Every founder dreams of the perfect launch day, the moment your digital product goes live and the world beats a path to your door. But then… *crickets*. Just because you've built something great doesn't mean people will automatically find or buy it.
The numbers show why this is a problem - around 42 % of startups collapse because they build something nobody needs (FF). If you are trying to get a digital product off the ground, throwing money at generic marketing burns time and money. People search in different ways, it costs more to get a customer, and the market is packed. The companies that succeed are starting to use AI in their sales and marketing to really understand their audience and give them what they need.
This article will talk about useful tools and what it takes to bring a digital product to market.
Natalia Loza, Product, Commercial, and Fundraising expert
The old way of doing things (build a buyer persona, pick a few popular channels and push out content) was always a bit of a guesswork. It maybe worked when there wasn't as much competition and people paid attention more easily.
Now, companies that frequently use AI turn 56% of free trial users into paying customers, while regular software businesses only convert 32% (Saastr). This shows that how people find, check out, and start using digital products has changed a lot. The trouble with old school tactics is they focus on *who* the customer is, not *what* the customer *does*. It's easy to collect things like age, company size, and revenue but that doesn't tell you why people buy, or when they're ready to buy.
Start with Apollo or Linkedin Sales Nav to get a list of potential customers (e.g. hiring and fast growing companies within your target industries).
Then enrich it with behavioural indicators rather than just names and company sizes. Tools like Clay or Clearbit get data from a variety of sources: what tech a website uses, how fast they're hiring, if they announced funding, and what other tools they use.
Say you're selling tools for developers. Look for companies that just hired a bunch of engineers, started using platforms like Vercel, and got funding. These things suggest they are ready to put money into tools that help them grow, which is way better than knowing they have 50–200 employees.
Set up Google Alert for:
If it matters what tech they use, use BuiltWith to see what tools they have.
By putting all this together, you can find the right companies: e.g. those hiring to grow, using the right tools, and that just got funding.
Digital products often solve general problems. Markets that act like your best customers but are in different fields can be a great chance.
Use Google Trends and Exploding Topics to find industries where people are searching for related things more and more. Then, see if their tech is like what your current customers use, to guess if they're a year or two behind in going digital.
Let's say your tool helps online stores automate emails to customers. You might see that hospitals are searching for similar tools. They have the same problem but less competition.
Before you put too much effort into new markets, you could try small tests. Spending £500–£1,000 on ads on LinkedIn, Google, or Meta (depending on your customer) can give you good data. Spending about £10 per campaign per day for a month works well. For the best info, run three campaigns at once, but that can cost more. Target people in these related fields to see if your message works and if they become customers like your main market. Test what you say is good about your product, and track how much it costs to get clicks, how many people click, and how many try your product, compared to your regular market.
Forums, Discord servers and Reddit threads are where potential customers talk openly about their frustrations. Try tools (like Hexofy) to copy posts discussing problems your product fixes.
Scrape poor reviews of your competitors from sites like G2 and Capterra. These usually have the most honest thoughts about what's missing, what problems they have, what they want, and the words they use.
Feed these posts/reviews into ChatGPT/Claude and ask it to pull out the exact sentences customers use to describe their pain, including any feelings and comparisons they make.
You'll get a list of the words customers use, that shows how different groups talk. For example, big business buyers might say operational scaling is hard, while founders say we spend too much time doing things by hand. Use these phrases to make your messaging more resonant.
Once you know who you're looking for, find out where they are and what gets their attention. See why your competitors' messages work.
Start with tools like SimilarWeb, Semrush, or Ubersuggest to see what brings people to your top competitors. Don't just look at the numbers, see which channels are growing, as that means your competitor is putting more effort there.
Also, use the Meta Ad Library and Google Ads Transparency Center to see the ads your competitors are running, what they're saying, and how they show it.
Collect their best content and analyse it with ChatGPT with a prompt like: “Identify the emotional trigger, logical argument and specific objection addressed in each piece, and indicate whether it focuses on features or outcomes.”
This shows why those messages work and what they're missing. For instance, you might see that competitors talk about being efficient but never about how they connect with other tools.
Generic messaging like “We help you work smarter” fail because they speak to everyone and no one. The secret is to use the exact words your customers use in your writing.
