I help product teams move from feature-driven to outcome-driven ways of working.

My methodology in a nutshell:
- Create internal alignment on target audience/ICP
- Align on business & and product goals (OKRs, hierarchy of metrics)
- Set up or improve idea discovery & validation processes (e.g. customer interviews, shadowing, protoyping, usability testing, A/B testing)

Interim Product Lead/ Advisor/ Coach (solopreneur)

Rodeo Software

- Improving the Rodeo New User Experience (setup & activation)
- Helping the Product team move to outcome-driven ways of working
- Setting up & executing discovery & experimentation processes

Interim Sr. Product Manager

HiveDesk

HiveDesk offers automatic employee time tracking software with project, task, and cost tracking. I'm advising the HiveDesk team on how to build a product that fits seamlessly to their customers needs. Setting up robust product analytics and continuous product discovery to help improve the HiveDesk onboarding flow - from 'aha' to 'habit' - and corresponding metrics.

Product Advisor

Value Rebels

Value Rebels help product teams create impact. 
I focus on helping organizations become product-led, through customer discovery, experimentation, and data analytics.

Product Expert

Paladine, A Hays Venture

Head of Strategy / Business Development

Datawallet

Head of Policy and Product Strategy

COVID Alliance

The COVID Alliance is a collaborative ecosystem moving at startup speed with public health scale, connecting decision-makers to experts in the fight against COVID-19.

Volunteer COVID Alliance Service Corps: Head of Ethics 

Bridgemaker GmbH

Senior Venture Architect

CrefoPayment GmbH & Co. KG

Head of Product and QA

UPG Technology GmbH (became CrefoPayment GmbH & Co. KG in April 2017)

Head of Operations

Product Leader | I help SaaS startups build products that customers love | sonderhouse.io

Read my Idea Discovery & Validation guide here: https://eu1.hubs.ly/H054V9Y0

What I do
I help your B2B SaaS product team move from a feature-driven to an outcome-driven way of working.
 
I do this by:
1. Creating (leadership) alignment on your #1 ICP
2. Creating alignment on business and product goals
2. Setting up/bolstering discovery and validation processes (evidence-based ways of working, product analytics). 

Who I’m not
I’m not a feature shipping machine. I’m not the voice of the stakeholder/customer (they say ‘jump’, I ask ‘how high’). I don’t code. 

What I believe
Good products put the (niche) target audience first (leadership alignment on #1 ICP)
Good products are built by continuous discovery and rapid validation
Good product teams drive product and business outcomes

Background
I spent 10+ years working for startups and scale-ups in Berlin, Germany (in a mix of Product & Strategic roles). I saw successes, but also many failures. I definitely drank the startup-life Kool-Aid. 

Work with me
You can hire me for coaching, advising, or as an interim product lead. Read more of my work on elsevanderberg.substack.com. I’m excited about both short- and long-term projects.

Yes, yes, yes! After months of having the most enjoyable chats with Michael Sawka I finally get to start working with the brilliant team at Wave Terminal as an Interim Product Lead. 

Wave is re-imagining the terminal on open web standards. Inline renders, persistent sessions, universal history across machines, AI integrations - all the cool stuff at your fingertips. Built for users who just want things to work well out of out-of-the-box.

Dear Backend Engineers, DevOps engineers & SysAdmins in my network: Prepare mentally for lots of interview & usability test requests ❤️ 


Dr. Else van der Berg

Should we launch new features, or optimize the features we have today?

I enjoyed reading Ken Rudin's article on Lenny Rachitsky's blog (link in comment). Key urges companies to cool down on their shiny new object syndrome (I'm with you, Ken!), and to optimize awareness and engagement with what the features already have instead. 

