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Understanding Ideal Customer Profile (ICP) Part 1: Defining the ICP

Posted on by Kae Team

This article talks about the importance of defining an Ideal customer profile in the initial days (when you have none or very few customers) and provides a framework for doing so.

Founders are often tempted to capture as much value (or revenue) as possible from different types of customers. To do this, they often wastefully spend their energies and resources on capturing multiple types/avatars of customers and therefore lose sight of the company’s core value proposition and focus. As a founder, you must identify and focus your energies on the customers who are going to be most successful for you- the ‘Ideal Customers’

First of all, it is important to expand on the term ‘Ideal Customer Profile (ICP)’. An ICP is not the customer that gives the most revenue, it is also not only the customer with the easiest sale potential. An ideal customer is one who is deriving the maximum value from your offering and whom you can serve best (compared to alternatives). This translates to:

  1. Easier Sale and lower cost of acquisition
  2. Better retention and higher Lifetime Value
  3. Customer Advocacy and referrals

 

You should also not confuse ICP with customer/buyer personas (‘marketing Michelle’ or ‘HR Harvey’). A buyer/user persona comes after you have defined a broader ICP and is used to create messaging that helps you connect best with different personas in that ICP group. An ICP defines Who to sell to, while a persona defines How to convey the value proposition of your offering to this customer.

Your ICP is a clear, common, objective definition of who the ideal buyers and users of your product are. A well-defined ICP lays the groundwork for your positioning, messaging, pricing, GTM, and even product roadmap. Once you have clarity and validation of your ICP, everything else ties into it. An important point to note is that the ICP definition is not stationary, it keeps on evolving along with the organization. As you keep on acquiring and learning about more and more customers, the ICP definition will keep changing and becoming sharper.

 

Defining the ICP

A good way to define your ICP in the very early days is to look at the broad market that you are trying to solve for and look for a common subset where you believe you are best positioned to serve that customer group. Look at the overall landscape of customers and competitors. You are looking for a large opportunity which primarily can be because of:

  1. A gap in the market– There is a gap in the market and a large customer segment is underserved.
  2. Better product/experience– There is an opportunity to serve the customers in a much better way compared to the current alternatives. A low NPS/Retention for the current alternatives points in this direction.
  3. Opening of the market– There is a latent need in the market or the customer behaviour is changing rapidly for a new offering to come in and disrupt.

 

You should then speak with your best customers (or do surveys with prospects if the product/service is yet to be launched) and list down their attributes.

 

For B2C Businesses

For a consumer-focused(B2C) business, the following attributes are a good start

    1. Demography
      • Age group
      •  Gender
      •  Religion, Race and Ethnicity
      •  Occupation
      •  Income
      •  Relationship/Family status
      •  Geography

 

  1. Psychographic and behavioural traits
    • Values
    •  Interests
    •  Hobbies
    •  Aspirations and Fears
    •  Social media behaviour
    •  Buying behaviour

 

A few iterations using customer surveys/research will lead you to your ICP.

 

For B2B Businesses

For B2B businesses, the following attributes are a good start

    1. Target Company
      • Industry
      • Customer base/Business model- For example ‘B2B company serving SMBs and mid-market customers’
      • Size- Very Small/Small Medium/Mid Market/Enterprise Businesses
      • Geography
      • Maturity/other differentiators- For example, ‘fast-growing startups’ or ‘more than 20 people development team’

 

  1. Target customer profile
    • Profile- Ex Sales Development Representative/VP Marketing/Engineering Manager
    • Key goals of the customer
    • What is the core problem?

 

Put your target group into different segments and think through your value proposition from the perspective of the following parameters. The attractiveness of your solution (compared to the alternatives) for a segment will drive you towards your ICP:

  1. Problem intensity– The problem you are solving can be severe and (or) frequent. Pain point intensity usually is different in different kinds of companies. It relates strongly to the industry, size, and maturity of the company.
  2. Awareness and urgency– How aware is the customer of the pain point? Is it a need (urgent) or good to have?
  3. Ability to pay– Does this customer segment have the ability to pay the right value for your solution? This usually relates to the size and industry of the company.
  4. Ability to sell and serve efficiently– How efficiently can you acquire customers of one segment? How equipped are you to serve them? Geography and size of the company are the most important variables for this parameter.
  5. Competition/Advantage over the competition– Are there any other solutions for this customer segment? Is your solution much better than the current competition? Is there a gap/underserved market segment that you can go for? Usually, this parameter relates strongly to size and geography. It is probably the most critical parameter which gives direction to a possible whitespace or possibility of disrupting incumbents.

 

A few iterations using customer surveys/research will lead you to your ICP. Articulate it very clearly. Try to be as specific as possible and use more nouns/verbs than adjectives.

