Issue#67: Building $1K - $10K MRR Products around Contextual Data & Research As A Service
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No fluffy content. If your goal is to build a $100m ARR business, this is not the right post. Here I am are NOT going to talk about building the next Facebook or Twitter. If your goal is to make a $1K to $10K MRR, continue reading.
This post will cover one SAAS area and talk about multiple niches in this space. This post also explains how to do tech implementation, do market analysis, how the current players are doing, and ends with a cost analysis to understand the overall cost for 100 users.
Heard of ‘Contextual Data’? - Contextual data is the background information that provides a broader understanding of an event, person, or item. This data is used for framing what you know in a larger picture. These relevant facts can be utilized to analyze your customers' behavior patterns, thereby improving their experience.
‘Research as a service’ is more about pulling the data from various sources and building a context for the data and providing the contextual data to users.
Many profitable starts ups around Data provide access to data and charge a recurring fee or just pull the data every week/every month and charge for sending the data (Research As A Service)
TheSEOLabs: The data of guest posts list to grow businesses. Find new guest post opportunities with more than 15000 blogs that accept guest posts, with contact information and SEO metrics.
GetCyberLeads: The easiest way to get the data of new clients for digital agencies. Get data about 1,000+ handpicked companies that just raised millions and are looking to outsource.
ExplodingTopics: ExplodingTopics data helps investors and entrepreneurs find exploding trends before they take off. ExplodingTopics was started as a small side project and got acquired eventually and now making significant revenue.
NewsData: The Platform to search, collect and track worldwide news. Get live breaking news or search historical news data for the past 2 years from 3000+ sources using NewsData.io API. Collect the data in JSON or Excel Formats.
BuiltWith: Find out what websites are Built With. Get the data about the Tech stack of various websites. The estimated revenue is $14M/year.
GetLatka: GetLatka captures the revenue data of SaaS companies and sells the data access for a monthly subscription.
NewsletterSpy: Gain valuable insights into the performance of over 100,000 newsletters. Study the critical trends, discover sponsorship opportunities, and find acquisition targets. Charges about $300/year for data about newsletters and their insights.
Wappalyzer: Find out the technology stack of any website. Create lists of websites that use certain technologies, with company and contact details. Use the data for lead generation, market analysis, and competitor research. Highly profitable.
LeadFuze: A Search Engine for Leads. Forget about bad data. Third-party data partners + LeadFuze’s own crawling allows AI to aggregate, match and verify real-time company info, emails, mobile numbers, social profiles, and more across 500+ million profiles and 10+ million companies.
UnderTheRadar: Monitors hundreds of sources to surface ideas, startups, apps, websites, and markets that are about to take off. Dozens of new trends every week. Profitable and charges $240/year.
IcyLeads: Icy Leads is a fully-packed cold outreach toolkit that helps you generate lists of hyper-targeted sales leads, send cold email sequences, and book more meetings with your ideal prospects all under one dashboard.
AnyLeads: The leading platform for lead generation. Data enrichment, email finder, local businesses extractor, email scraping, cold email automation, lead scoring - all in one place.
ScopeLeads: Automate the lead Generation and cold emails. Find leads and outreach in seconds with personalized, effective emails.
VisaList: The complete data about visas and restriction. Find the data about visa requirements and document checklist for 238+ countries. Crossed $5500 MRR.
Uplead: B2B Prospecting with 95% Data Accuracy Build prospecting lists free from dodgy data, bad-fit buyers, and low-qualified leads. UpLead made $8M in sales by providing quality leads. See here - a great Twitter around this about UpLead.
Hunter: Hunter lets you find professional email addresses in seconds and connect with the people that matter for your business.
🔒 👉 [In Pro] See which company crossed $6K MRR by sending leads to the agencies.
🔒 👉 [In Pro] See which company is making $300K in revenue per year with data of SaaS companies.
🔒 👉 [In Pro] See which platform for lead generation has an estimated revenue of $2M per year.
🔒 👉 [In Pro] See which who is having an estimated revenue of $17M per year from data about emails.
🔒 👉 [In Pro] See which company’s estimated revenue is $30K MRR with close to 200 customers from Leads data.