His core arguments:
🔷  𝗧𝗵𝗲 𝗺𝗼𝘀𝘁 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝘀 𝗳𝗼𝗿 𝗮 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 𝗮𝗿𝗲 𝘂𝘀𝘂𝗮𝗹𝗹𝘆 𝘁𝗵𝗲 𝗼𝗻𝗲𝘀 𝘁𝗵𝗮𝘁 𝘄𝗲𝗿𝗲 𝗯𝘂𝗶𝗹𝘁 𝗳𝗶𝗿𝘀𝘁. They represent the core of your 'raison d'etre'. Adding frill on top often just causes unnecessary bloat and value dilution.

🔷  𝗬𝗼𝘂 𝗰𝗮𝗻 𝗱𝗿𝗶𝘃𝗲 𝘀𝗶𝗴𝗻𝗶𝗳𝗶𝗰𝗮𝗻𝘁𝗹𝘆 𝗺𝗼𝗿𝗲 𝗴𝗿𝗼𝘄𝘁𝗵 𝗯𝘆 𝗳𝗼𝗰𝘂𝘀𝗶𝗻𝗴 𝗼𝗻 𝗴𝗲𝘁𝘁𝗶𝗻𝗴 𝘂𝘀𝗲𝗿𝘀 𝘁𝗼 𝗲𝗻𝗴𝗮𝗴𝗲 𝗺𝗼𝗿𝗲 𝘄𝗶𝘁𝗵 𝘆𝗼𝘂𝗿 𝗲𝘅𝗶𝘀𝘁𝗶𝗻𝗴 𝗸𝗲𝘆 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝘀 𝗮𝗻𝗱 𝘂𝘀𝗲𝗿 𝗳𝗹𝗼𝘄𝘀 (he backs this up with experience from Salesforce, Zynga, Google, Facebook...)

I believe there's a time and place for both building new stuff, and optimizing what we have.

First off: Startups & scale-ups are in a different position than Google & Facebook. Optimizations and tweaks won't help if the core-value you imagined would be well-received doesn't resonate at all in reality. 

𝗜𝗳 𝘂𝘀𝗲𝗿𝘀 𝗱𝗼𝗻'𝘁 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝘄𝗵𝗮𝘁 𝗮𝗱𝗱𝗲𝗱 𝘃𝗮𝗹𝘂𝗲 𝘆𝗼𝘂𝗿 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 𝗯𝗿𝗶𝗻𝗴𝘀 𝗼𝘃𝗲𝗿 𝘁𝗵𝗲 𝗰𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝗼𝗻, 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀 𝗮𝗿𝗲 𝗹𝗶𝗸𝗲 𝗹𝗶𝗽𝘀𝘁𝗶𝗰𝗸 𝗼𝗻 𝗮 𝗽𝗶𝗴.

On the other side of the spectrum, I've seen my fair share of early stage companies get caught up building more & more (almost random) features to try to catch up with every direct & indirect competitor that gets a nice wad of VC cash. 
Shiny new object syndrome is real, and product bloat hides the value. 

How do you define Aha - the moment when a new user first realizes the value of your product - for a multi-use-case product?

Imagine Schmoho: a one-stop-shop that solves a bunch of customer jobs to be done: There’s a sales pipeline (for prospects), a CRM database (for customers), and a customer support inbox for CS with automatic email workflows. Users can also build a support center, integrate a live chat, and set up a chatbot. 

Such a cool, powerful product. But... not so cool if you need to figure out Aha.

Because what Aha, or 'value' means to a user depends entirely on 𝘸𝘩𝘢𝘵 𝘵𝘩𝘦𝘺 𝘤𝘢𝘮𝘦 𝘵𝘰 𝘵𝘩𝘦 𝘱𝘳𝘰𝘥𝘶𝘤𝘵 𝘧𝘰𝘳 𝘪𝘯 𝘵𝘩𝘦 𝘧𝘪𝘳𝘴𝘵 𝘱𝘭𝘢𝘤𝘦. And that’s not so easy to figure out with a product that solves a variety of jobs. 