Example: Hull.io ICP definition- “Post Series-A (scaling) SaaS startups with more than $5 million in annual revenue, who use Salesforce & Redshift.”

After nailing the ICP statement, to plan and sharpen your go-to-market (GTM) strategy, we suggest that you put together the following as well:

  1. Success metric for the customer– What is the metric that the customer is likely to look at to validate that your solution is proving to be successful? (eg. it can be the lowering of churn or increasing of NPS)
  2.  Success metric for you– What is the metric that you would track to validate that your customer is deriving value from your solution? (eg. it can be the number of emails sent or tickets closed)
  3. Value Metric– What is the metric/unit that the customer is likely to measure that correlates with the perceived value? (eg. it can be the number of users or GBs of data storage)
  4.  Time to value– How much time does it take for the customer to start realising the value of your solution?

 

This way, you can approach the problem of defining your ICP, depending on the kind of customer profile and end goals you are targeting.

In part 2, we will talk about steps taken, post defining your ICP.

Generating the Future: Transforming SaaS with GenAI

Posted on by Veenu Choudhary

In the last 6 months, the world of generative AI has seen an explosion of interest and hype. There is no denying that GenAI is changing the landscape of software development. GenAI is disrupting the industries, software and the way we work, and it is happening at an incredibly fast pace. Every knowledge worker is playing the game of catching up with so many AI models and sexy tools getting launched every week.

SaaS as an industry is undergoing a complete disruption; nearly all the startups we have evaluated in the last 3 months were using GenAI in some form. The GenAI tech stack has been rapidly evolving, with the emergence of several new models and tools.

 

We broadly look at the existing stack in five layers-

Infrastructure layer includes hardware and cloud platforms which provide compute hardware and GPU. This includes companies such as Nvidia, AWS, GCP, Azure.

Foundation Models are GenAI models on top of which the entire stack is being built. They are AI neural networks trained on massive unlabeled datasets, enabling them to perform a diverse range of tasks, including test/ image/ audio/ code generation, text translation, and summarization. GPT-3, PaLM2, LLaMa are the well-known LLMs. Some open-source models trained on much smaller parameters are also getting interest for specific use cases.

Companies are using a combination of different models to increase accuracy and performance. A layer of domain/ vertical-specific models (health, legal, ecommerce, finance etc.) over foundation models has become a well adopted practice.

Next is a layer of tools that enables the use of these models, which we call Enablers. These tools are critical for the rapid adoption of foundation models by developers/ businesses, facilitating the shift where every company large or small is working towards adding GenAI capabilities to their products. Building production-ready AI apps is a challenging task that involves various steps. Starting with infrastructure setup, model hosting, database configuration, data collection and preparation tools, model selection, training or fine-tuning with your data, orchestrating different models based on use cases, integrating with your systems, deployment and maintenance of models, monitoring performance and cost of these models – all are part of this complex process. Hence, the emergence of enablers. Enablers offer capabilities such as orchestration, model management, observability, compliance, security, and more. Pinecone and Langchain are the most popular ones in this layer. Pinecone is a managed, cloud-native vector database with a simple API and no infrastructure hassles. Langchain is a framework for developing applications powered by language models.

Next is the Application layer, where customer-facing applications are built on top of GenAI models. It includes tools like Jasper, Glean, Copy.ai, Rephrase.ai. With GenAI, companies are providing better personalized customer experience, the conversation interface is taking over the clunky software UI and reducing their time to value.

Beyond all the excitement, it’s important to note that building and scaling an AI native tool is not as easy as it looks from all the Twitter chatter. We have spoken to many GenAI founders and tried to understand the challenges they are facing in customer adoption and product building. There are few interesting insights –

  1. Most of the GenAI tools from India are very early. They are seeing a lot of excitement and adoption from the market. Users are trying out different tools, but there is high churn. Prosumers and SMBs are the initial adopters of these products, but founders have to crack the retention and path to monetisation.
  2. Generational and non-critical use cases are seeing more traction. Generational use cases are some kind content generation- text, image, blog, code, audio etc. Non-critical use cases are business use cases where the cost of failure is not high and can work with not-so-high accuracy – sales, marketing, hiring etc. In high value use cases like cybersecurity, there is a cautious adoption of GenAI.
  3. GTM motion for enterprise SaaS remains the same. There is a sense of curiosity among enterprises regarding GenAI and acceptance to use it in their workflow but they are cautious. Their concerns about data privacy, security, and compliance persist, and there is limited trust in public LLMs. We are seeing a trend of building on the client’s VPC, which can increase the time to adoption.
  4. ChatGPT has changed the customers’ expectations. Customers are conversing with tools in natural language, they are not only asking for information or insights from the data, they are expecting end-to-end tasks to be done. The expectation is AGI (Artificial General Intelligence). We spoke with an AI native marketing product from India where customers are spending more than 30 min every session and asking in one single command to look into the data, identify cart dropout and design and send a campaign to them.
  5. There is a lot of adoption of picks and shovels- libraries, tools helping developers build apps for different use cases. Autonomous agents have become very popular. SuperAGI is one of our portfolio companies, which has gained more than 7k GitHub stars in two weeks. It is one of the trending repositories on GitHub. It is a dev-first open-source autonomous AI agent framework, enabling developers to build, manage and run useful autonomous agents quickly and reliably.

