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Alok Goyal

Investor
Software
Healthcare

Alok's passion for venture capital is fueled by the energy of ambitious entrepreneurs and their big dreams. He believes founders must be dreamers and foolish (read courageous) enough to pursue their dreams. Alok began his investing career as a Partner at Helion Ventures and previously served as the COO of SAP India, holding various leadership roles at SAP since 2004. Alok is an alumnus of IIT Delhi, the University of Texas at Austin, and INSEAD. He is one of the founding trustees of CAPED, an NGO, and a co-founder of Plaksha University.

Write to him at alok@stellarisvp.com

investment
philosophy

My primary investment focus is on the enterprise software stack, from end-user applications to infrastructure. I am particularly excited about AI's ability to reinvent the world of enterprise software and services. I am a firm believer that a great product gives the company its right to exist, but a great distribution is what gives it the right to succeed. I therefore, am looking to partner with bold teams that have unique insights to build differentiated products, and can continuously evolve their GTM strategy.

why we invested

BLOG
Decoding our Investment in LimeChat
Alok Goyal
Arpit Maheshwari
April 11, 2022
6 min read

As a consumer, I (Arpit) have had several shopping experiences I remember fondly – our local grocer reminding me of adding something to my list by virtue of knowing my family and our preferences, a retail associate helping find the right skin product for my mother which also happened to be ~50% less expensive than what she would have bought otherwise, a footwear shop owner suggesting better boots to my brother, and many more.

All these instances had one thing in common – the merchant leveraged an understanding of our context to provide better solutions to our problems. In its purest form, commerce is about problem solving. Two parties come together, one with a problem (the buyer) and another with a solution (the seller). When not done well, which is very often, buyers experience frustration during a purchase; when done well, however, buyers experience satisfaction, and sometimes delight.

Consumer behaviour is fast changing, and brand / consumer interactions are becoming increasingly more digital. Leveraging digital products – predominantly chatbots – for improved customer support has been mainstream for a few years now; additionally, there is increasing evidence that consumers are open to making new purchases via chat as a medium – in fact, millennials surveyed in North America said they would actually prefer to purchase digitally via chat.

Within this space of evolving consumer preferences, we find two tailwinds worth highlighting (a) the explosion of D2C brands across categories (b) the adoption of WhatsApp as a commerce channel, particularly in Asia. We needed to look no further than our own portfolio (shameless plug: Mamaearth, Zouk, Nestasia) to see how D2C startups are likely to reshape India’s brand landscape over the next decade, and WhatsApp is considered India’s de facto OS for a good reason.

While consumer preferences have evolved and are likely to evolve even further, technology in this space has not kept up. Chatbots are still the most common mechanism for brands to engage users, and interactions with them often feel like breaking your head against a brick wall.

It is very common to feel frustrated at a bot’s inability to understand even simple requests, especially after our expectations are set with rather lofty promises – “Hi, I am <XYZ> bot, and I will help you find the right product in no time”. This is not surprising, since most bots are simple decision trees where the input is made via chat, as opposed to, say IVR. For the few that utilize NLU (Natural Language Understanding), they are still unable to figure out user intent, because they lack that all-important variable we mentioned earlier – context.

Context awareness for helping drive better commerce outcomes is a hard problem to solve, and requires a knowledge of prior customer conversations, combined with an understanding of a brand’s products. As a simple example, adequately processing the following request – show me more products like what you showed me last time – is not possible unless one has knowledge of a user’s conversation history. Similarly, responding intelligently “I don’t like this one, I liked the previous sweater better” is not possible for simple NLU driven bots, even in an ongoing conversation, since they have no way of knowing what this / previous are referring to.

The possibilities of this technology are endless. Limechat has already built a sophisticated conversational marketing solution for brands – as opposed to displaying ads that take you to a website, their solution allows a click-to-chat-and-buy experience, directly from the ads, for end consumers. Their experiments with initiating remarketing conversations with consumers for use cases such as abandoned carts suggest consumers are 10x more likely to complete the purchase on WhatsApp compared to SMS or email. Also, while today they deploy exclusively on chat, the technology by itself can work across other interaction media as well, e.g. voice.

We first started working with them about a year ago, when we led their pre-seed round – along with Pi Ventures – and the business has only gone from strength to strength since then. In addition to their fundamental technical abilities, Aniket and Nikhil have also impressed us with their business building abilities – they learn very rapidly, have dozens of happy customers, are already thinking deeply about the kind of organization they want to build, and have the ambition to build a large business.

It would have been folly on our part to not double down given what we were seeing, and that is exactly what we did. We are delighted to lead their Seed round, and are eagerly looking forward to what lies next!