Things get even more complex if:

👉  You have multiple ICPs. An enterprise customer might use your product very differently from an SME.
👉   Your product caters to teams, not individuals. Because team members with different roles will likely have very different jobs they’re trying to get done with your product, and you'll be expecting very different usage frequency. 

𝗦𝗼 𝗵𝗼𝘄 𝘁𝗼 𝘀𝗶𝗺𝗽𝗹𝗶𝗳𝘆 𝘁𝗵𝗶𝘀 𝗰𝗼𝗺𝗽𝗹𝗲𝘅 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻:

👉  Do the ‘aha’ searching exercise for 1 ICP at a time. If you’re pre-PMF, your whole company should be focusing on only 1 ICP anyway. 

👉 Pick the persona/role that is the most important for you to address now, for example by looking at what you’re trying to tackle. If you’re trying to improve new user onboarding, and you know that most of your new users are small business owners who are trying to figure out if your product is right for them, then put your focus there.

Now that you’ve drastically narrowed down the scope, it’s time to figure out what Aha could mean for them.

𝗦𝘁𝗮𝗿𝘁 𝗾𝘂𝗮𝗹𝗶𝘁𝗮𝘁𝗶𝘃𝗲, 𝗲𝗻𝗿𝗶𝗰𝗵𝘁 𝘄𝗶𝘁𝗵 𝗾𝘂𝗮𝗻𝘁𝗶𝘁𝗮𝘁𝗶𝘃𝗲
I usually start with qualitative data, for example from customer interviews or shadowing sessions.  I use that qualitative data to narrow down my list of potential aha’s, and then back up those potential aha’s with quantitative data. 

𝗧𝗵𝗲 𝗼𝘂𝘁𝗰𝗼𝗺𝗲: 𝗮 𝗵𝗶𝗴𝗵𝗹𝘆 𝘀𝗲𝗴𝗺𝗲𝗻𝘁𝗲𝗱 𝗮𝘂𝗱𝗶𝗲𝗻𝗰𝗲

Often you’ll see that within your #1 ICP and #1 persona, you can build multiple segments based on jobs to be done.

In the case of the Schmoho : some business owners of SMEs will come to Schmoho because they’re looking for a sales pipeline for their business, and others because they’re looking for a customer support inbox. By segmenting your audience by these jobs, you can become far more precise in measuring whether the users from a specific segment are taking the necessary actions to experience the right features, and whether that corresponds with retention.

(PS I wrote an article on this topic not long ago, link is in the comment )

Having hired a bunch of people doesn't make you a scale-up in my book.

If you don’t have 
🔷 Product/market fit for at least 1 ICP
🔷 Figured out your unit economics(CAC payback period, CM, LTV, etc)
🔷 proved that you have a repeatable and scalable sales model

…you’re scaling a leaky bucket. 

Adding people just adds more communication paths, deteriorates trust, increases the need for bulky processes, etc. 

Two companies that inspire me by staying lean whilst still solving a specific problem extremely well:

😍  June.so (PS. follow Enzo Avigo if you don't already). June raised a little over $2M in 2021 and is running on 11 people (last time I checked). It’s my product analytics tool of choice for B2B SaaS companies because it’s so easy to set up and can deliver most of what I need. + the level of support is incredible (how do they do this with so few people?)
😍 Userflow - $4.6M ARR with just 3 employees  🤯  

(Of course, staying *this* lean doesn’t work for every business model. Inspiring, nonetheless!)


I spend way too much time looking at data going "This can't be right..." 
Usually because... it isn't 😫 

Data reliability is a real problem, and Joy Chatterjee & I dove into the nitty gritty of it. 

🔷 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻: 𝗘𝘃𝗲𝗻t 𝘁𝗿𝗮𝗰𝗸𝗶𝗻𝗴 𝗻𝗼𝘁 𝘀𝗲𝘁 𝘂𝗽 𝗰𝗼𝗿𝗿𝗲𝗰𝘁𝗹𝘆.
Surprise, surprise: When you implement Segment or the SDK of your product analytics tool of choice incorrectly.... things go sour. Firing off the wrong events the wrong time, not logging certain users, messing up the association of users to accounts, I've seen it all... 

