S2E06 – From Proactive to Predictive Customer Support – Danish Muti, Scaler Academy

Danish Muti has been in the HR-tech and Ed-tech space and has worked on setting up teams and defining more efficient processes. Being in the start-up space, he has experience in 0 to 10x and 10x to 100x journeys. Currently, he works at Scaler as Head of Customer Success and delivery. He has built the Customer success team from scratch and implemented more efficient processes to keep up with that 10x pace and go past some of the key metrics.

We cover:

• [01:26] Understanding Scaler Academy’s customer support operations
• [03:30] How to measure customer support effectiveness
• [08:05] What channels do customers prefer when it comes to support
• [16:56] Was the pandemic the catalyst that led to more innovation in support
• [19:19] How has AI enhanced the quality of customer support

Podcast Transcript

In this proactive to predictive customer support podcast, we have Danish Muti as our podcast guest and Siddharth Sharma as our podcast host.

Siddharth Sharma

Today I have with me Danish. Danish is the Head of Customer Success at InterviewBit and Scaler Academy. Danish, welcome to the show and… why don’t you start it… about introducing yourself to our listeners and viewers?

Danish Muti

Thank you, Sidharth. Thanks a lot for the quick intro and I’m really excited to be here. So just to basically give a brief introduction about myself, right now… I’m leading the customer success and the delivery here at Scaler Academy. So Scaler Academy is one of the fastest-growing EdTech companies of the country.

Here, our major aim is to ensure that we’re able to change the technology landscape of the country. So just to put in simple terms, you can actually think of Scaler as an online parallel university all together, where we are intaking some of the most aspirational developers out there.

Training them for the duration of months and then basically ensuring that they get placed at some of the best technical… uh… technical companies out there… uh… in the world.

Here I’m… I’m leading a team of customer success and… and recruitment specialists. At the same time… uh… improvising some of the processes from scratch, and ensuring that we are able to hit that 10X to 100X of journey here that Scaler.

[01:26] Siddharth Sharma

Right. Now… so Danish, let me first ask you about… you know, what does customer support in your organization look like, and if you could also elaborate a bit on the team structure when it comes to the support section of the company.

Danish Muti talks about customer support structure

Sure, sure, Siddharth. So, overall, if you look at our support section, right now… before we move to the support section, I’d just like to give you a brief about how does the… uh… entire structure of the company look like.

So right now, if you look at Scaler, we have two kinds of customers. We have our B2C customers which are the learners, which are the developers who enrol with Scaler to enhance their technical capabilities.

Then we have our B2B customers. B2B customers are… are some of the larger enterprises where these developers are getting placed once they complete the training program. And… and there are different other solutions there as well. But largely, if you look at the entire customer… base there are two sets of customers here.

For each of the different sets, there are different ways. Basically, if you look at the B2B segment, there is a customer success team that basically ensures the success of these customers at Scaler. 

And then if you look at the B2C team, because the volume is large there, we have a different structure in place where, with the help of the operations, customer success, support team, we ensure that… uh… all of their queries are being resolved. They’re having a really great journey with Scaler.

So… uh… right now, overall, if we talk about the B2C side, uh… for the learner’s side, we use JIRA for all the email communications that… then we have our internal tool as well which is mainly for the registered user… users at Scaler, where basically we communicate with these learners and try to proactively resolve their queries.

While on the B2B front, definitely, that is one front where more proactiveness is needed right? So right now, you know, mostly we use the pipeline management tools and… and most of our conversations that we have with these learners, with these customers It’s mainly one to one.

Just to have… ensure that there’s that personal touch in the entire engagement with the customers out there. So, in a nutshell, this is how we are managing our B2B and B2C customers here at Scaler.

[03:30] Siddharth Sharma

Sure got it. Alright. When it comes to measuring effectiveness, right, how do you and how does Scaler measure it? And what metrics do you track internally on a regular basis?

Danish Muti talks about customer support metrics

Sure. So if you look at the effectiveness, then largely… uh… I would say there are two metrics. One is the volume… basically, how many tickets are we receiving… the… on the monthly basis, on a weekly basis, on a daily basis.

Number 2 is basically NPS or the quality as well, right, where we want to ensure that these candidates or these companies are reaching at us… are reaching out to us with any problems, are these getting resolved?

