Emilia Korczynska

Userpilot

VP of Marketing

Doing all it takes to get more Product People over the code barrier with our code-free Product Adoption, Marketing & Experimentation Platform:  
Designing, developing and implementing a marketing strategy that ensures higher visibility 
Leading our stellar content team 
Implementing and driving a paid ads strategy to diversify customer acquisition. 
Driving funnel growth
Implementing an email marketing strategy 
Identifing and testing new acquisition channels
Overseeing, training, and coaching team members

Head Of Marketing

Managing content operations for a fast-growing B2B SaaS company - Product Experimentation and Marketing Tool for Product Teams: 
- Content planning, SOP development, SEO keyword research and topic ideation 
- Content editing and creation (blogs, website copy, social media content, ebooks, landing pages) 
- Community building (esp. Facebook - growing Product Growth & Retention Group, and LinkedIn) 
- Partnership management (guest posting, co-promotion)
- Writing weekly newsletters and developing email marketing workflows
- Organizing Product Drive - an annual online conference for Product People  (first edition: 2200+ participants)
- Data Analysis and Reporting (Google Analytics)

Marketing Manager

Wisemont Language Services

Boutique language agency helping SMEs sell more through great content on international markets

- Content marketing: translating, localisation and copywriting of SEO blog content, articles, website copy, newsletters etc. 
- International Social Media management 

Responsibilities:
- Developing and marketing new service packages and new in-formation products 
- Supervising development of content marketing strategies and SEO content for our clients that bring results – e.g.  ranking on 1st page in Google for competitive keywords, growing Twitter following to 3500 in 4 months

Owner

Postfity.com

- Helping more startups and small businesses hear about the most affordable social media scheduler designed specially for SMBs through: 
- creating a documented content marketing strategy, planning paid and organic marketing activities (content resharing, social media listening using Brand24, email marketing), setting and monitoring KPIs, measuring results using Google Analytics and Social Media Insights 
- hiring and managing marketing professionals: Social Media Managers, Copywriters, Facebook Ads Specialists, Google Ads Experts, Graphic Designers
- setting up and optimising email marketing drip campaigns
- doing Competition and Keyword Research, optimising blog content for search engines, creating new blog content optimised for low-difficulty keywords
- A/B testing Facebook ad campaigns
-  managing the marketing budget

Marketing Strategist

Find in China

Find in China is an online directory of local services, venues and events on a map in English designed for the expat population in China. Together with other local websites for expats we are creating the largest database of information and socialising opportunities for foreigners in China, as well as  a nationwide discount card. [Acquired October 2018] 
Responsibilities:
- Designing a web-app - map-based directory of venues, ser-vices and events in China
- Front-end project management – liaising with the front-end developer to produce the desired results in terms of design, functionality and user-experience, and with the back-end pro-ject manager 
- Business development and general management -  searching for joint ventures and collaborations to grow our database of point of sales and events quickly (we launched with over 1000 POSs across China), social media marketing

Co-Founder and CEO

Birmingham City University

Leading an in-country presessional course for students of Nanjing University of Science and Technology 
Teaching Academic Study Skills

ICP Visiting Lecturer

Swansea University

Teaching (Polish) Translation and Interpreting MA students:
- Module: Advanced Translation) 
- Module: Public Service Interpreting: Local Government Option
Supervision: Translator's Tools 
Material, test and examinations development

Part-time Translation and Interpreting Tutor

Runner's Delight

Runner's Delight was an innovative brand of functional porridge designed especially for runners. 
Responsibilities: 
- Designing and launching a sports nutrition product for runners
- Assisting in branding, social media and influencer marketing

Co-Founder and product manager

PayPal

EMEA Collections Specialist

Stream Universe TV

- managing relations with contributors: 
- contacting influential bloggers attracting large numbers of followers with commissions for film / TV series reviews and content writing;
- providing writers with updates on new releases, writing opportunities, etc.
- keeping  submission deadlines

Account Manager

The Cambridge Student

- writing a weekly series of satirical columns

Columnist

Passionate about SaaS product growth, and both the pre-sign up and post-sign up marketing. Talk to me about improving your acquisition, activation and retention strategy. 


2 years ago I thought LinkedIn ads were a complete waste of money. Any “attempts” we made didn’t bring any results…now our ABM program is just over 1 year old, runs 100% on LinkedIn, and has brought in multiple 7 figures in pipeline & very soon 7 figures in revenue…

What changed? 

