right. There was not enough awareness that you can leverage this data.
There are solutions that could automate analysis, right? And people didn't believe in that, that they shouldn't be leveraging this data, but we are seeing quite shift in the attitudes and the mindset people are realizing that they need to be leveraging this data. So, yeah, that's, that's, that's obviously helping us as a startup because we are getting a lot more traction.
We are getting, uh, too many inbound queries now, customers, prospects coming to us and saying, Hey, you have this problem. Can you of help us? Yeah. This is, this is, and this is kind of going, uh, to kind of, uh, change for, for the good, to be honest, because COVID has [00:11:00] also, uh, had, I would say a big impact to this now more and more businesses are focusing on digital channels, right?
Uh, digital interactions are increasing, uh, everything is happening over chart WhatsApp and these kinds of similar channels. So how do you deal with such a scale? Technology is the only option. If you don't leverage automations, even you will lag behind your competitor. So, so this, this space is kind of is going in the right direction.
I would say awareness plus the market dynamics have changed. How consumers interact with businesses has changed all leading to you. Need to leverage technology.
[00:11:40] Andrew Michael: Yeah. I wonder if it's changed of, it's just that like online and tech businesses now are really starting to catch up and adopt old practices that have been around for centuries, but because of like the lack of competition in the early days, like if you look back 10, 15 years ago, there was like 2, 3, 10, 15.
Uh, technology [00:12:00] companies. And today, if you looked at it in the same, uh, stack there's 2, 3, 4, 5,000 companies all competing for the same Mindshare. And then at the same time, I think like we're, we've shifted going from like the early innovators and early adopters of software and solutions. And, uh, now we are entering a stage where like, we were definitely into early majority, maybe even getting to like majority now, Uh, when it comes to like the types of people using our products and services.
So naturally I think it's just become so much more demanding for software and product developers, uh, on their products and the solutions that they're building that they need to be like looking at alternate sources is no longer just enough to acquire customers and getting them using your product. Yeah.
You really need to like, understand their pains, their needs there and build the best product for them. It's not only can you just get by with a mediocre product. I'm not mentioning any names and build a huge companies, but, uh, now it's like, it's a different time. It feels it's like a nature of progression.
I think that this one where people [00:13:00] realize this is a pain, we need to solve this now. And we need to take advantage if we want to be able to compete.
[00:13:05] Sharad Khandelwal: Yeah, absolutely. And customer expectations have changed massively over the years, right? Like you, you, you can't send those emails saying we got your query.
We'll be in touch in 24 hours or 48 hours or 72 hours. Right. We, we live in basically WhatsApp age, right? You, you expect a response immediately and unless you leverage technology automations, you, you, you cannot be with such customer expectations.
[00:13:31] Andrew Michael: Yep. That's one thing I'm always a little bit wary of. And it's just, I think, because the technology hasn't sort of wild me in any way yet, but it's the ability to sort of use bots or to use automations, to respond, to support tickets and queries like, um, I very often get frustrated when I'm like greeted with the bots and then I've asked questions and I just realized at the end, there's no ways that the bot is going to be able to answer my question.
It's going to need to go to support. [00:14:00] Uh, and I need to chat to somebody about it. Like, how are you seeing this challenge at center time? Is this something like on your radar, uh, which is something that completely off the books. No,
[00:14:10] Sharad Khandelwal: I agree. And I am probably completely with you on the bot thing. It's so frustrating when you are, when you face a board that doesn't even understand you.
So I think that's where kind of some misconception comes in that automation in customer support or customer experience doesn't mean that you just simply fall back on bots, right? Yeah. Th th there are better ways to automate, like, like you can understand your customer support interactions to understand what kind of queries can first move to self.
So like simple enough to be moved to self-serve. How can you use these automations or that real-time reasons for contact? But I dies that tickets because not every support ticket is equal or same. Right. You cannot be answering every query in 24 or 48 hours. Some tickets deserve a higher priority. Right?
So that's where again, you can, you can leverage, uh, [00:15:00] technology automated, tagging that's. If you're using Zendesk to say, if the reason for this ticket is of type. Please give it a high priority and please delegate it to this team, right? This is this, this can free up so much of your, uh, agents time, where we are first level of kind of triaged can happen by technology without even using the bots.
Bots can be used for maybe just getting collecting basic information about your account details and name and for complex queries. Then you need a human again. These automations can help you.
[00:15:32] Andrew Michael: Yeah, for sure. For sure. Let me ask you a question then something else, every guest that joins the show, let's imagine a hypothetical scenario that you join a new company and churn and retention is not doing great at this company.