And if these are getting resolved, what kind of happiness index is there for all of these problems? What is the turnaround time with respect to all of these problem resolutions there?

Overall, these are the key metrics that we measure and… and… and… and definitely like… our aim on the B2C front is to ensure there’s a quicker turnaround time, even on the B2B front. 

At the same time, we want to ensure… so, ideally, if you look at any customer support section, I think the ideal scenario for that support function is…The ideal scenario will be when they are receiving no tickets, right?

There’s no customer who is reaching out with any complaints or anything, but… but definitely, we’re on that track and that’s why we have another wing which is customer success, which proactively ensures that OK, we are reaching that ideal stage where we are trying to understand their problem even before it arises.

Also trying to move towards a predictive stage, right, where basically we are trying to… based on the past data that we have, we try to ensure that OK, this is… has been the pattern of a particular learner at Scaler and this is something that we can expect out of it.

So even before that happening, we try to get to that depth of those problems and try to ensure that that does not arrive at the first time. 

So right now I would say definitely Scaler as an org is already at a proactive level, and then we are slowly and gradually, with the help of technology, moving towards that predictive level. Where, even before that problem happens, we are able to get to the root cause of and trying to solve for those.

[05:33] Siddharth Sharma

Got it. And… you picked up a very interesting thread… in my head, right? You mentioned the words customer support and success in the same sentence, right?

What’s your experience with using these terminologies, right?

What do you think of the word customer support, and what do you think of the word customer success?

Danish Muti talks about customer success

So I feel while customer support has been there in the industry for quite some time, right. So, for example, if you are running a SaaS company, you need to have a customer support function. 

If you are running a… let’s say, food tech company or… or … or an EdTech company, Customer support is something that… that is well known to all of this industry, right, that their… their functionalities, which is more reactive in nature where customer support gets into picture wherever there is a query, or some kind of question that are coming out of the customers out there. Where if you look at the customer success, customer success is a domain which is relatively new to the entire industry right? 

I would say that this was non-existing if we talk about some 15 or 20 years from now, right? It recently started about… uh… into the picture right now. Mainly a customer success as a function like… is becoming very, very popular among the SaaS company.

Where the idea is like if you are having a product in place, where you are having a licensed product, a solution in place, you know, it’s someone who can basically ensure that the end-users are seeing success out of it. Which again, comes to the proactive and reactive part of it, right? Uh.. uh.. a bunch of people are ensuring that your customers are proactively using the product.

Your customers are adopting the product, so the customer adoption in that proactiveness, all of those are being handled by the customer success professionals.

So in my head, if you ask about the difference, I think these are the major difference between a support function and a success function, in terms of proactiveness or reactiveness to look at it. 

But… but what I believe is that…I think, 5 years or 10 years from now on, definitely there will be a lot of evolution in the entire customer support or success part of it, where, definitely like, as I mentioned, since we’re moving towards that AI, we are implementing more of the intelligent solution.

 We are moving more of the machine learning solutions onto the data learning solutions as well.

It is very simpler to analyze what would be the next possible steps for a particular client? What would be the pattern of a particular client? Based on that pattern, how we are actually preparing ourselves to serve those lines?

So I think this is something that we are moving towards, which is no more of a predictive model of it.

Some of these organisations I see adopting to this model already, but… but really really interested to see that where it goes right?

Starting from the customer support… now customer success and… and really excited to see the future of the entire domain here.

[08:05] Siddharth Sharma

I truly believe that right, I think brands need to be proactive going forward, right? It… they cannot just be on the back foot and always thinking of a defence when it comes to a ticket or a support as such, right?

They have to be thinking about how do you, you know, enable customers to even give them a big… and that is what is basically building their delightful support experiences, right?

I mean, that’s when you have the delightful support experience coming into the picture. Going a bit further into the support, right, we have all had the experience where, you know… uh… typically support has been… you call a particular number or you basically, you know… email them, right.

Typically phone and emails have worked, right? Do you think customers are changing their mindset when it comes to support?

And are they trying to reach a brand on different channels or new channels?

Danish Muti

Uh… I think we are tech-savvy, right, and I am… wherever we see the presence of com… for example, recently, post-pandemic, whatever… a new trend I… I started seeing about some of these companies is, wherever a set of customers were not really happy about the services of a particular company, they also started reaching out to those companies over LinkedIn.