☠️ We used to spend $1500-2000 per month on “experiments”, and measured results by…demos! 🤦‍♀️ that we expected to drive directly, and almost instantly, from a few random ‘we’re so great, book a demo’ ads (with not enough budget to even get enough clicks to the website, which we didn’t even measure).

🍀 Now we know a) Linkedin is just a content distribution channel, yes, it’s pay to play (but you pay to have a pretty darn good targeting) - but ultimately, you’re building awareness through good content.
You need to resonate with the pain, show different benefits of your product, social proof, etc. enough times 

☠️ We didn’t have target account lists. We just used broad targeting by job titles. 

🍀 Now we know 50% of the success is building the right target account list, and spent a lot of time tweaking the SAM criteria, and use Clay, Builtwith, Apify, Wappalizer etc. to build our lists based on intent signals. We use almost exclusively matched audiences. 

☠️ Our goal was to “generate leads” - “MQLs” - we didn’t look at leading engagement metrics at all. We didn’t look at the correlation between which company saw our ads in which campaign - we only looked  

🍀 Now we look at “campaign influence” - the deals (and pipeline / $ spent) from accounts that saw/engaged with our ads enough time BEFORE the deal was opened in ZenABM (my husband's startup, so do sign up for free 😜 https://lnkd.in/dp-Ym6Wj) We have account stages and monitor progression through them on weekly basis (and velocity). We know that it takes 100s of impressions, not a single "last touch" click, to get someone to book a demo 😉

☠️ We looked at LinkedIn as an isolated channel. We didn’t do any email follow up, any re-targeting campaigns, we didn’t target the same lists on different channels. 

🍀 Now we run email (with Smartlead) & Linkedin DMs (with HeyReach.io) follow up campaigns (planning to send 32k+ emails per month), personalised with hundreds of different intent signals (including intent we’ve gotten from LinkedIn ads, but not only). We’re splitting the audience between cold and warm. We’re enriching retargeting. We’re experimenting with reddit ads, and planning to look into other channels too.

☠️ I don’t even wanna know what we did in terms of campaign settings (objectives, goals, audience expansion…all the booby traps LinkedIn has in store for inexperienced marketers)

VP of Marketing @Userpilot. Author @ Product Rantz.

I went through my “saved” folder today and realised a) there’s a clear shift in Linkedin ads going on, as most LinkedIn ads experts are saying very similar things b) most of the posts I’ve saved lately came from the same 7 people. Do yourself a favour and give them a follow:

👉 Tim Davidson - founder at B2B Rizz, a boutique LinkedIn ads consultancy for ABM for B2B SaaS
👉 Gabriel Ehrlich - founder of Remotion, a LinkedIn ads agency
👉  Philip Ilic - founder of KiiN, a LinkedIn ads agency
👉 Ali Yildirim🌲 - co-founder of Understory, end-to-end growth agency for B2B tech companies, but focusing heavily on paid media (not only LinkedIn ads but also Google Ads)
👉 Maximilian Herczeg - LinkedIn Strategy & Ads for established B2B brands & founder-led companies, worked at LinkedIn for over 2 years (sadly writes in German, and I thought I'd never have to read German again 😝) 
👉 Ivan Falco - Head of Growth at Cold IQ - a GTM agency for B2B SaaS that uses LinkedIn ads to drive pipeline through inbound-led outbound

These are the people I’ve learned practically everything I know about LinkedIn Ads* from (and ofc, our own Siddhesh, but he never posts anything!). Some of them I've worked with as consultants before, some I'm planning to, some have very generously spend hours with me giving me feedback & reviewing our ad account 🙏 this is the little I can do in return. 

If I forgot to include anyone here - blame it on LinkedIn algos, I'm not seeing your posts 😉 Also - where are women posting about LinkedIn ads? 🤔) 

Here’s what I’ve learned from them in the last month (or so):

1️⃣ Thought Leader Ads (TLAs) are the hottest ad format

- Use your best organic posts with a clear monetization logic as ads.
- Aim them at the right list (ICP, buyers, and their influencers).
- Add a simple CTA link so the folks you target actually *go* somewhere (should be relevant to their stage - COLD: resources; WARM/HOT: audit/offer) 

2️⃣  TOFU–MOFU–BOFU is basically dead

 Nobody’s buying (in) "funnels" anymore. The new model is brutally simple:
COLD = trust-building (zero-click content, POV posts, case studies)
WARM = activation (retargeting, DM/convo ads, offers).