 

Based on our learnings over the last few months, we are more bullish on a few spaces in GenAI where we believe large outcomes from India can be generated:

  1. Picks and Shovels for developers: GenAI tech stack has become fairly complex and it is changing rapidly, only LLMs can’t help with production level use cases. As discussed in the above section, it is a long iterative process and these tools help developers build, experiment, train, and compare quickly. This is a new need that has emerged while developing in GenAI. Vector database, framework, model orchestration layer, autonomous agents are some examples of the types of tools getting created. Pinecone and Langchain fall under this category.
  2. No code enablers for businesses: We have seen copilot (GenAI) in a box model, where the entire AI stack is taken care of by the tool, you just have to integrate with your existing software. This new layer is emerging in the tech stack and it can be an opportunity for new players.
  3. ModelOps/LLMOps:MLOps used to be a not-so-attractive industry until 6 months ago. With GenAI, more models are going into production and none of the existing MLOps were made for that. Existing MLOps companies are adding capabilities and a new set of ModelOps tools are also emerging. ModelOps/ LLMOps tools include model lifecycle management, observability, data security and privacy, and model monitoring.
  4. Autonomous Agents:As discussed above, customer expectation is for AGI which can be provided by autonomous agents. They have the ability to analyze intricate problems, solve them iteratively, and take actions. AutoGPT is the most popular one, it has more than 139K stars on GitHub. In today’s form, it is not easy to use AutoGPT for business use cases. AGI is still in the early phase and will take some time to reach the customers’ expectation levels.
  5. AI native companies: On the application layer, we are keen on these companies. In many use cases, incumbents have the right to win because of distribution advantage. That’s why we believe all the niche use case products will get commoditised as incumbents will launch it as a feature. However, if you are building an AI native software with some vertical focus and data flywheel, then there is an opportunity to deliver better accuracy compared to incumbents.
  6. GenAI-powered Vertical SaaS: Vertical LLMs are trained on curated high-quality data from a specific industry. This allows Vertical LLMs to generate more accurate and relevant results. Legal, health, and finance are among the industries where a lot of knowledge resides in the massive historic data, which is the play of Vertical LLMs. GenAI-powered Vertical SaaS companies are getting popular, such as Hippocratic in healthcare and Evenup and Harvey.ai in legal.

 

A lot is happening in the GenAI world and we have been continuously learning about the latest developments. Our thesis will keep evolving. We will release a series of articles on GenAI to keep you updated on our learnings. If you are a founder building in GenAI or an enthusiast, we would like to have a discussion. Please feel free to reach out to veenu@kae-capital.com or sarthak@kae-capital.com.

Crafting a compelling pitch deck

Posted on by Kae Team

The pitch deck helps in communicating the company’s story to external stakeholders. This could be to raise capital or bring in customers and partners. This blog will focus on crafting a pitch deck for early-stage founders to sell their vision to investors.

Slide 1

What do you do?

A 1-line blurb, which should communicate who you are. The common misconception is that it is best to go for an “X for Y” positioning ~ for eg. a “Thrasio for Apps”, which might not always be the best option.

Sometimes, it is best to provide a line on the model and TG that you are targeting. A sample could be “SaaS enabled B2B Marketplace (business model) for Pharmacies (TG)”.
Eg. Zetwerk is India’s largest on-demand manufacturing network, serving customers in every major industry.

Slide 2

The team slide

Who is in the founding team, along with backgrounds (organizations you have worked in, along with your alma mater) and whom you have hired outside of the core founding team form the basis of investors’ judgement. At the early–stage, investors are primarily backing the founding team, so this slide must be given importance in your presentation’s hierarchy

Slides 3-4

Problem and Status Quo

It is important to succinctly explain the problem you are going after, which can be best explained through a user journey and point of discomfort at present for all stakeholders. Feel free to use diagrams/charts to explain the journey, but make sure to do it across all stakeholders.

‘Status quo’ defines how things are being done presently. The problem gets fleshed out better when all the other alternatives to solve it are highlighted, post which it becomes a matter of making an argument as to why your solution is the best.