Uh, the CEO comes to you and says, Hey, Sharad like, you really need to turn things around. You've got 90 days to make an impact. Um, you're in charge. What do you. [00:16:00] But the trick here is that you're not going to do what everybody says. I would speak to customers, understand the main point points and then pick the highest, lowest hanging fruits and golf to that.
You're going to pick one thing that's worked for you in the past that you've seen be effective, uh, for yourself or for others. And just run with that sec. What would you choose?
[00:16:21] Sharad Khandelwal: What would I choose? I mean, I can start with, what would I not choose first is I would not choose what my gut says. I would not choose what others are saying.
I would probably not go with what has worked with me in the past because every company has its own unique challenges, their own unique business, their own unique customers. I think I would, in this case, I would like to rely more on what customers are saying on the data. Actually, I don't need to go, go to the customer and start interviewing.
Right. I can, all I need to do is just go to the last six or 12 months of data to understand what kind of customers have churned, when have they churn, what [00:17:00] kind of issues they have had with the company. Right. But it's all in your data.
[00:17:04] Andrew Michael: I'm not going to let you get away with it this easy, because this is the typical time.
Give me one thing that's worked for you in the past. It doesn't matter if they it's not going to. And I really liked the points you made as well, but don't pick something I'd worked in the past because it's not necessarily the same thing. That'll be applicable to your current company. But, uh, just give us one thing that you've seen effective and it's really great valid points as well.
What have you here now?
[00:17:26] Sharad Khandelwal: Well, for me being, being a tech person as well, I think be data driven. Yeah. Rely on data. And then make this prioritize, understand the impact based on data. Then make decision. Don't jump into fixing things.
[00:17:41] Andrew Michael: Yeah. 90 days though, it's not much time. I
[00:17:45] Sharad Khandelwal: think it's enough time. 90 days you can spend a good 30 days on just understanding what are the reasons and prioritizing it the next 60 days in kind of improving things.
[00:17:56] Andrew Michael: Yeah. Cool. Next question [00:18:00] then is like, what's one thing that you know about churn and retention today that you wish you knew when you got started with your career.
[00:18:06] Sharad Khandelwal: Hmm, interesting one at the start of my career. Uh, I learned more than 15 years of career. So trying to kind of. Yeah. I mean, I mean, I think, uh, if you, if you look, if I look back a few, five, 10 years ago, I think maybe the misconception or I kind of thought that people would switch only because of maybe price.
And again, it has to do with the shift in the expectation time, that time. Less awareness around customer experience. That little things can make a huge difference. When, when you think that I'm going with a different brand, the obvious thing which comes to mind it, is it, is it kind of cheaper or is it a better product?
Right? These were the two factors that always used to come into play, but now there are so many other factors that come into play [00:19:00] around customer experience, right? How you're treated, how they communicate with you, how the delivery how's the packaging, how are they? They, they are concerned about the environment.
And then do you resonate with it? But with that kind of a brand. So it's, it's like, like, like you were saying, there is no one, some magic bullet which can say this, this is going to solve chill. There. They can be hundreds of hours. Reasons. I think that's, I would say is the change in my awareness then versus now I know that it's it's complicated, but I know you can understand that he's this.
[00:19:33] Andrew Michael: Yeah. And it's not just about price for sure. You definitely do have an audience that is fickle about price and they will flip and switch, but, uh, typically they would have flipped and switched anyway, no matter what exactly. Exactly. Very cool. Uh, well, Sharad, uh, is there any sort of thoughts, so final thoughts you want to leave the listeners with today?
Anything that they should be aware of that you're working on or interesting. How can they keep up to speed with that?
[00:19:59] Sharad Khandelwal: Uh, I mean, [00:20:00] uh, we also run our own podcast and kind of the welcome people who are experienced in the CS space of why the CX space to come to our podcast and share their learnings. We have an active blog.
We have a website we write about, we are very active on LinkedIn as well. We are below subscriptions, so that's where we keep sharing what we are going through. Our learnings are part of dates and company.
[00:20:24] Andrew Michael: Cool. Um, very nice. Well, Sharad it's been a pleasure chatting to you today. Uh, really, really appreciate the time and, uh, wish you best of luck now.
Thanks Andrew.
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Sharad Khandelwal
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My name is Andrew Michael and I started CHURN.FM, as I was tired of hearing stories about some magical silver bullet that solved churn for company X.
In this podcast, you will hear from founders and subscription economy pros working in product, marketing, customer success, support, and operations roles across different stages of company growth, who are taking a systematic approach to increase retention and engagement within their organizations.