Tagging the founders, different people of the company, with the hope that, OK, their query will get resolved a lot faster.

So what I think that with the evolution of the entire domain here as well, with the evolution of… like our generation becoming very tech-savvy, right now, in terms of customer support and other areas as well.

So I see that these consumers have a lot of options, a lot of mediums through which they can reach out to these companies with the hope that, OK, they will be able to solve the question.

And Twitter has been a very proper example where, in case their problems are not being resolved, they generally submit Twitter tagging again, some of the key decision-makers of those companies, with the hope that over there query is going to get resolved. But definitely, I think this is more of a part where I feel when an organisation is not able to address some of their burning questions to their streamline process, through the proper customer support channel.

I think this is when these customers have to go out using these other… other channels just with the hope that, OK, their query might get resolved through these channels. But if you have the right customer support structure in place… uh… I don’t think that most of these customers go out and using these other channels out there.

[10:19] Siddharth Sharma

Got it. And just picking up a thread from this, right, you know, when it comes to entire customer support and experience with Scaler, what other platforms do you currently operate in?

Danish Muti

So overall, if we talk about the platform… uh… on the B2C front, we use JIRA for all the email code operations.

Then, as I mentioned, we also have Mattermost through which we connect with these learners… uh… who are registered with Scaler, who are availing the services of Scaler Academy. So that’s how we differentiated leads from the actual consumers of the product here. 

And these are the different platforms through which we interact with our learners or our customer base right now. 

[10:55] Siddharth Sharma

How has your support team, over a period of time, right, has grown or evolved, if you could shed some light on it?

Danish Muti

I think overall, that’s a very interesting question, for sure. I think if I… uh… just to basically talk in number, I would say until last year this time, Scaler was a team of some 100 employees.

At that time, we were at a journey from zero to 10 X, but since the pandemic started, definitely like… Edtech was one space that was positively impacted, right?

And I think in the span of one year itself now we are a team of 500 people.

Like… like we ended up hiring 400 more people, adding 400 more people to the team.

The reason why we added so many people is, because of the scale with which we thought that Ok, Scaler could expand into different other verticals.

How Scaler can ensure that we are solving most of the challenges with the current situation, or we can adopt to the current situation.

And there itself we realised that now, I think, we need to have a proper support system in place.

Until last year, there was a support channel, but the volume is… volume was quite low there. That’s at that time, we were not actually thinking of automating the process.

But all of a sudden, all in a span of four to five months, the customer support team was entirely found from scratch.

It was formed from being a team of two people now being a team of 25 people. So that is the part where we are headed now.

And I think, over the time and over the span of, I would say, another one year, we are expecting the team to grow from another five hundred to a thousand.

So… so this is the growth path where we are headed and, with that growth, definitely, you have to stick to a fundamentals, stick to… stick to basics right, with that expansion. 

So, definitely like… we are heading towards that direction, staying connected to our roots, but in terms of expansion, in terms of… uh… customer acquisition, in terms of expanding our own team, I think, we are on a financial… financial growth here.

[12:42] Siddharth Sharma

Got it. Since you have been in this industry for so long, right, and… this is a question which I’ve been… uh… you know, I wanted to ask you from the time we started interacting,

you know, when it comes to providing customers with a delightful experiences, right, wanted to understand, you know, there’s been a lot of change, right? 

What has used…so I want to understand what used to work in the past and what do you think works today?

Danish Muti

I think in the past, if you talk about a delightful experience, I have seen… like, things used to be a lot more transactional back in the past. Now… now people have started thinking about qualities like empathy, like how well you are able to empathise with their customers, right.

Now when you are able to ensure that you’re getting into their shoes and basically understanding the entire problem from their, uh… perspective.

Earlier. I think, things were a lot more transactional. Now, for example, today, uh… my team onboards any customers, we try to ensure from the day one itself these customers are having a delightful experience.

For example, how we ensure that we are connecting with these customers, for example, while onboarding, we are sending some personalised gifts, which is very close to… uh… their hearts, something that they’ve achieved in the past.

We are basically aggregating all of those things and sharing them with as good will, as a welcome gift. So, from day one itself, they feel like they are being felt special here while collaborating with Scaler. 

So, something… I think those little elements have been added in the entire journey here, where we have to move above from being a very transactional in nature rather than being very I think, is connected with these customers.