BLOG
Why We Invested in GTM Buddy
Alok Goyal
September 21, 2021
6 min read

Our typical thesis in SaaS is about backing great teams in new categories. This typically means that there is no established category (e.g. employee performance management or sales incentive compensation) that solves that pain point. Usually businesses solve these pain points through a combination of different tools with tacky integrations, spreadsheets and other means, compromising both efficiency and effectiveness.

Examples of such theses for us in the past include Digital Adoption Platforms (Whatfix), Buyer Intent Intelligence (Slintel) and Buyer-Seller Alignment (BuyerAssist).

What makes this investment very different and contrarian for us is that this is smack in the middle of a very crowded category – Sales Enablement – a category that already has multiple unicorns.

Having been a software sales guy for a large part of my life, I have seen firsthand the challenges sales teams face in finding the right content at the right time. Even something as simple as the “standard company pitch deck” has a hundred versions spread over the hard drives of different sales people. It gets even more complicated when you begin to segment content by verticals, size of customer, geography. Not to mention the type of content – competitive battle cards, customer testimonials, ROI proof points, implementation ease/ time to value, product roadmap and feature coverage. Imagine, therefore, this 4-dimensional space of customer type, content type, sales person and versions and what you get is a royal mess!!

This is complicated further by the specific situation in the sales cycle. We assume a beautiful linear flow of MQL to SQL to demo a proposal to nego and viola signature on the page and money in your bank. In reality, it is a lot more complicated, moving back and forth between a variety of different stakeholders on the customer side, and also on the vendor side. This creates additional context which requires the content to be tailored to that context.

Historically, when sales enablement did not exist as a category, all content was stored in either hard drives of various sales team members, or in a classical directory structure accessible through a web interface (what we called an intranet). In theory it should have worked but for the problem that there is a combinatorial explosion of content (as described earlier) and if there is one function known to not be disciplined, it is sales!

Consequently, you have many different versions of what is the best content for different situations. As always, the best sales people, at best 15% of the sales force, are smart enough to get access to the right content and tailor it specifically to meet their needs. 20% never will even if you give it to them on a platter. But the mass middle – two thirds of your sales force can actually benefit if there were the right tools to make the right content available to them.

The first generation of sales enablement solutions went about creating more accessible file repositories – the category was earlier known as ‘Digital Content Management for Sales’. A decade later and after rebranding to become “sales enablement software”, the fundamental nature of the current solutions remains the same. They are basically a file repository, with decent content organization & search capabilities, and with an ability to share content links with the prospective customers with associated tracking on content engagement. These vendors have started expanding into adjacent categories such as LMS, while under-delivering their core value proposition.

In a day and age where software can automatically predict how you want to complete a sentence, and recognize what your prospect is saying on a video call and give you advice, a lot better can be and needs to be done.

That is where our first meeting with Sreedhar came in sometime last year. My initial instinct was a courtesy call as we got connected through Aneesh Reddy, co-founder and CEO of Capillary. I had little interest given that this is a very crowded category and therefore against the grain of my thesis.

However, the very first meeting with Sreedhar was very refreshing and it was clear that this was not an ordinary founder discussion. Sreedhar has created two large global enterprise software companies in his past – Host Analytics and Gainsight. The second one is a category creator with a $1B+ exit.

What most people see as a crowded market, appeared like a fertile ground of opportunity to Sreedhar, as he uncovered a ton of unmet user needs. This includes capabilities such as:

  • Content is historically looked at as a collection of files – PDFs, PPTX, DOCs etc in a static file repository. But in reality the content has a meaning, a purpose – these can be a customer story, product deck, common objections, competitive content etc.
  • An intelligent system ought to develop a semantic understanding of the basic nature of this content and the context in which the content is relevant. Such a system must be backed by AI models that are trained with the vocabulary used in that domain and even specific to that particular customer, competitor etc.
  • Backed by such understanding of the content, an intelligent system must surface the most relevant content in the context of a sales conversation that is underway – say, an email exchange with the prospective customer, to identify what is being talked about, prior context of the account, buyer persona, stage of the sales cycle etc.
  • And deliver this information to the sellers just in time to the sellers and in their daily workflow – with minimal friction.
  • Given the bloat in the sales tech stack, we can’t expect the sellers to login to yet another tool to identify the most relevant information! This requires building systems with a ‘Seller first’ mindset to drive adoption!

When we partnered with Sreedhar, all of these were ideas. Fast forward several months, today GTM Buddy has the best sales enablement software in the industry, bar none. Feedback from early customers suggests that the unmet needs are even greater than what we anticipated.

