Wanna know the secrets to building AI software that sells? If you’ve got an awesome idea for an AI Software, and you want to make sure it’s actually going to sell before you start building, this post is for you! I’m going to show you 5 easy ways to make sure that your AI software will be a success BEFORE you ever write one line of code.

At the end of this post, I’m going to share the exact process I used to bring in $68k in revenue within the first 2 weeks of launching my last product. That was a pre-sold product, sold in December of 2020 and released in Jan 2021 – so I know that this approach works in 2021.

YouTube URL:​ https://youtu.be/JM_ALyIs6G0

If you prefer to read instead of watch then, read on…

For the best data leadership and business-building advice on block, subscribe to my newsletter below and I’ll make sure you get notified when a new blog installment gets released (each week). 👇

Ready to become a better data leader or entrepreneur...

(without needlessly spending years on trial-n-error approaches)?

If yes, this newsletter is for you. Drop your details in the box below and we will be in touch!

First data-safety lesson: Always read the fine print!! Don't worry - we don't sell our data - so your data is safe with us. Also, we are committed to you having a spam-free experience! Powered by ConvertKit

Why am I qualified to say anything about building AI software that sells? Well, I’ve been selling data science products since 2014…to the tune of 6-figures in profits per year, just from data products alone.

My name is Lillian Pierson and I support data professionals to become world-class data leaders and entrepreneurs.

If you’re reading this, you probably have an awesome idea for an AI startup or an AI software  –  and what we need to do is to make sure that you’re actually starting with consumer needs and not technology. To validate your focus, that’s going to require market research…

Phase 1: Market Research

I’ve been updating my book Data Science for Dummies lately and when I was looking at tools that I recommended in 2016, I found that most of them are now extinct. In other words, they’re not supported anymore, the websites are down and the businesses are no longer operating.

I’m sure that the people who created these tools were smart people but they had the wrong focus. So what I want for you is to focus on monetizing and then building and it all starts with MARKET RESEARCH.

After you have researched your AI software idea, do your market research and make sure that:

  • There is a need for it in the market 
  • That people are willing to pay to have that problem solved
  • There’s not too much competition

After you’ve nailed down the exact niche of who you’re going to help and how you’re going to help them, AND made sure that there’s a demand and not too much saturation, then you will be ready to start delivering.

Phase 2: Sell & Deliver the Service 

Selling services is the fastest way to monetize your data business. Another added benefit is you can get paid and earn money while building your software. You can also build your business and your tribe of your future software users while you’re actually building them the product.

Here’s what you need to do: 

  • Deliver the AI SaaS as an ML service
  • Sell it to customers
  • Optimize the processes
  • Tweak it to better fit on-the-ground needs of your ideal client

AI software idea

 

Phase 3: Build your Business while you Build your SaaS 

This would take anywhere from 12 to 18 months, but because you’ve monetized your services, you don’t have to worry about hitting the market fast because you have some leeway – you have some budget in order to bring in a team that can help you develop your product faster and make your business more scalable.

So you’re basically growing your customer base while making money from your machine learning services. 

Now, it’s time to do the following: 

  • Reinvest some of the money you earn
  • Hire a team
  • Save money for operations & maintenance
  • Have an extra budget
  • Build up your social media and email list
  • Hire launch help!

Phase # 4: Pre-sell Your AI SaaS 

How do you make sure that your product release is profitable? 

This is why you will need an email list of your prospective clients, as well as, a bank of clients you’re already working with – because these are the people who will likely pre-purchase your product before it’s actually ready for release. This is also why it’s important to build trust by contributing to your community, posting blogs and getting to know your customers via email marketing, so when this time comes, they will be ready to work with you and try out your product. 

What you’ll need to do:

  • Pre-launch to your list
  • Offer them an extra bonus for signing up early – probably a custom configuration set-up or support that you can give them for free because they trusted you
  • Set a release date
  • Create your launch content

This pre-launch will probably last about 2 weeks – launch privately inside your email list and then you can start working to get these pre-sales about 5 weeks before the official release of your product. 

Speaking of selling data science services If you want to learn how to sell yours for $300/hour or more, then check out this video I did on Consulting Rates for Online Data Analytics Services in 2021.

Now peeking back up, so far you have done  market research, started delivering AI SaaS ideas as a machine learning service, started building your SaaS product as you deliver your service and you have pre-sold your product.

Now it’s time for you to launch your product!