Eg. If you are evaluating an IoT-based vending machine to be placed in corporate offices ~ you need to think about it holistically.

The fundamental problem is to get a meal at lunch ~ it may be tempting to lay out the status quo as the office canteen. However, this paints an incomplete picture, as you have alternatives like food delivery apps, restaurants in your vicinity, a dabbawalla, or perhaps your nearby multi-purpose store, which typically has ready-to-eat meals.

It is pertinent to understand why a vending machine (IoT-enabled or not) will be the best solution to offer lunch to office-goers.

Slides 5-6

Market Size and Trends

Large markets can be seen in two ways ~ either you sit on existing spend pools which are getting organized/digitized ~ for example, gold lending is a $140 Bn market, however, $90 Bn is unorganized, making this a large opportunity. Sometimes, markets are nascent but fast-growing – for example, in blockchain gaming between 2020 and 2021, the number of active wallets interacting with gaming smart contracts exploded. If it’s not large now, why do you think this will become large in the future?

Investors want to understand this market, broken down into volumes and pricing. These are revenue pools/spend pools, of which you wish to capture a segment at scale.

Market trends answer the ‘why now’ question, which refers to tailwinds or recent inflection points which incentivize adoption. At the early stage, investors prefer to see bottom-up calculation over referring to industry reports to size the market.

Slide 7

Competition

While in ‘Status Quo’, broad solutions are addressed, the next step is to go one level deeper into the competition, which should include both direct and indirect competitors, covering their scale, your differentiation and positioning.

While most founders end up putting out a checkbox chart where they benchmark the features and functionalities with other competitors, which is important, it alone doesn’t answer the core question. Investors look for something that will be difficult to replicate for other founders, and if so, why.

Slide 8

Traction, cohorts/engagement, and usage metrics

Investors want to see how you have grown over the last few months, how sticky your customer is, how often they use your product and for what. Showing steady month-on-month growth in toplines is a helpful metric to share. Alongside this, having stable or growing margins and good usage metrics make for a strong case for fundraising. You should go for pre-series A/series A fundraises when you have strong metrics.

However, at the pre-seed/seed stage, traction becomes a good to have, not necessarily a must-have. If you don’t have traction, investors will index more on the team and look for deep insights – what you have gleaned speaking to customers, how deeply you think about the market, competition, etc.

Slides 9-10

Roadmap and Funding

Investors want to know your roadmap – which customers you will target, through which channels/GTM strategies, how this will evolve at scale, and how much capital will it take to get there.

They look for clear thoughts on what are the kind of toplines and margins you look to hit over the next 24 months, and what resources will you need to get there.

In summary, this is a bare-bones structure to highlight the key questions that investors are trying to get answered when they hear your pitch. The deeper your insights outside of the general framework, the better your discussion will be!

If you are building something interesting and need further help in crafting a pitch deck, reach out to sarthak@kae-capital.com

Investment in Onwo

Posted on by Veenu Choudhary

We at Kae Capital are very bullish on India to the world theme. We have already seen an increase in the global software businesses building from India. We believe to see a similar trend in global trade as well.

India is one of the largest agri-product exporters in the world. In FY22, the Indian agri exporters reached $49.6Bn, which is a 20% increase from the previous year. India is an agri commodity hub and one of the largest producers of several agri commodities like rice, sugar, and spices.

Most of the food products are traded as commodities from India with little to no value add. Major value chain margins lie with the outside processors/ buyers. There is a scope for adding value at the source to ensure better margins and value for the Indian manufacturers and sellers. The Government of India is pushing a lot to increase food exports and processing from India. The ministry of food processing industries (MoFPI) is boosting investments across the value chain of the food processing industry. Under PMKSY, GoI is making efforts to develop many mega food parks, agro-processing clusters, food processing units, and cold chain projects across the country. We believe with maturing processing infrastructure, India is at an inflection point to become a processing superpower. India’s food processing sector is one of the largest in the world and is expected to reach the output of $535 Bn by FY26.

The majority of these producers are MSMEs with a broken, unstructured and offline supply chain. Global food supply chains have a lot of intermediaries, inefficiencies and low transparency on the rates and transaction timeline. There is a need for an online platform to bring in trust and efficiencies in the value chain, which is where ONWO comes in.

ONWO is at the forefront of reimagining the food export industry using a digital-first approach in an otherwise traditional industry. ONWO’s full-stack solution will help Indian manufacturers and SMEs access the global markets in a fully managed and asset-light model. ONWO is creating a digitized global food supply chain through contract manufacturing and a structured food export segment, allowing Indian manufacturers to ship processed products to the world.

