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Last month I partnered with ChartMogul and ProductLed to analyze new conversion data from 200 B2B software products. The findings demystified the economics of free products and the user journey in 2026.

The TL;DR if you missed it:

But this data only tells half the story. Readers also wanted to know how to improve free-to-paid conversion, which remains one of the highest-leverage ways to grow revenue. Even a modest 1 percentage point improvement in free-to-paid conversion equates to a roughly 15% increase in new revenue per trial.

This follow-up report takes a data-driven look at what’s working to improve conversion with insights on tactics, tech, marketing channels, pricing, and sales touchpoints. Most of the tactics highlighted here don’t require more marketing spend or new headcount.

The survey was conducted in January 2026 and included 200 software products. A typical respondent is between $1 to $10 million ARR with an average revenue per customer of $50-$249 per month and a year-on-year growth rate between 25-50%.

43% of survey participants improved free-to-paid conversion over the past 12 months. They most often saw modest gains of 10-25% (one-third of participants) although one-in-ten improved conversion by 25% or more.

We asked participants for their highest-impact growth experiment or tactic, collecting 30 experiment ideas after consolidating duplicates.

Five key focus areas emerged to help you prioritize growth bets:

In my experience, the fastest path to higher conversion doesn’t involve changing the product itself. It’s about attracting more of the right users in the first place.

Organic signups from search, referral traffic, social media, and LLMs convert at the highest rates, according to the survey. Signups from paid marketing (ex: paid search, display, Meta ads) convert at the lowest rates. The immediate action items: (1) expand organic acquisition efforts to their max capacity (which is easy to say and hard to do as SEO has declined) and (2) get more precise with performance ad targeting and paid search campaigns.

LLM optimization (referred to as AEO) and mid-funnel SEO was mentioned by several survey participants. At Webflow, profiled earlier, ChatGPT traffic converts at 24% (!), which is 6x higher than Google. Some tangible examples from the survey for expanding organic acquisition efforts via SEO and AEO:

Better performance advertising starts with reverse engineering the characteristics of the highest-converting users. Fyxer, for instance, noticed that work email signups had a 10x higher LTV compared to personal email users.

Campaigns can then be optimized to get far more precise at bringing in these exact users. In the words of one survey participant, “We invested in paid traffic with the right ICP. It was scary how precise the thing got.”

New users are, in a word, impatient. There’s a narrow window to impress these users and convince them to invest sweat equity into the product.

Faster time to value comes down to (a) reducing friction and (b) increasing a user’s motivation to overcome friction.

In my experience, the user onboarding that works for one product doesn’t necessarily transfer to a different context. It needs to be tested.

More importantly, this testing needs a dedicated owner who’s accountable for the number. This is where things get messy.

Product activation, which includes new user onboarding, tends to be owned by the product team (49% of the time) with an assist from growth (16%), sales (13%), or customer success (11%). Yet few of these product teams are actually accountable for free-to-paid conversion. That usually falls to sales (28%) or growth (26%). This disconnect likely means product activation never gets the attention needed to really move the metrics.

People need the right tools to measure and improve these growth KPIs. You might wonder: which tools do I need today and which ones should I try next? We unpacked that question using the same dataset.

Based on the survey responses, the most impactful conversion tools were Mixpanel (#1 most cited), Amplitude (#2), Google Analytics (#3), and ChartMogul (#4). All four provide visibility into how free users behave and convert, making them core to the growth stack.

The ‘must try’ conversion tools were more varied. The top four were PostHog (#1 most cited), HubSpot (#2), Clay (#3), and Statsig (#4). The theme across the ‘must try’ tools is automating growth plays whether through lead enrichment, outreach, qualification, support, or user engagement.

Pricing and packaging had the highest number of mentions when survey participants submitted their most impactful growth experiment from the past year. Perhaps no surprise here.

What’s confusing is figuring out which pricing and packaging changes can meaningfully move the needle on conversion. In my experience, simply raising or lowering prices tends to not change conversion rates very much, which is why price increases can make so much extra money.

Changing plans seemed to make a bigger difference. This includes adjusting limits and feature gates, introducing or removing plans, and adjusting trial mechanics. Some tangible examples that worked via the survey:

Adjust limits and feature gates

Introduce or remove plans

Adjust trial mechanics

Other optimizations

Software companies used to have sharp lines between self-service and sales. Not anymore. Nearly every at-scale B2B company with a self-serve motion also has a large sales team.

Sales reps can enhance the user’s experience by helping guide them through the buying process rather than forcing them to go it alone. Some buyers prefer to DIY; others want to talk to a human. Contract size may be a proxy for this, but it’s never perfect (and even free tools might get scrutinized if important data is involved). What really matters is having the ability to route people into the right experience (sales versus self-serve) and letting them move between those paths in a way that feels effortless.

Among freemium products, 69% have human touchpoints when an enterprise user self-serves onto the product. The touchpoints are usually owned by an account executive (28%) or sales-assist (22%). Sales-assist teams don’t have a traditional quota; they focus on product onboarding and then handing off leads to sales.

Among free trial products, 80% have human touchpoints for enterprise users. Interestingly, these are frequently led by customer success (33%) or sales-assist (18%). I suspect this approach drives better response rates and helps qualify enterprise opportunities. Account execs might multi-thread or go top-down to catalyze a larger deal with the decision maker.

The latest frontier is combining self-serve product experiences, AI agents (both in-product and outside of the product), and sales for efficient growth.

SafetyCulture, which I featured previously, gets 500,000 free signups per year and there wasn’t an easy way to identify the highest fit and highest potential customers for sales. This meant the sales team resorted to manually sifting through the backlog of leads, researched companies one by one, and wrote personalized custom outreach. They introduced an AI inbound BDR, which increased meeting bookings by 3x and opportunities created by 2x.

The AI inbound BDR handles (1) personalized outreach sequences, (2) knowledge base powered responses, and (3) meeting booking, synced with AE calendars. This is supported by AI-powered waterfall lead enrichment, calling five providers in parallel for greater accuracy and coverage.

The lines are already blurry between product and growth (typically focus on product touchpoints) versus sales and customer success (typically focus on 1:1 touchpoints over email or on calls). But the customer doesn’t care about these differences.

Everything that influences conversion should be fair game, and it should feel seamlessly connected. The winners will treat conversion as a team sport. And they’ll get an assist from AI.

Related resources: