Issue#84: Building $1K - $10K MRR Micro SaaS products around A/B Testing Methodology
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Micro SaaS News this week in 2 minutes
(This saves you hours of time and keeps you up to date on what's going on in Micro SaaS.)
Remote Rocketship, a job board for remote jobs by Lior Neu-ner hits $1,000 MRR.
Our Micro SaaS HQ Pro-member Anton launched ChatYourDomain, an AI-powered chat interface that simplifies the process from idea to available domain.
Tom crossed $100 MRR from his iOS app Aiva: AI Virtual Assistant.
Nick crossed $9K MRR, without any ad spend, with Movevirtual, a platform for hiring off-shore growth assistants.
JobBoardSearch by Rodrigo Rocco ****reaches $16,308.10 or $1,359/mo. Here’s the founder’s earlier interview on FounderBeats.
Bruno Hills shares how he grew Featurebase to $2,500 MRR.
AI tool BBLY hits $3K MRR within the first month of launching.
WebMagic AI by Ryan Morrison hits €693 MRR and crossed 91 paying customers.
Hailey Ellis-Kelley had a $30k exit from Podcast Production School, a digital course + membership community.
Dan got 35 students and $53,000 in sales for a Build a GPT-4 chatbot course.
Let’s see today’s Newsletter around a Micro SaaS niche.
No fluffy content. If your goal is to build a $100m ARR business, this is not the right post. Here I am 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, and how the current players are doing, and ends with a cost analysis to understand the overall cost for 100 users.
A/B testing is a method of comparing two versions of a product or website feature, called "A" and "B", to determine which one performs better. This is commonly used in website design, marketing, and product development to measure the effectiveness of changes and make data-driven decisions. For example, a company might create two versions of a website's homepage, one with a red "Buy" button (version A) and one with a blue "Buy" button (version B). They would then randomly show the two versions to different groups of users and measure which version leads to more purchases. The version that performs better, as determined by the chosen metrics, would be implemented for all users.
Many people think that A/B testing is meant for just website testing where you present two different designs of websites to different sets of users and see which one has a better conversion rate.
Let’s see what the various models built around A/B Testing methodology and how they are generating revenues.
Birdy: Birdy helps you optimize your Twitter profile with automated A/B testing. Create two profile versions and let Birdy determine which one converts more visitors into followers. Built by Maxime Dupré in 2022. Currently at $450 MRR
ThumbnailTest: Helps users to A/B test thumbnails and titles live on YouTube. Founded by Rox in 2022. Reached $200 MRR in just 1.5 months with 15 paying users.
Ship Scout: Ship Scout enables Shopify merchants to test different shipping rates & free shipping thresholds on their Shopify stores. It lets merchants target tests by destination and see real-time test results. Founded by Ben Kennedy and Conor Parrish in 2020.
Chameleon: Set up A/B tests for product tours in Chameleon, and use the insights to increase revenue through better onboarding and feature activation
Founded in 2015 by Brian Norton and Pulkit Agrawal. Received $14.9M in funding.
Dexter: Dexter is a Shopify app that enables you to increase your average order value simply by finding the best price for your product through A/B tests. Dexter let you price-test a product simultaneously in a given time and not just the basic AB tests – v1 for week 1, v2 for week 2, and so on. It also monitors the revenue per 100 visitors to ensure you know which price is doing well in one glance. Dexter was launched in July 2020 and acquired by Staytuned in May 22
Upflowy: Upflowy is a drag and drop no code tool to build and optimize web experiences. Easily A/B test signup flows, sales lead funnels, customer on-boarding and more. Experiment with new copy, new images and new assets to better optimize your flows. Founded in 2020. Received $5M in funding
Botanalytics: A conversational analytics software that helps you get deep insights on how people interact with your business via text or voice. Conduct A/B tests with different funnels. Received $1.3M funding
MeetEdgar: Social media management tool that also lets you monitor and A/B test variations to see what resonates best with your audience across multiple social networks. Founded by Laura Roeder in 2014, who bootstrapped it to $4MM in ARR in 2.5 years
Appcues Design, deploy, and test captivating onboarding experiences. Perform an A/B test to measure the effectiveness of multiple versions of an experience in parallel. Checks if users are more likely to engage with a slideout containing a gif or a static photo? Checks if users like a tooltip tour, or would they prefer one modal containing all content. Estimated annual revenue is currently $25.8M
Unbounce: Unbounce’s landing page builder has now AI-powered split testing tool called Smart Traffic. It sends visitors to the landing page variant where they’re most likely to convert. It analyzes which variant performs best for different types of visitors based on things like their device, location, browser, etc. Unbounce was bootstrapped in 2009 by Rick Perreault and others. Received $39.1M in funding. It has hit $25.9M in revenue with 14K customers in 2022.
Crazyegg: An analytics platform with A/B Testing for website optimization. Try experimenting with different headlines, sales copy, or product descriptions and quickly learn which idea converts the best. Estimated annual revenue is currently $5.2M
ABTesting: Automate A/B Testing. Boost conversions on landing pages with the help of AI. The easiest, fastest, and most efficient way to A/B test.
Mailerlite: Email platform with feature to do A/B test with different email elements like subject line, sender name as well as the content. Helps test variations of all aspects of content including headlines, images, CTAs, and more to gain valuable insights into what subscribers like and optimize click rates. Founded in 2010 by Eimantas Norkunas and Ignas Rubežius. Reached $12M in revenue in 2022.
Splitbee: Splitbee lets you create and run experiments on your page. Compare multiple variants, try different wordings, swap buttons, images and more to find what works and increase conversions. Founded by Tobias and Timo Lins in 2020. Acquired by Vercel in October, 2022
FlagShip: Faster and Safer Releases through Experimentation. Engineering teams deploy continuously and monitor the impact of features on technical infrastructure, while product teams control how features are released and their impact on users' experience and business KPIs.