ONWO is a curated marketplace to reliably discover, transact and fulfill orders of processed food products from Indian manufacturers. ONWO offers end-to-end solutions to its customers in a full-stack digital model, involving contract manufacturing and private label solutions, quality assurance and risk management and complete order fulfillment using a cutting-edge technology platform. ONWO ensures better margins and value add for both manufacturers and buyers. The key markets serviced by them are the US, Canada, UAE, Saudi Arabia, Qatar and Oman.

Onwo was started by second-time entrepreneur and former Flipkart executive Bipul Kumar in July 2022. We have known Bipul from his first startup and believed in his vision of transforming India’s food export value chain. Bipul has built an experienced and high-quality team. They have executed well in the last 6 months, exporting more than 10,000 MT of food products, with a high repeat rate of >90%. ONWO has covered more than 15 countries in operations.

ONWO is on a mission to build a solution for this large category. We are very excited to partner with them. It is a massive opportunity and they are a great passionate team with the right skills to build this business.

Understanding the Cross-Border Fintech Market

Posted on by Kae Team

With over $ 130+ Trillion flowing globally in cross-border volumes, cross-border fintech offers a rare opportunity to create multiple unicorns.  16% of cross-border revenues (not flows) lie in EMEA, 8% in APAC, 5% in LATAM, and 6% in NA (as per EY)

For the purpose of understanding the landscape better, we have divided it into Infrastructure and Application layers

Infrastructure layers help integrate with local banking rails in both/either sender and receiver geographies. They, in turn, integrate with fintechs (Wallet providers for cross-country money transfers, International Money remitters etc.). They solve for:

  • Virtual account creation (which in turn helps them access local payment methods & helps with multi-currency accounts creation)
  • FX rates by buying and converting currency in bulk
  • Reconciliation – This may not be a service offered by all infra players. This depends on the value prop being offered to their customers.
  • Take on average 50 bips on GTV

Application layers own the customer, they may manifest as a checkout page on marketplaces:

  • They acquire and manage customers
  • Solve for customer support and are usually the closest to customers ~ allowing them to build out other higher margin services.
  • The take rates here vary depending on the core use case ~ players can make up to 80 bips as checkout solutions, an additional 20 bips as treasury solutions, and potentially upwards of 1% per month as working capital interest on a monthly basis

 

Bifurcations between Infra and application are not cut and dry, and often there exist fintech players who are infra providers in one geography, and application layers in other geographies. For eg., they may have local bank accounts (i.e. are directly connected to banking rails) in geographies to solve for collections in that geography but need to work with other infra players (who are integrated with the local banking rails in other geographies) to solve for payouts in those geographies.

In India, payment volumes less than $10k fall within the purview of OPGSP and most players solving for payouts/collections within India are operating within the constraints of this license, for volumes in excess of $10k companies are relying on SWIFT-based bank transfers

In addition to understanding the value chain, it is pertinent to understand payment flows in a little more detail. Given below is a sample of Inward flow of money from Australia to India ~

Why we choose to make bets in both Infra and Application layers ~

Understanding the market dynamics of payment infra players ~

Infra players will want to have access to as many local bank accounts as possible, and by extension, have access to relevant licenses which allow them the most degrees of freedom, i.e. the ability to send and receive money from multiple geographies. For example, UK’s E-money license (auth. EMI license), Australia’s international remitter license, Singapore’s major payment Institution license, Hong Kong’s Customs and Excise Dept., etc.

There seem to be inherent network effects here, i.e. if I add more geographies solving for both inward and outward payment flow, this will improve the experience of my end customer, i.e., the end customers who will want to send and receive money from as many countries as possible.

Additionally, forex rates are also solved through economies of scale ~ further incentivising market concentration towards only a few infra players.

Having said that, we don’t feel this will be a winner takes all market ~ because each local bank will integrate with multiple infra providers, and we feel that beyond a point forex rates will not be further optimizable, hence commoditizing the FX rates as a differentiator.

So it is our estimate that there can comfortably be more than 3-4 players dominating the global cross-border payment infra market.

With more than USD 130 Trillion flowing through the market, we feel capturing 10 Bn in GTV will ensure a large outcome for us as investors, which we can do by focusing on any one of the several geographic corridors. Additionally, we have seen some infra players start entering the application layer as well.

Understanding the dynamics of Application Layers ~

Infrastructure provides the rails to all kinds of application layers. We can further segment application layers into the following subthemes ~

  • Customer segments ~ B2B, B2C, C2C
  • Flow of money ~ payouts vs collections
  • Use cases ~ B2B trade, health, education, payroll, etc.

Application layers that offer the best customer service/support, and keep expanding their product offerings without compromising on quality will be poised to win. Each use case gives an opportunity to go deeper into specific use cases, for example, education ~ which will allow them to double down on use case specific products like education loans.