3️⃣  LinkedIn ads ≠ ABM. You need the rest of the GTM system.
 Ivan, Tim & Justin talk a lot about what happens after the click:
Retarget engaged accounts
Pipe signals into Clay / outbound
Make sure email, SDRs and content are all aligned (I know, I know, we all hate the word - but it's true. Better still - replace initial manual outreach with automated outbound)


 *I’m really bad at institutional learning (maybe because I was home schooled for the first 2 years of my education) and I most of the courses I’ve bought I haven’t finished. But why buy courses when you can learn so much for free here in a bite sized format (sometimes even while watching brain rot at the same time, right Tim Davidson 😅)?

Top Posts about LinkedIn Ads by LinkedIn Ads Experts

I saw in recent Kyle Poyar’s post (from a survey done with Maja Voje!) that intent-based outbound is the 2nd biggest bet marketing teams want to take in 2026. I'm not surprised - we already took this bet in H2 2025 (for once, I'm not late to the party 😅) and can share ‘early reviews’. 

Let me tell you…it’s not easy. In the last couple of months, since we started this “signal based outbound”, our new “BDR team of 0 (ZERO)” opened only low 6 figures in pipeline. That’s a bit disappointing, but we’ve only reached ~ 10% of our operational capacity (will explain why below). 

But perhaps more interestingly - it was also more than a team of 4-5 BDRs sometimes did in ‘slower months’. And the cost of running this op, relatively - is significantly lower: 
 
⚫ $852.8 - Clay - our key orchestration engine, we push all our CRM contact & company data there (which is the most precious source of signals…especially those high intent inbound signals like sales touchpoint, high intent pam) & use various APIs there (like Builtwith and Apify) to collect 3-rd party signals about technologies used, new job postings, and new executives starting their jobs (a common buying trigger). We also use OpenAI API in Clay for actually generating personalised messages in 
⚫ $501 - Heyreach - for LinkedIn automation 
⚫ $94.00 - Smartlead - for email automation
⚫ $0 for ZenABM - fetching signals from LinkedIn ads engagements (by specific campaigns = intent signal) & deanonymizing high and mid intent page visitors with LinkedIn Text retargeting ads - pushing that into Hubspot & Clay
⚫ $0 for Vector & RB2B - currently using free plans for de-anonymizing certain key page website visitors 
~ $100 for domains & inboxes
~<$50 Open AI token usage 

Total = $1,597.80 per month - you could not hire a single BDR for this. The mastermind behind this & only full time hire working on executing this is our rockstar GTM engineer. 

This operation has the capacity to send tens of thousands of personalised emails and ~ 3,000 Linkedin messages. 

Why we haven’t been able to reach full capacity yet? 

We’re still learning on the job - we’ve been running into API/ integration issues, and e.g. email sending delays based on non-obvious tool defaults hidden “under the hood”. 

There are of course, great tools like Usergems or CommonRoom that have productised this to a large extent (I have demoed a bunch and some are really impressive) - but the cost is always mid-to-high five figures at the very least. And it’s not in our DNA here to buy expensive solution before proving ROI.

So I’m bracing myself (or rather - I’m giddy with excitement for) another quarter of testing what our in intent-based outbound system can do (before it all goes mainstream 🫠) and hopefully I can report we’ve smashed all our quota targets after Q1 🤞

Every marketer will tell you the same thing “We have enough data. We don’t have enough insights.” Especially at the end of the year, when we’re all going into “reporting mode” - we’re drowning in data and desperately trying to make sense of it, to plan our 2026 budgets. 

AI should change that. 

This is why I’m so proud that Michal Jackowski is launching Zena - LinkedIn Ads AI Analyst today on Product Hunt - please check out the launch here: https://zenabm.com/ph

Zena answers all your questions about your LinkedIn Ads performance, your ABM campaigns, your target companies’ engagements with your ads *AND* the impact of your campaigns on revenue and pipeline. 

TL;DR - my husband has been working very hard on making it happen for almost a year, and I’ve been the harshest critic ;D I rarely like anything he does that doesn’t involve pasta - and I wouldn’t be sharing this launch with you if I didn’t think this is a game changer for reporting on ABM Campaign performance through LinkedIn ads. I’ve been feeling all the pain of doing this manually myself and this product is made of my tears (proverbially, of course :D) 

How does it work? Zena combines data from 30+ LinkedIn ads API endpoints with data from your CRM, and processed data from ZenABM (that already combines all the above data sources into one single source of truth, and calculates account engagement scores, ABM stages etc.) 