So I think, more personalisation, this is something that has come into play now, and I have been seeing this being adopted, and a lot of customers success function throughout the industry, where the personalisation is one of the key qualities, personalisation and empathy, uh… which is being considered now in the customer success domain.

[14:31] Siddharth Sharma

You know, when you talk about this… you know, and this is the thread I’m taking a point you talked about being proactive and reactive, right?

I would like to get your thoughts on this as well. I’ve always felt that you know, brands used to wait on me to raise a complaint right? And… now, with lot of changes, uh… proactiveness is coming out in the support.

Like you are able to predict, OK, this person might not be having a great experience, right? What’s been your experience with that?

How have you, used that to your advantage or how are you building towards that. If you could shed some light on it?

Danish Muti talks about customer experience building strategy

Sure. You know, as of now, I would say, data is a friend, definitely. Like, you can actually predict a behaviour of a customer even before I would say, the customer starts acting on the certain situation or starts behaving, right.

Like, there is a very interesting used case to it, like even at Scaler, we try to understand the pattern about mainly the happiness index of these customers, how healthy is the relationship with these customers right now? Whether they’re categorised at red, yellow, green, uh… in what bucket do they fall right now. And then, that bucket keeps on changing right?

Because the nature is so dynamic, the issue is so dynamic that a customer cannot always be in the green bucket right.

That kind of dynamism is definitely there, but definitely, like here… what we do here is we have very defined structure. 

For example, if a customer is moving from a green bucket to yellow bucket, then definitely we have our team who gets into action, who tries to understand that why this would have been happened. 

And definitely, we have different metrics tied to it that when… and at what time duration our customer moves from a particular bucket to another one.

And basis on those inputs, we ensure that that customer who is moving will be getting moved back to the green bucket as soon as possible.

Within the turn around time of 1 week itself. So first of all, you try your best that customer is not going to red bucket. 

Red Bucket is for us is definitely a used detractor and we try to ensure that our customer is not even reaching there. So, even before reaching that bucket, we have an intermediate stage.

Our team gets into action and ensure that ok, they are being moved to the green bucket again. 

So this is a very simple formulation that we follow here, which has been working really well, in our case, and ensuring that we are retaining most of the customers, most of these customers are really happy with us.

But yeah, overall, what I see that, if you have the right set of data, if you know how to slice the data to, I think you can excel it, ensuring that have little or no detractors over time.

[16:56] Siddharth Sharma

So, taking a segment from this question, right, do you feel there is a need to reimagine the way customer support has evolved over the years?

And do you feel that, you know, the pandemic… unfortunately, is a turning point and it has forced organisations, when it comes to organisations to… innovating with their customers, like, engaging with their customers?

Danish Muti talks about customer engagement

This is absolutely… look, I think… I think the pandemic has forced everyone to look at things from a fresh perspective.

Like earlier, before pandemic, definitely things were happening at a… at the right pace, but now, I think post pandemic, a lot of these operational tasks has evolved rapidly, because now you cannot see each other in person, right?

We cannot make things happen very immediately. So, how we can replace that… how we can have other solution, we can make those things happen.

I think on the customer support part as well, uh… I think there have been a lot of changes. Again, if we talk about the platform, the solution that we are using, earlier

I think customer support was if you look at the back end part of the customer support, a lot of these things were definitely being data oriented, but a lot of these things were manual as well on both side. 

Just to give you an example, I think over the past, I think one or two years, I’ve seen a lot of new players coming into the picture, right, in the entire customer support journey, where we are automating the entire customer support experience. 

Where they are categorizing, let’s say, a bunch of questions and ensure that, there’s a very less turnaround time in answering or resolving those queries out there. There have been companies who have… who are coming with such solutions where basically, while you were speaking to the customer, you will be able to categorise those customers in different bucket. And you have a different solution already prepared for those customers who are falling in to that bucket.

Thankfully, that will subsequently… uh… reduce the entire turn around time and ensure that is a very delightful experience with these… uh… customers.

Earlier, if I talk about… some five years or four years from now on, I think past, I don’t think that these kind of solutions existed.

But, because of the pandemic, because of the volume that is coming to picture, a lot of these companies are forced into… uh… coming up with such products that can solve these customer support related questions.

Even to the purpose… in… the customer support professionals as well. Supporting them at how they can reduce the churn, how they can ensure there’s a less turn around time, how they can ensure these customers are going back… back with the right… right kind of answers.