We do not think this will be a winner takes all market because there doesn’t seem to be a case for network effects, i.e. the addition of new customers (think marketplaces) will not add additional value to the n+1th customer added on the platform in terms of rates/convenience/etc. Additionally, integration with rails will also not be a differentiator since rails will try and partner with all application layers and we expect this to converge at scale.

We will go after the use cases with the largest TAMs.

Summarizing~

If you are building something in either infra layers or application layers with large vertical TAMs, we would be happy to speak to you!

Investment in Contlo

Posted on by Veenu Choudhary

Global e-commerce is a massive market. Online retail sales are expected to reach $6.5Tn by 2023, according to eMarketer and Statista. The US D2C (direct-to-consumer) sales have crossed $128Bn in 2021 and are expected to reach $213Bn by 2023.

The pandemic has led to unprecedented growth in digital adoption, shifting consumers’ shopping behaviour to online. We have seen an exponential rise of D2C brands from India post-pandemic. According to the Unicommerce report on India’s retail and e-commerce, D2C brands are driving growth in India’s e-commerce with a 45% CAGR and has the potential to reach $ 70Bn in a few years. According to Statista, India’s D2C market is expected to grow by more than 15 times from 2015 to 2025. In 2020, it was around $33Bn and is forecasted to reach $100Bn by 2025.

Globally e-commerce brands are moving away from marketplaces to headless commerce platforms like Shopify. Shopify is an e-commerce platform which enables merchants to set up online stores and has seen massive growth, doubling the number of merchants using Shopify in the two years from 2019. Shopify ARR was around $5.2Bn in Sep 2022, a 24.5% YoY growth. It was $4.6Bn in 2021, 57.4% YoY growth from 2020.

As brands continue to sell online, they struggle with high marketing spending on CAC and customer retention. They want to build direct relationships with consumers on different channels. To build a long-lasting relationship with the consumer, a consumer needs to be engaged at different points in the journey.

At Kae, we have invested in many D2C brands and keep evaluating more D2C brands in different categories. From all our conversations, customer engagement and high marketing spending came across as common areas of concern. The legacy horizontal marketing tools are not built for e-commerce specific use cases. There is a need for a verticalized marketing automation solution for e-commerce.

We are very bullish on vertical SaaS as a theme and believe the next evolution of customer engagement/marketing automation has to be more personalized. This is exactly where Contlo comes in. It is purpose-built for deep e-commerce use cases via seamless integration with leading e-commerce platforms like Shopify, and Magento. We have been in touch with Ishaan and Mukunda, from their early days and have seen their impressive journey of building an AI-led marketing automation for e-commerce.

Contlo enables e-commerce and D2C brands to accelerate their sales growth, drive revenue generation and automate personalized experiences for its customers using e-commerce centric omnichannel customer engagement across email, SMS, WhatsApp, mobile and web push. It is leveraging AI to build hyper-personalized commerce experiences for end customers.

Today more than 1000+ brands use Contlo globally. It has witnessed a 50% MoM growth since its inception. It is empowering brands to build direct channels with their consumers, leading to increased retention and LTVs.

Contlo beautifully fits our investing framework for SaaS, leveraging data to build an AI-based vertical SaaS software with a PLG motion.

We at Kae, are thrilled to partner with Ishaan and Mukunda in this journey. They have built a very strong team with a vision to build a world-class AI product. You can find out more about Contlo here.

The Modern Data Stack

Posted on by Veenu Choudhary

Data Sources–

Companies generate a lot of data from different sources.

  • OLTP Databases– OLTP (Online transactional processing) systems handle large volumes of transactional data. It consists of user information and operational data generated by users such as e-commerce purchases and online banking. A standard database management system (DBMS) is an OLTP system. Mysql, mongoDB and Postgres are some well-known databases.
  • SaaS tools– Companies use many SaaS tools to run their business such as CRM tools to store sales, marketing and customer success data (Salesforce, Hubspot), payment/billing softwares (Stripe).
  • Event Collectors– Nowadays every possible touch point with the users is recorded as an event, which is used for analysis. It includes recording every click on websites and apps. Segment and Snowplow are popular choices for collecting events.

Extract and Load

All data from different data sources is extracted and loaded to a centralized data warehouse/ data lake. Earlier, the sequence used to be ETL- data is first extracted then transformed and then loaded into the data warehouse. Now, it has evolved to ELT- data is extracted and loaded into the datahouse and later transformed at the warehouse itself.

Data Storage

Ingestion tools stored the data at a cloud data warehouse or data lake. Data warehouse stores structured data (tables) that can be directly queried for analytics. The popular cloud data warehouses are Snowflake, Google Bigquery and Amazon Redshift.

Data Transformation

After storing the data, it is transformed directly in the warehouse into a structure ready for analysis, which is used by the data science and business team to run different analytics and ML models. Dbt, Airflow and LookML are the most popular transformation tools.