Here are the types of questions you can ask Zena about your LinkedIn ad and ABM performance data: 

 🟢 Ask Zena about your top performing ads, and ad formats - which had the highest number of clicks & CTR. 
🟢  Ask Zena to get you a list of your most engaged companies in different timeframes by clicks, impressions etc. AND by inventory type (image, TLA, chat).
🟢 Ask Zena which of your ad campaigns are driving pipeline, and which are only wasting budget. 
🟢  Ask Zena about the impact of your ABM campaigns on your funnel and TAM - how companies you’re targetting moved stages month over month, how much you’ve spent on them etc.
🟢  Ask Zena which of your ABM campaigns (and LinkedIn Campaigns) had the highest impact on revenue e.g. this vs. last month. 
🟢  Ask Zena about your ICP’s engagements - which job titles engaged most with your campaigns - month by month.

Getting all these questions answered just by looking at LinkedIn Campaign’s Manager or my Hubspot dashboards would take me ages - now I can get them answered in seconds, with beautiful reports generated by Zena.  

P.S. You can try Zena for free - you get 10 chats with Zena in ZenABM’s free trial - perfect for your end of the year reporting.

Someone (from the tech industry) asked me where I worked and what Userpilot was this weekend. And for the first time (hold my coffee), without thinking much, I responded: it’s a “Lovable for Product Adoption”. I know it’s a bold statement…and a complement for Lovable for becoming a household name for the category of no-code software in such a short time. And I know - sadly, no matter how much I bend myself over backwards here - it will never be as popular - because product adoption, unlike acquisition (which I have a hunch Lovable is mostly used for) is still “Cinderealla’s ugly cousin”. 

But here’s the irony - as the entry barriers to shipping software are getting lower and lower with Lovables of the world (and the competition is getting more and more cutthroat) ease of use and Time to Value are the strongest factors in determining whether someone will continue using your product, or start shopping around again at the slightest hint of friction. Nobody’s reading help docs anymore. You either provide instant answers in-app, or the users leave.

The irony why perhaps product adoption software hasn’t been that popular is also because the legacy solutions in the industry were notoriously difficult to use (iykyk).

The popularity of Lovable lies in a) how easy it is to use b) how fast it allows non-technical users to ship market-acceptable assets they could never dream of producing without a designer and a developer. “Acceptable” is better than “perfect” - because the difference between acceptable and perfect, in my experience, is exactly the same as “done” vs. “Not done”. 

👉 Yes, you could hard-code your onboarding experiences. But you know you won’t.
👉 Yes, you can use the legacy product adoption platforms…but that’s the modality of the word ‘can’. If you can’t ship what you need in < a few hours without developers’ / designers’ help - you won’t.
👉 You could buy 5 different solutions for lifecycle email, in-app communications, and product analytics - but you know the data will be falling through the cracks and you don’t use it consistently between the different tools. Your use communication will be broken. 

So give Userpilot a try for 30 days - we’ll support you with our new “Product Growth Jumpstart 2026” program (Chat to our product Growth Expert: https://lnkd.in/duKmW2hY to participate) to help you make most out of your free trial, and demonstrate to you how much more product-led growth (not only in terms of new acquisition, but also expansion) your team can produce if it’s empowered to engage users and build in-app product onboarding & adoption experiences truly on their own, with data available on their fingertips.

Open article: 15 Minute Meeting - Kelli Truelove by calendly.com

Idk if it’s perception bias but I see everyone dunking on attribution here. But I believe it’s because we’ve perverted attribution. It’s almost turned into “performative action”. Every week we’re spending hours and hours poring over our channel performance, trying to figure out how we can squeeze more last-touch conversions out of a channel by tweaking things to hit quota within budget, while at the same time believing it’s largely meaningless - because 99% of the time it’s not the single touchpoint that made someone book a demo or buy. As Ashley Faus wrote recently - you don’t know if it was the first touch, last touch, or the 57th touch that made you marry your husband ( no pun intended 🤣 ). It all starts to boil down to CRM credit. It becomes theatre.

Hot take: Attribution shouldn’t be about determining if you should spend more $ on Google Ads or LinkedIn ads based on last touch conversions or initial traffic source.

But there’s one super-important question that we should answer - and if we were playing with our own money, not some sort of marketing-budget-monopoly-money-: we’d want to answer it ASAP: 

Which channels don’t make any sense to spend your $$$ on? 