They are happy at the end, uh… once you are basically, disconnecting the call with these customers. So… so, I think I… I think there have been a very rapid evolvement in the entire customer support journey. I think in the last one and a half years at least.

[19:19] Siddharth Sharma

You know, how do you think automation and conversational AI, right, can help enhance the quality of customer support?

Danish Muti

Well, definitely. I think… I think, we go back to the rules where everything is very data driven, right, if you talk about conversational AI and… basically how it’s tied to the customer support, and the entire automation piece of it, it is working on the basis of data collected in the past, right? 

So I think definitely, right now, what is happening that…how even basically, Scaler is trying to leverage that data is to ensure that we are putting our smart solution on the top of our existing database, right? 

How we can ensure that the entire system becomes more efficient,  if right now, if a task takes, let’s say 2 hours to perform if a query takes 2 hours… uh… of a solution.

How we can ensure that we are reaching a stage where the query is being resolved in less than, let’s say 20 minutes or 30 minutes?

So that is something that even we are striving towards. And… and… and, I think, all of these smart solutions, all of these operational automation and the conversation AI part of it.

I think all of this sits on the top of the existing data, an existing system that we have on the place and how… how basically, we can leverage this data to ensure that OK, the entire system is becoming much more… uh… efficient here.

If you talk about conversational AI, so definitely, I think the past example that I gave, where, while you’re speaking to these customers.

You know the system starts categorising these customers into different buckets. They start categorising the questions that they are having in to different buckets.

And start coming up with a solution. Which is in line with your company policies, a kind of solution that you want to give… uh… to these customers out there.

So I think, this has a great future. 

I think, we have just begun in these segments.

[20:57] Siddharth Sharma

What is that one tech you want today in customer support that is not available?

Danish Muti

They… that’s, I think, a very, very interesting question. Uh… no, I think the tech that I need is definitely in terms of automation.

How well we can categorise different segment of queries, how… how well we are able to basically come to a conclusion whether… this is the right set of questions that we should be addressing.

Whether… what team should be addressing certain questions or set of question, how it flows to the entire organisation

Because, customer support, is basically the front facing team right? There is a lot of things that keep on happening on the backend. How we can connect that front end to the back end more efficiently, how we can reduce the entire turn around time between these two teams, so that the entire process is seamless.

Because whenever, let’s say a customer support query comes in, by the time the entire team get… uh… gets into the picture and they start acting on it. Yeah, this is what happens… I… what is happening with a lot of these tech firms.

[21:53] Siddharth Sharma

Sure. And, how do you think chat bots and the automation, as an industry, right, is going to evolve over the next coming two or three years?

Danish Muti talks about chatbot automation

Basically, I think, if I talk about chat bot and automations as well, uh… I think we have seen a lot of evolution in the chat bot.

Some of the companies, like who have… having these great chat bots and, even Scaler is using… to have partnered with some of these companies to automate certain flows, not even on the customer support, but other areas as well, for internal communication as well.

Like, as I mentioned that we do from a, I would say 10X to 100X, or we are on that path where our company is going rapid.

Having said, there’s a lot of…Inter… uh… inter team communication that needs to happen. We need to ensure that… uh… we are keeping up with that pace.

So, so definitely if I talk about chat bots that… even internally we are… we have implemented a few chat bots that actually helps us to ease of the entire process.

Ensure that we are cutting that time that used to take a lot longer in the past times, right?

So, so definitely on the customer support, like… it has a huge… huge, huge benefit, uh… I would say. Right now, uh… like, already we are using that where we are having a bottom place and most of that, That is being the top layer of the customer support where the candidate can ask questions and if the bot is not able to solve those queries, then definitely it is passed on to the larger team out there.

And that’s how the entire hierarchy works here. So that being the front layer and then supported by the entire customer support team here.

Siddharth Sharma

Got it, got it. And, Danish, this has been super interesting and I can keep asking you questions and keep picking your brains, right? But that will be a never-ending conversation. So with this, we come to the end of the podcast. Thank you so much Danish for being with us today.

Danish Muti

Thank you, thank you so much Siddharth. Was lovely being a part of this show and I think, overall, I really enjoyed the conversation. You came up with really interesting questions. So thanks,

Thanks a lot for having me here Siddharth.