How AI will change PLG forever👇 🤖

🥇 “The race starts today, and we’re going to move and move fast” ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ ‌ Hey Folks! I know, I know. You're probably dead-sick of even hearing the word "AI" by now. So am I. I'm waking up every single day to learn I now need to read up on Bard, then Bing, and feeling guilty of not using ChatGPT nearly enough, wondering if I've boomered prematurely. But while we might be intimidated by this revolution, I can't help but see how it's going to transform PLG completely (and hopefully finally heal my rocky relationship with SaaS products...) by allowing product managers & marketers to understand and respond to users' behavioral cues in real time, provide 100% personalized in-app support also in real time, and [work on various behavioral KPIs on autopilot.]( [Image] "It's not that we don't have enough data. We don't have [enoughÂ]([insights.](" This is my standard reply to cold emails pitching me yet another data analytics tool. You're solving the wrong problem, bro. Both Product Managers and Marketers that use any analytics tools have in fact plenty of data at their fingertips. The crux of the issue is - you have to be able to use the data.  [Animated thumbnail for video]( [Let's rant about it...]( - almost nobody uses user segmentation remotely to its full capacity to personalize the in-app experience, shorten Time-To-Value, and foster deeper product adoption; simply put - we don't have the "computing power" to fully understand the subtle differences between different user groups, and segment them accordingly. - almost nobody uses [predictive analytics]( to identify at-risk users and prevent those users from churning; - almost nobody uses behavioral analytics to detect[the most active PQLs](and improve trial-to-paid conversion rates; - show me one SaaS company that reacts to users' disengagement/dead clicks/rage clicks and pushes them back on the "[happy path](" - their ideal user journey, allowing them to hit their goals in the shortest amount of time. With the current state of affairs, very few companies can actually leverage Product-Led Growth. Most just open a free trial/ freemium account and hope for the best.  How can AI change PLG in the next 5 years? 1. Identifying hot[PQLs on autopilot to improve trial-to-paid conversion ratesÂ]( Today, in order to identify your hottest Product-Qualified Leads in your free trials/freemium accounts and work on them, you need to analyze tons of data, manually create segments, and then build tons of automation workflows in e.g. CRMs to e.g. notify your sales/ CS folks there's a hot lead that needs to be worked on OR helped with something. It's possible, but very few companies have the resources to do that: [Image] You can make some (more-or-less data based) assumptions about the key events a hot PQL performs in your product in a specific time period, funnel the data from [Userpilot]( to Hubspot, set up workflows to assign the PQLs to an SDR based on their timezones... ...or you could wait for the Machine Learning algorithm to draw conclusions by reverse-engineering the conversion path of your different person in the past, automatically segment your PQLs by conversion likelihood and different JTBDs, and even suggest the most-effective way of approaching them to push for a sale.  2. Dynamic auto-segmentation [Image] Similarly to what I wrote above - keeping track of *all your users' actions*, making conclusions, and creating the right segments is still a nightmare.  I believe that in a few years' time, AI-powered product analytics tools will be able to analyze large volumes of historical user data, and dynamically create relevant user segments that require individual approach.  3. Trend detection & Predictive Analytics What do you see below? [Image] Making sense of event analytics and user trends these days requires so much effort and manual work. Imagine an ML model would do that for you, and just send you notifications on worrying trends occurring in your user base, with recommendations on how to counteract them? In a few years' time, AI may be used to determine the correlation between different user actions and various outcomes (both for the user, and the business) - both positive and negative. And based on that - it will be able to predict future events for individual accounts, users or whole user segments, and help you take action before they happen. 4. Happy Path Redirects [Image][Source]( Since we'll understand and segment each user accurately, as well as use predictive analytics to determine their "[happy path](" to the most successful outcomes, we will be able to react instantly (with in-app experiences, e.g. reactive tooltips) when they wander off that path. Imagine GPT being able to write microcopy in reactive tooltips in real time 🤯 - so product marketers don't have to predict and write for all the possible user action scenarios (which we all know is impossible...) It will be like having a co-pilot watching you use the product in-real time, and giving you ultra-personalized prompts based on your goals and current behavior so far.  5. GPT Chat-powered Self-Serve Support Needless to say, AI will also be able to provide specific answers to user questions (based on the information provided in the Resource Center, your help docs, and billions of user events) in real time - and even trigger the relevant in-app experiences based on that. [Image]  “The race starts today, and we’re going to move and move fast” This is what Microsoft CEO Satya Nadella said at Microsoft's last conference on Tuesday, announcing the new ChatGPT-powered Bing search. [Image] The race starts today for you as well. Will your product adapt to this revolution, and use the latest tech to serve its users' needs better, or remain a product-boomer? Leaving you with this thought 😉 See you all next week! [Image] Emilia Korczynska, Head of Marketing at Userpilot I'm a marketing manager obsessed with product growth. Wanna talk? 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