Analysis/ Output

The transformed data can used for different purposes-

  • BI/ Visualisation– These tools enable business users to derive insights. They provide a dashboard view with graphs/ pie charts which facilitates business visibility. Tableau, Looker, Power BI are some popular BI tools.
  • Data Workspaces– These tools make it easier for different users to query, visualize and collaborate on data and create dashboards. Some of the emerging data workspaces tools are hex, deepnote, mode, noteable.
  • Data Science, AI/ ML– Data scientists can run ML models on data with help of these tools. Some of the popular tools are Sagemaker, Continual.
  • Reverse ETL– It syncs back the aggregated data to SaaS tools like customer support, sales and marketing to provide full consumer visibility to business users at their primary software. Census and Hightouch are the popular reverse ETL tools.

Data Monitoring and Governance –

We also need to maintain operational data hygiene. There are three major data ops categories of softwares, which help in reducing the risk, operational complexity and cost of the cloud data-

  • Data Observability– Testing and monitoring pipelines are developed to detect and resolve errors or issues. Monte Carlo, Acceldata and Great Expectations are the popular choices.
  • Data Discovery– Data cataloguing, documentation and discovery so that people can discover the right tables for their use. Atlan, Amundsen, and Alation are the popular tools here.
  • Data Security– Access control and data security to safeguard the company’s data. Control which employee has access to which data. Cyral, Immuta are the emerging tools in this category.
  • Introduction of Data lakehouse by databricks and Unistore by Snowflake- Databricks has introduced the data lakehouse. A data lakehouse combines the flexibility, cost efficiency of a data lake with the data management capabilities of a data warehouse. It is an open data management architecture to enable analytics, BI and ML on all data types.
https://www.databricks.com/glossary/data-lakehouse
https://www.snowflake.com/en/data-cloud/platform/
  • Data Marketplace — Snowflake has become a behemoth and is now adopting a platform approach enabling products to develop on top of it. Idea is companies can use the native application framework to build native Snowflake apps that can be distributed through Snowflake Marketplace. Snowflake customers can discover, evaluate and run the apps in their accounts, removing the need to move data, thereby improving privacy and security. It is enabling customers to bring apps to data rather than moving data to different apps. It eliminates the delay and cost of traditional ETL with direct access to ready-to-query data and pre-built SaaS connectors.
https://www.snowflake.com/snowflake-marketplace/
  • MDSaaS– Modern Data Stack as a service. Data Stack is complex and evaluating tools and setting up the entire stack can be a challenging time taking process. There are low/no-code platforms that provide all the tools needed to go from data sources to interactive dashboards. Some of the emerging startups here are Selfr.io, Octolis.

Unravelling the Portfolio: 1K

Posted on by Kae Team

Brief about 1K

1K is a hyperlocal omnichannel grocery chain focused on fulfilling the aspirations of ‘Real Bharat’. The business was founded in 2018 by Kumar Sangeetesh, Sachin Sharma, and Abhishek Halder. The founders believe that Kirana entrepreneurs will play a pivotal role in building a sustainable channel to deliver wow micro-experiences to aspiring consumers of Bharat. The ultimate goal is to create a seamless flow of goods from brands to consumers and overcome the shortcomings of traditional distribution systems with the help of their in-house technology-enabled platforms and “smart” warehousing.

Vision and Mission

To revolutionise the grocery shopping experience for the non-urban population of Real Bharat.

Building “Bharat’s” first “omnichannel” distribution network that brings consumers’ aspirations closer to them.

Genesis

Two of the co-founders were working together at one of India’s largest logistics companies; they identified that one of the biggest struggles for brands was to reach and distribute their products in smaller towns of the country. Due to broken distribution networks, product availability has always been a massive issue in smaller towns/cities, despite rising customer demand.

Hence, they decided to solve this problem by making an efficient and cost-effective distribution model by aggregating the distribution rights of multiple brands.

Market Opportunity

Less than one lakh people inhabit 65% of towns in the country. There are about 7,000 towns with 5,000 to 100,000 residents. They are trying to serve a market worth a solid USD 150 billion. Their approach is distinctive in that it prioritizes grocery sale purchases, which account for 70% of consumer spending in such markets.

5-year Plan

Over the next five years, they want to increase their market share in these markets by 5%, making them one of the leading retailers in the country. It is crucial to keep in mind that more than 25,000 regional microentrepreneurs will support this as they develop the company and satisfy the customers’ needs in these areas.

Unravelling the Portfolio: TranZact

Posted on by Kae Team

Brief about TranZact:

TranZact is a freemium digitisation software for 14MN+ SMEs Manufacturers & Traders, empowering them by digitising business workflow right from sales to dispatch.
With scalable distribution and engaging software, they are capturing real transaction data, which becomes the foundation to build a transaction-backed marketplace at scale.