E.g. They may be there, as a touchpoint - but that touchpoint just simply doesn't matter, and you're throwing $10k per month on it.

If you turned off Google Ads/ LinkedIn Ads/ Reddit/ Stopped posting on LinkedIn/ Stopped running webinars/ events today - would your pipeline stay the same? 

Might it be that a lot of your last-touch conversions from your branded cold search ads are just taking a lazy “shortcut” to your homepage, and would have converted anyway from organic? 

I’m not good enough at statistics (the class was at 8 am on Friday…) but it sounds like we should be doing multiple regression analysis on cohorts of SQLs, taking out different channels and seeing what happens, like with a food allergy test. 

But we wouldn’t dare. And we probably couldn't figure it out anyway, because dark social yadda yadda, and because...most people themselves don't even know what made them buy. 

Like - we’ve been running certain campaigns since before I even joined Userpilot (which was before covid…yes, I’m that ancient). We never dared to stop. 

What would happen if we did? 

But then we started running LinkedIn ads only ~14 months ago, and see an increase in conversions from the target lists vs “control group.” 

It’s easier to see because they are defined. But with inbound? 

Is it all trial and error? Is there no way out? 

I’m genuinely curious how you folks make peace with attribution and what tools you use to inform your decisions how much $$$ to put in each channel and when to stop 😅

Most people know whether they are "just dating" someone or "in a relationship". Except for my cousin. She doesn't know. Meanwhile - most Product Managers I talk to are like my cousin. They don't know if the features they shipped have been "activated" or "adopted" - and what % of their users have done the latter. And how to measure it. 

If your KPI is retention - this is something you need to measure (and improve). 

Cover photo credit to Vrinda Tyagi, whose Medium post (link in the article) inspired my Product Rant today!

Feature activation is not the same as engagement, and not the same as adoption. Most people know whether they are "just dating" someone or "in a relat

Open article: 🤔 📈 Are they in a relationship or not?  by Emilia Korczynska • 3 min read

🤔 📈 Are they in a relationship or not?

After George tagged me in his post about which of his 2025 “marketing projections” panned out and which didn’t - I had a strong feeling of deja vu. At the start of 2025 - we were all betting on “original, thought-leadership content” as an antidote to “AI slop” and organic traffic decline. I’ve announced our blog is dead - long live the PITT - Product Innovation Think Tank. 

Well, turns out the PITT lived just for a short 6 months. And that “thought leadership” is extremely hard to scale. I’ve tried so many times, in so many ways:

 A) 2021 - hiring “subject matter experts” in-house - something that even OpenAI (how ironic) is trying to do now (check out Kyle Poyar’s recent post about it - in the comments). It was a disaster; they all quit within 3 months - turns out thought leaders don’t want to mass-produce thought leadership to OKRs. I know of maybe one company that has done it successfully (Ahrefs) - so I wonder how that pans out for OpenAI. We say 'a star is born', after all, not made. 

B) 2023-24 - partnerships & sponsorships - like herding cats and playing one-armed bandit, was just burning cash while creating a disproportionate amount of nuisance for our demand gen team to manage;

C) 2025 - Content syndication in an “owned” online magazine + boosting LinkedIn posts based on the original content with Thought Leader ads. You can’t just find more Akashs Guptas, Kyle Poyars, or Maja Vojes to keep playing that game over time. Plus - getting the influencers to agree to participating in a program like that is art. So after a strong start, the quality just kept going downhill, and we fizzled out after a few months. 

No, onto what has worked, so far, ish:

ABM - moving from a purely inbound motion to building an account-based marketing motion has worked for us - driving a significant % of the pipeline every month. BUT - because of all of the above, we’re really only just capturing demand. We didn’t manage to create this exceptional program full of amazing content that would really “generate demand” (some people are going to tell me I believe in Santa in the comments - fair enough, I hear your point. As we all know, nothing exists in marketing anyway ;)) 

“SEO is dead” - well, that was my biggest “positive disappointment” - turns out both SEO and link building still exist, and have respawned as a whole new channel - AI referrals (and no, we haven’t changed much about how we do SEO). 