At a more macro level, we believe that most of enterprise software will be reimaged, rethought with AI-first SaaS, i.e. SaaS where AI is a core underpinning and not just a side feature. GTM Buddy is one such company which is changing static content repositories into a semantic one with its users (sales team) being shown relevant content at the right time/ place using machine learning.

Looking forward to the journey with Sreedhar and his team, and to the emancipation of the seller tribes of the world!

insights

sort
BLOG
From $10M to $100M: Lessons Learnt at Whatfix
September 25, 2024
BLOG
Bootstrapping SMB-centric GTM: Insights from our SaaS portfolio
May 21, 2024
BLOG
Launching your enterprise GTM engine: Top 10 takeaways from SaaS Talks #34
July 12, 2024
BLOG
Paying it Forward with the Stellaris Founder Network
June 13, 2022
BLOG
Spectrum is just the start: How 5G will enable a wave of new applications
August 8, 2022
BLOG
Why SaaS companies can withstand the funding downcycle better
August 16, 2023
BLOG
Tired of too many SaaS metrics?
January 10, 2023
BLOG
Customer Marketing – Your Most Important Lever in a Down Cycle
July 11, 2022
BLOG
Is the recession already upon us? A SaaSy take
June 30, 2022
BLOG
Slintel’s Journey From Seed to Exit in Less Than 3 Years
October 11, 2021
BLOG
Slintel: Learnings from Building a Data as a Service (DaaS) Business
June 10, 2021
BLOG
Scaling Mount Organization
July 31, 2020
BLOG
Navigating your start-up in uncertain times
March 20, 2020
BLOG
So, how do you move upmarket?
January 21, 2020
BLOG
Why moving upmarket is (mostly) important for creating large SaaS companies
December 20, 2019
BLOG
Speech recognition: Our view on how the market will evolve for enterprise and consumer use cases
September 27, 2019
BLOG
Electric Vehicles: The Imminent Disruption
April 22, 2019
BLOG
Electric Vehicles in India: A Forward Looking View
April 29, 2019
BLOG
Whatfix: What we Learnt from Series A to Series B in a SaaS Business
March 15, 2019
BLOG
Coin operators… And what coin do you need?
February 28, 2019
BLOG
India centric SaaS: Are we ready for take-off?
July 23, 2018
BLOG
'To sell is Human' - Getting the sales model right
January 25, 2018
BLOG
Business travel: Ripe for disruption?
October 6, 2017
BLOG
To AI or not to AI
June 6, 2017
BLOG
Building Data as a Service (DaaS) Companies: Early Learnings from Our Partnership with Slintel
October 22, 2020
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SaaS Talks #35: Pricing AI Products
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SaaS Talks #13: Channels and Alliances
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SaaS Talks #16: Turbocharging Webinars
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SaaS Talks #23: Bootstrapping your GTM
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SaaS Talks #5: Building Product Roadmap
March 19, 2021
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SaaS Talks #37: RevOps - Why, When & How?
October 16, 2024
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SaaS Talks #7: Solving the Pricing Puzzle
March 21, 2021
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SaaS Talks #24: GTM for Developer Software
April 22, 2022
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SaaS Talks #29: Domiciling your SaaS company
August 3, 2023
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SaaS Talks #2: Remote Sales for Global Markets
March 17, 2021
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SaaS Talks #21: Bootstrapping your SaaS Business
December 20, 2021
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SaaS Talks #20: Evolution of a Sales Organisation
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SaaS Talks #1: Asian Elephants vs American Rabbits
March 16, 2021
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SaaS Talks #33: Winning GTM Strategies for SMB SaaS
May 10, 2024
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Saas Talk #15: Product Analytics and Instrumentation
August 2, 2021
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SaaS Talks #28: Integrating LLMs in your SaaS product
May 29, 2023
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SaaS Talks #26: Your Product & Engineering Org Post PMF
November 21, 2022
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SaaS Talks #34: Building enterprise-centric GTM motions
July 1, 2024
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SaaS Talks #30: Impact of Gen AI on Software Development
September 13, 2023
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SaaS Talks #27: Customer Onboarding for AI-first Companies
February 6, 2023
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SaaS Talks #36: Kick-starting GTM - The India vs. US debate
September 6, 2024
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SaaS Talks #18: Slintel's journey from seed funding to acquisition
September 18, 2021
PODCAST
SaaS Talks #38: Navigating the SaaS-mic Shift: SMB to Enterprise
December 10, 2024
NEWS
Gen AI will compel companies to rethink their value proposition: Alok Goyal Stellaris Venture Partners
September 7, 2023
NEWS
Alok Goyal at Stellaris VP on opportunities in the slowdown for Indian SaaS companies
July 15, 2022

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