ConvertKit - ConverKit's email marketing tool helps to test two different subject lines to 30% of email subscribers list and automatically deliver the winning copy to the rest. Founded in January, 2013 by Nathan Barry. Crossed $2.79M MRR
Shogun: Build optimized ecommerce pages for Shopify, faster without code. Design and A/B test Shopify landing pages, blog pages, product pages.
Negative Nancy says: A/B Testing can only be a feature of big products but not a product by itself.
Me: Not really. Now, most people are preferring simple tools that can do one thing but at their best. For example, see Birdy that does one thing at its best: Optimizing Twitter profile. Birdy is currently at $450 MRR. The same is the case with ThumbnailTestwhich helps you A/B test thumbnails and titles live on YouTube. ThumbnailTestcrossed $200 MRR in just 1.5 months with 15 paying users.
Negative Nancy says: But I want to build a full-blown product but not just A/B testing product.
Me: You can start with A/B testing for a given niche and once you have an audience, you can add more features to your product. For example, A/B Webpage Testing is only a feature in Splitbee. A/B Testing for Social Media posts is only a feature inMeetEdgar. A/B test with different email elements like subject line, and sender name is only a feature in Mailerlite.
Opportunities in this space
Let’s see some of the opportunities in this space.
Website Builder that supports A/B version that gets generated automatically: Building a working website is often challenging for any founder. Founders often test various versions of their website by changing the titles, colors, and various combinations to see what works the best. Create a Micro SaaS website builder that supports the automated generation of various website samples from one base sample. This hugely saves a lot of time for customers as they create one version and get dozens of versions just to choose or let the custom domain feature has inbuilt A/B testing that tests the selected versions. For the interested, Flezr NoCode Builder will eventually have this feature to generate various versions of the page/text/content from one base design/page. You can also plugin AI for this. Create a website builder that runs on AI to generate most of the elements and get the users up and running as fast as possible. When a new website is created, most of the users spend time creating logos, writing headlines, correcting images, etc. Create a tool around this that can do all these based on AI and attach this as an add-on to the Website builder. See Zyro for some inspiration. The landing page builder Zyro comes with an AI Logo Maker, AI Business Name Generator, AI Heatmap, AI Content writer, and a lot of tools based on AI. Annual revenue for $4M. To improve this model further, you can also automate A/B testing with a couple of variations and show the metrics to customers.
Generating E-commerce descriptions: There are thousands of e-commerce companies and one of the biggest problems for these companies - is “Writing the Product titles and product descriptions”. Writing the titles/descriptions doesn’t just mean merely writing but also validating with various A/B tests and multiple variations to see which text is giving higher ROIs and better SEO. Create a Micro SaaS tool based on AI that can automatically generate multiple variants of titles and descriptions for a given product. The Micro SaaS tool should be able to generate titles/descriptions for thousands of products. To start with you can let users upload a file with some data and create AI-generated data and ask the users to download the generated file But in the long run, you need to automate this and integrate with various e-commerce providers and add this as an Add-on on their marketplaces. Integrations with Shopify, Magento, Woocommerce, etc will make it much easier to get more paid users. Perci started in this space and started growing and is currently at $300 MRR.
A/B Testing for Social Media Publication based on historical data of the user’s posts: A tool that uses historical data of a user's social media posts to help with A/B testing for social media publication can provide several benefits to businesses and organizations looking to optimize their social media marketing efforts. Here are a few ways it can do that:
Personalized testing: Analyze the historical data of a user's posts to understand their audience, engagement, and performance, and use this information to personalize the A/B testing for their specific needs.
Identify best-performing elements: Use the historical data to identify patterns and trends in the user's posts, such as the best time of day to post, the type of content that receives the most engagement, and the most effective call-to-action.
Automate testing: Automate the process of running A/B tests on different elements of the user's posts, such as headlines, images, captions, hashtags, and calls-to-action, making it more efficient and less time-consuming.
Historical data analysis: Provide insights and analysis of historical data to understand the behavior of the audience and make adjustments to future posts.
Optimization: Use the data from the tests to automatically optimize the user's posts, making changes to improve their performance over time.
Predictive modeling: Use historical data to predict the performance of future posts, allowing businesses to make data-driven decisions about when and how to post.
Overall, a tool that uses historical data of a user's social media posts can help businesses optimize their social media marketing efforts by providing personalized testing, identifying best-performing elements, automating testing, historical data analysis, and predictive modeling.
Feature Flags Automation: Feature Flags Automation is a set of techniques and tools used to manage feature flagging or the process of toggling software features on and off. Feature flags can be used to quickly and safely deploy new features, perform A/B testing, and control access to features. Feature flags automation tools help developers, product managers, operations, and QA teams manage the entire process of feature flagging, from creation to deployment to monitoring. This can help speed up the process of releasing new features while reducing the risk of deployment. In its simplest form, you can enable/disable a feature in your code by turning on/off options in the console. There are several SaaS tools available for feature flag automation, which allow businesses to release new features to a subset of users, track their performance, and make data-driven decisions about when and how to roll them out to the rest of their user base. Some examples of these tools include:
LaunchDarkly: A feature flagging and experimentation platform that allows businesses to test and roll out new features, track performance, and improve collaboration between development and business teams.
Split: A feature flagging and experimentation platform that allows businesses to test and roll out new features, track performance, and optimize the user experience.
ConfigCat: A feature flagging and experimentation platform that allows businesses to test and roll out new features, track performance, and optimize the user experience.
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