How has your 2025 been? Different than you expected? 😉

What do you do with “pipeline overlap”? 🤔 As a marketing leader, you’re expected to make clear-cut decisions: where to put the marketing $$$. October has been one of our best months in terms of pipeline generated from Organic, ABM and Google Ads. But a lot of this pipeline overlapped depending on whether we looked at first, last touch or ‘ABM influenced’ pipeline. I’ve spent (wasted?) the last 2 days between Looker Studio, Hubspot, GA4, ZenABM trying to tease out which channel I should give credit for which deal- and where do we should best spend the budget next year. 

ABM-influenced pipeline is most fun in this respect

Last touch attribution:

- 51% converts through direct traffic
30% through “offline sources”. I can easily attribute 80% of the pipe to “direct ABM influence”. 
But: 
< 10% converts from Google Ads. 
18% converts from Organic Search results. 

Then, the situation looks even more interesting with the contacts “original traffic source”: 
37.2% had organic touchpoint
17.3% had paid search touchpoint
The rest came from direct & “offline sources” (which is Hubspot’s way to say “I don’t know”)

And then when you ask the prospect what made them book a demo they will tell you they found you in Perplexity, or they don’t remember 🫠

Is there a point in doing this exercise? 

All the flavours of my pipeline below…

If (as I wrote last week) - most PMs don't know how the "regular" features are performing and whether they have been adopted by their users - imagine what it's like with AI features...

Hot take: digital products ship AI features faster than the users are adopting them: 

We’re great at signing contracts, we’re terrible at changing habits.
Adopting AI doesn't mean using AI. 

This is probably the most uncomfortable truth:

AI is not failing technologically - it’s failing behaviorally.

If you look at enterprise adoption, you see the same curve we see in product teams adopting new analytics tools:

💠 Excitement (“this will change everything”)
💠 Procurement
💠 Pilot
💠 Two power users 
💠 Everybody else goes back to Google Docs
💠 Leadership says adoption is low
🫠 Tool gets replaced next year

Why? 👇

If (as I wrote last week) - most PMs don't know how the "regular" features are performing and whether they have been adopted by their users - imagine 

Open article: AI is not failing technologically — it’s failing behaviorally. by Emilia Korczynska • 2 min read

AI is not failing technologically — it’s failing behaviorally.

I know a lot of you are probably about to dig into a massive portion of turkey & stuffing 🦃 🥘 ...but hopefully this post will give you some food for thought this Thanksgiving too 👇 I have some very interesting insights form our recent Product Analytics survey for you (a full report is coming soon!) - and some predictions for how Product Analytics will change in 2026 based on that: 

We've recently asked product managers & marketers a few questions about their experience with product analytics - and their expectations. 

They said what we all feel: 

⛔ There's too much data, and not enough insight; 
⛔ Reporting takes too much time; 
⛔ It's hard to connect data cross-functionally;  

Perhaps, even more interesting were the answers to the question what the users are now expecting of their Product Analytics solution....

...AI has changed us, duh: most users don’t want to build reports, set up tracking, or learn SQL.

This is what they want - and how I believe Product Analytics tools will need to change to stay competitive (+ how we're addressing these expectations too): 

1. AI-Driven Insights & Predictive Analytics

The biggest shift is moving from dashboards to automated, actionable insights.

Tools that can:

🟣 surface anomalies automatically
🟣 explain why metrics changed
🟣 predict churn, upgrades, and expansion
🟣 recommend actions for improvement
🟣 identify friction points and Aha moments
🟣 act as a “copilot”

…will replace those that require manual digging.

This aligns fully with our user research: “tell me what matters, what changed, what to do.”

2. Unified Data Integration & End-to-End Data Flows

Tools that win in 2025–26 will make it easy to combine product usage data with CRM, support, and BI tools, merge quantitative & qualitative data (events + heatmaps + surveys) and remove engineering from the integration process.

3. Embedded Analytics & In-Product Workflow Integration

Analytics is moving from stand-alone dashboards into workflows.


4. Ease of Use & Low Technical Barrier

One other major differentiator of next gen analytics tools will be the zero-friction setup: users are expecting the insights to be available for them without committing any engineering hours to setting the analytics tools up: 

🟣 automatic tracking instead of event tagging, prebuilt dashboards, reports & prompts, already available in Userpilot, 
🟣 simple, non-technical UI,
🟣 democratized analytics for PMs, CS, product marketing

Which brings me to the next point:

Brace yourself: Analytics 2.0. is coming this winter! 

I've already started casually calling Userpilot the "Lovable for Product Adoption" - but I will soon also be able to call it the "Lovable for product analytics" - more research & details inside 👇

taplio

Emilia Korczynska's Linkedin Analytics