Vision and Mission:

Empowering SMEs owners to grow their business through digitisation.
Building a digitisation platform for 14MN+ SMEs to convert their business data into actionable insights.

Genesis:

TranZact started with the idea of creating digital technologies for 14MN+ SMEs, which are still struggling with very old digital technologies. They felt that in today’s era of digitisation, even though the SME space is often ignored, it remains a very large sector, and if there is specific technology built for this space, the impact will be much larger and deeper.

Market Opportunity:

14MN+ Indian manufacturers and traders

5-year Plan:

Going to build a transaction-backed market network platform with over $500MN in revenue coming from multiple revenue streams like software and transactions.

Wysa secures $20mn to address global mental health demand with AI digital Therapeutics

Posted on by Kae Team

 

  • HealthQuad and British International Investment (BII) join earlier investors W Health Ventures, Kae Capital, pi Ventures, and Google Assistant Investments.
  • Funds will enable access to clinically evidenced digital therapeutics (DTx) in the US, UK, India and other global markets.
  • Will enable further reach through multi-lingual support and access via alternative technologies.
  • Follows FDA Breakthrough Device Designation and clinical evidence of a Therapeutic Alliance.

Wysa, the leading AI digital platform for mental health, today announces it has secured $20M in financing. Wysa will use this capital to further expand into the US, UK, India and other global markets across enterprises, payors, and providers as well as improve wider usability through multi-lingual support and easier access via WhatsApp. The round is led by HealthQuad, who along with British International Investment (BII), the UK’s development finance institution, joins earlier investors W Health Ventures, Kae Capital, Google Assistant Investments, and pi Ventures amongst others.

Globally, there is a huge demand-supply gap in the mental health space. One in eight people in the world lives with a mental disorder, according to the World Health Organisation. With high treatment costs and limited access to qualified therapists, employers, healthcare providers and insurers are seeking ways to help people manage their mental health and well-being through clinically proven, cost-effective and scalable solutions.

Wysa uses AI (Artificial Intelligence) to triage users according to their personal needs, guiding them through appropriate, evidence-based CBT (Cognitive Behavioural Therapy) exercises within the app, towards other mental health services or crisis support. Wysa’s platform provides employers and health services insights into usage rates of Wysa and digital well-being tools while maintaining user privacy.

Wysa has achieved FDA Breakthrough Device Designation for its AI-based digital mental health conversational agent for adults with a diagnosis of chronic musculoskeletal pain and associated depression and anxiety. Additionally, clinical trials have validated Wysa’s efficacy and published peer-reviewed results show that therapeutic emotional bonds formed by Wysa are equivalent to human therapist relationships. The company has, to date, achieved a revenue-generating user base of over 4.5 million people across 65 countries. Clients include Accenture, Colgate-Palmolive, Aetna International, Swiss Re, the National Health Service (NHS) in the UK, and the Ministry of Health in Singapore.

Charles Antoine-Janssen, Chief Investment Officer, HealthQuad said: “We are thrilled to be part of the Wysa team. Wysa is developed in India and is marketed globally. The needs for Wysa are present all across, from high-income to low-income countries. Mental health triaging of patients using AI which is fast, effective and non-stigmatising for patients living in unaccepting societies answers a huge need in India, the rest of low-income Asia, Africa as well as the wealthiest countries of the world.”

“Wysa provides help across the care continuum – from the first point of access to digital therapeutics and companion alongside a clinician to ongoing monitoring & routine management thereby democratising access to mental health. FDA Breakthrough Device Designation status, user privacy further validated by Mozilla and real-time AI-CBT support makes Wysa one of the few clinically validated, privacy-focused and personalised solutions built for a global scale” added Ajay Mahipal, Director, HealthQuad.

Srini Nagarajan, Managing Director and Head of Asia at British International Investment added: “Good mental health is a crucial pillar for sound physical health which in turn promotes social and economic development. Through our investment in Wysa, BII is taking a holistic approach to supporting long-term productive economic prosperity by backing an innovative tech-enabled company that is increasing access to mental health services for low-income and rural individuals. We are excited to continue working with Wysa’s team to grow their offering and help improve health outcomes and quality of life for people.”

Ramakant Vempati, Co-founder, Wysa, said: “Wysa has not only been extremely successful as a consumer well-being platform but has also developed into a clinically validated, powerful tool to proactively manage mental health and well-being. Wysa meets people where they are, whether that means a little help with occasional workplace stress, right up to coping with debilitating pain, depression and anxiety. With this funding, we look forward to scaling up further and helping millions of more people.”