Beyond social media posts and reviews, record calls (even if just early interviews) using tools like Otter.ai (I use Fireflies because it's more correct and lets you name who's talking). Transcribe what was said and put it into ChatGPT to pull out:
Phrases describing pain points (including emotion and comparisons)
Organize it by group and how strong the emotion is. When you write a web page or email, use phrases that fit the group you're talking to. For example, instead of saying “Save time with automation,” you might say, “Stop burning hours in spreadsheets,” if that’s how your customers talk about their problem.
Regular email sequences don't pay attention to how people really buy. Tools like Customer.io, Klaviyo, or ActiveCampaign let you send different messages based on what users do.
Create micro-segments, like:
Use Posthog/Hotjar to see where people leave your site using heatmaps. Put this data into ChatGPT: "Based on this heatmap showing 60% of visitors leaving at the pricing section, generate 5 alternative headlines and value propositions addressing pricing anxiety.”
Create different versions of your site for different people using Unbounce, e.g. LinkedIn visitors need different messages than Google Ads visitors. Test messages that talk directly about the things that make people hesitate, based on your data.
Tools like Mutiny or Replo (especially for Webflow/Shopify) also let you change websites for different people automatically.
Make a small community (like Slack or Discord) where early customers can share thoughts and questions. This is like a live focus group for testing messages, getting feature ideas, and finding people for case studies.
Copy the chat logs often (or use Zapier to log new messages in a Google Sheet) and put them into ChatGPT: "Read these messages and summarize top recurring pain points and feature requests by frequency and sentiment." Services like Dots also have AI that can do things when something happens, show trends in the community, and automatically find influential members.
Many digital products fail because people don't start using them, not because they don't get enough customers. Once you launch, track how long it takes users to get value using Mixpanel or Amplitude. See where users stop in their first session and make email sequences to help.
Use Customer.io to trigger helpful content when users get stuck on certain steps.
Random A/B tests on button colours won't do much. Make tests meaningful by focusing on what will have the biggest impact and learning what works.
The classic ICE score (Impact, Confidence, Ease) is too simple for digital products. PIERCE adds three things and makes prioritizing easier.
For every idea, rate each of these six things from 1 (low) to 5 (high). Multiply the scores to get a number - the higher the number, the better the experiments.
For example, a social proof section might score: Probability 4, Impact 3, Ease 5, Reach 5, Confidence 4, Engagement 3. Compare this to other ideas to test the ones with the most impact first.
After running experiments, measure success by a single main goal that shows the value of your product, like trial-to-paid conversion, weekly active users, or retention in the first week. This makes sure AI-driven tests are working towards things that matter, not just vanity metrics.
Platforms like Statsig and Klaviyo have A/B testing built in. Choose what to test, and they automatically show different versions to different people, track conversions, and pick winners when there's enough data.
Ask ChatGPT for advice: "We get 500 trial sign-ups monthly and want to know which landing page headline converts better. How long should we run the test for confident results?”
After the test, give it simple numbers (like subject line A got 120 clicks from 1,000 sends, subject line B got 150 clicks) and ask what it sees. ChatGPT finds trends, like what group responded better and why, making it easy for non-tech teams to experiment.
Use Zapier or Make to build an idea machine. Each month, put recent product usage data, interview notes, and support tickets into one place. Ask ChatGPT to come up with experiment ideas scored by PIERCE. Put the best ideas into your Notion or Airtable backlog.
You might, for example, find that social proof experiments work better than pricing tests, and decide to put more effort there.
Don't try to do everything at once. While most tools have free options, it will cost at least £300-500 a month to start scaling. The trick is to start small and build slowly.
Start with one area where AI can help your business right away:
Natalia Loza is a product, commercial, and fundraising expert with a proven record of taking digital technologies from concept to revenue to exit — including software that broke even in four months and tools generating over £600k in six months.
She also founded Connected.Ventures, a 300+ member network of UK tech innovation leaders, and mentors for organizations such as Foundervine, OneTech, and Techstars. Natalia also advises global networks on technology strategy and, as a UK Tech Innovation Delegate, represents the sector at international events including global entrepreneurship conferences in the USA and Italy.
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