🔒 👉 [In Pro] See who is making $550 per month with data of guest posts list.
🔒 👉 [In Pro] See which company’s estimated revenue is $25K MRR with close to 1K customers.
Negative Nancy says - I can scrape my own data and I can write my own crawlers.
Me - You can. But that may not be worth your time. Instead spend time on what you can do with the data.
Negative Nancy says - The churn rate is usually high when I charge monthly access to data. People often get full access to data, download and cancel subscriptions.
Me - There are multiple ways to solve this. Charge a full yearly fee without a monthly option. Another alternative is to provide a few credits on a monthly subscription so that customers can only unlock limited data with the available credits. To reduce churn, add more value to the offering by sending weekly updates, keeping the database up-to-date, and by building a community if possible. Other things like Podcasts with niche influences etc will also help reduce the churn.
Deep-dive & Some niches
Data is powerful. Charging for the data is not a new model. For years, companies have been charging for access to data. Having the access to data is an unfair advantage as it helps to take decisions quickly and make certain tasks easy. Let’s see some of the possible tools in this space.
Data about new trends: Create a tool that can capture the growing trends before they gain traction. For example, see companies like ExplodingTopics making thousands of dollars in revenue with this model. ExplodingTopics was started as a small side project and got acquired eventually and now making significant revenue. Wondering how ExplodingTopics started as a side project? This is a comment from the founder - “we monitor lots of different places like search, shopping, online communities looking for interesting topics and then we cross-check that against Google Trends data and curate topics ourselves.” Gimpse is another solution in this space that is making considerable revenue by predicting trends.
Data about SaaS/Micro SaaS companies: There are hundreds of companies coming up daily and there are only a few making revenues consistently. Track the companies that are profitable and are generating revenue. You can find this from various sources like IndieHackers, searching on Internet, following founders on Twitter, going through ProductHunt, finding hashtags like ‘BuildingInPublic’, Founder Interviews, Case studies from the internet, etc. Consolidate the data from these sources and create a single place for data about the revenue of the SaaS companies. You can pick a single niche or you can pick multiple niches. Keep tracking the data and sell this data to subscribers. You can either charge a one-time fee or a recurring charge. For example, companies like GetLatka, CrunchBase make millions of dollars in revenue with tools like these that consolidate data about companies.
Data about Tech Stack of websites: Finding the tech stack of the websites and then gathering/consolidating the data about the tech stack of these websites is a great data asset. BuiltWith that helps to find out what websites are built with and helps get the data about the tech stack of various websites has an estimated revenue of $14M/year. Wappalyzer is another highly profitable company solving the same problem. The beauty of data consolidation is that, as the data volume grows, the value of the data grows exponentially and the maintenance cost remains the same. For example, BuiltWith was run with a single employee and grew to $14M/year. Create a data platform that gathers data about the websites and consolidates the data under one platform. With the advent of cloud technologies, automating this is possible to a larger extent.
Generic Lead generation tools from Social Data: One of the most important things that any company, whether it's a startup or an established organization, has to do is lead generation. There are all sorts of programs and channels that many companies use to get leads for products and services. Create a Micro SaaS solution around lead generation tools. One of the biggest problems for B2B companies is finding quality leads. This could include a lot of things like scraping for information, scraping specifically from LinkedIn, mapping the data from various sources to update email, phone number, designations, etc. Automate this process and create a high-quality list of leads with verified company designations, emails, and phone numbers. B2B companies love to have high-quality lead lists. UpLead made $8M in sales by providing quality leads. See here - a great Twitter around this about UpLead.
Data about Emails: Finding emails of a person from a specific company is tough. While there are many tools for larger companies that scrape LinkedIn and build a database, there are not many tools around an ‘email search’ across the web. Imagine you want to search for all contacts under xyz.com. This gets more complex for email contacts on relatively newer websites. For established companies, it might be easy as there will be other places like LinkedIn where you can find the data. Create a search solution that can pull email data from web pages. This means you need to write web scrapers that can just extract the emails info from various web pages. Over a period, you will have millions of contacts available for thousands of websites. Hunter is doing well in this space with an estimated revenue is $17M/year.
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Technical chops
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Marketing chops
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Cost Analysis for 100 customers
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