On this 5th step, I will show you how to do a profitable launch so when your product is released, you are rolling in the moolah…

Phase # 5: Product Launch

Remember we discussed setting your product release date? Great! Take that product release date and back calculate 8 weeks prior, because that’s when you need to start working on your launch.

Let’s look at the timelines:

T – 8 weeks: Create your launch storyboard: Map out the content you’re going to share each day of the launch and because you’ll be launching a new product, you probably want to release for 3 weeks. You want to think of content ideas for anywhere between 16-21 days depending on how frequently you want to publish your content during your launch. 

T – 7 weeks: Create your email copy: You need to put together about 14-16 emails for your customers – they follow your storyboard and they help sell your product. It’s probably going to be about 40-60 pages of email copies written out.

T – 6 weeks: Create your launch event copy: Anytime you’re launching a product, you want to make sure that you are showing up and doing live events that will help build trust. Offer free mini-trainings that will get mini-transformations for your target customers and ideal clients which will give a little taste of what it’s like using your product. Make sure you have your copy in place for all the live events – may it be a webinar, 5-day challenge or a live Q&A event. 

T – 5 weeks: Create your social posts: Take the email copies you created and repurpose it to social media posts.

T – 4 weeks: Schedule your content: Get all your copies pre-scheduled as much as possible so you don’t have to worry about publishing stuff. I also want to advise you to leave a gap here just because crap happens and you need to leave a little wiggle room on your launch calendar, always.

T – 3 weeks: Warm up content: Start publishing some of the content you created – these warm up content should demonstrate your expertise as a solution-provider in your niche and start building people’s trust and kind of give them an idea that something’s coming.

T – 2 weeks: Launch event promo: Start promoting that launch event part and get as many people as possible to sign up.

T – 10 days: Launch event: Hold the launch event and unveil your new AI SaaS product available for purchase at the very end. You want to give people some sort of early bird bonus for signing up early, especially since your product isn’t officially released until the end of the launch, which is gonna be 10 days later. 

T – 7 days: Early bird ends: End your early-bird pricing.

T 7 – 4 days: FAQs: Do FAQ type of content to help people make the decision of whether or not they want to get the special deal you’re offering.

T 3 – 0 days: Last call: Do a real push and let people know that they might be missing an opportunity to be an early adopter of this new product. This is probably where you’re gonna get 70% of your sign ups.

Product release date: Make sure that you have your team ready and in-place to help support you and all of the customer service inquiries that will be coming in as people start using your products. Be prepared for that by hiring support before you actually start launching so that when you need admin people in place, they are prepared, trained and ready to go and you can have a seamless customer experience for all of your clients.

 

If you’re digging all these tips and tricks on building AI software that sells and how to make money for your artificial intelligence expertise, then I’m sure you’re going to love my FREE Data Entrepreneur’s Toolkit

It’s an ensemble of all of the very best, most efficient tools in the market I’ve discovered after 9 years of research and development. A side note on this, many of them are free, or at least free to get started, and they have such powerful results in terms of growing your business. These are actually the tools we use in my own business to hit the multiple 6-figure annual revenue mark.

Download the Toolkit for $0 here.

You may also love it inside our Data Leader and Entrepreneur Community on Facebook. It’s chalked full of some of the internet’s most up-and-coming data leaders and entrepreneurs who’ve come together to inspire and uplift one another. 

Join our community here.

Hey, and if you liked this post, I’d really appreciate it if you’d share the love with your peers by sharing it on your favorite social network by clicking on one of the share buttons below! 

 

NOTE: This description contains affiliate links that allow you to find the items mentioned in this article and support the channel at no cost to you. While this blog may earn minimal sums when the reader uses the links, the reader is in NO WAY obligated to use these links. Thank you for your support!

Lillian Pierson, P.E.

Lillian Pierson is a CEO & data leader that supports data professionals to evolve into world-class leaders & entrepreneurs. To date, she’s helped educate over 1.3 million data professionals on AI and data science. Lillian has authored 6 data books with Wiley & Sons Publishers as well as 8 data courses with LinkedIn Learning. She’s supported a wide variety of organizations across the globe, from the United Nations and National Geographic, to Ericsson and Saudi Aramco, and everything in between. She is a licensed Professional Engineer, in good standing. She’s been a technical consultant since 2007 and a data business mentor since 2018. She occasionally volunteers her expertise in global summits and forums on data privacy and ethics.

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.