Secondly: Without a well-thought-out 𝗲𝘃𝗲𝗻𝘁 𝘁𝗿𝗮𝗰𝗸𝗶𝗻𝗴 𝗽𝗹𝗮𝗻 (what do we track, why, which properties should we store?) and 𝗻𝗮𝗺𝗶𝗻𝗴 𝗰𝗼𝗻𝘃𝗲𝗻𝘁𝗶𝗼𝗻𝘀, things get out of hand.... quickly. Especially when developers are  responsible to track new events as part of new feature launches. No naming conventions = CHAOS.

I'm not sure whether we should always hire a data engineer before any other role on the data team to avoid such disasters. But it 𝘪𝘴 important that someone (or a committee or someones) properly thinks through what the end state should look like. 

🔷 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻. 𝗖𝗿𝗲𝗮𝘁𝗶𝗻𝗴 𝗼𝘂𝗿 𝗱𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱𝘀 𝗼𝗿 𝗿𝗲𝗽𝗼𝗿𝘁𝘀.
I'm all for democratizing data, but there's an obvious problem with having non-data-experts self-serve: Messing up the filters, segmenting incorrectly, running the wrong report for the use case.... and then coming to incorrect conclusions based on the wrong data. 

Big thanks for Dr. Mario Lenz for telling me I'm not alone in this (❤️ ), and for giving me some solid advice: "We allow everybody to play around with data — but key metrics come via „certified“ dashboards from the data team." 

It's a messy affair.  Stay critical, don't trust anything 🙃 . 

#useranalytics #data #productmanagement

Where are you on the "working with data" confidence curve?

I love Joy Chatterjee's explanation of the curve emotions Product Managers go through during their journey toward data enlightenment 💡  

🔷  𝗣𝗵𝗮𝘀𝗲 𝟭 "𝗜 𝘁𝗼𝘁𝗮𝗹𝗹𝘆 𝗴𝗲𝘁 𝗱𝗮𝘁𝗮". That blissful phase, right after getting access to some nice dashboards or out-of-the-box product analytics reports. For critical thinkers, this phase is short-lived...
🔷  𝗣𝗵𝗮𝘀𝗲 𝟮 "𝗧𝗵𝗶𝘀 𝗱𝗮𝘁𝗮 𝗱𝗼𝗲𝘀𝗻'𝘁 𝗹𝗼𝗼𝗸 𝗿𝗶𝗴𝗵𝘁...", "𝗪𝗵𝗮𝘁 𝗮𝗺 𝗜 𝘀𝘂𝗽𝗽𝗼𝘀𝗲𝗱 𝘁𝗼 𝗱𝗼 𝘄𝗶𝘁𝗵 𝗮𝗹𝗹 𝘁𝗵𝗶𝘀 𝗱𝗮𝘁𝗮?" "𝗪𝗵𝗮𝘁 𝗶𝘀 𝗺𝗼𝗱𝗲𝗹 𝗯𝗶𝗮𝘀?!". The first moments of despair arise.
🔷  𝗣𝗵𝗮𝘀𝗲 𝟯 "𝗦𝗼 𝗜 𝗱𝗶𝗱𝗻'𝘁 '𝗴𝗲𝘁' 𝗱𝗮𝘁𝗮 𝗮𝗳𝘁𝗲𝗿 𝗮𝗹𝗹...". The moment of painful realization.
🔷 𝗣𝗵𝗮𝘀𝗲 𝟰 "𝗪𝗼𝗿𝗸𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗱𝗮𝘁𝗮 𝗶𝘀 𝗰𝗼𝗺𝗽𝗹𝗶𝗰𝗮𝘁𝗲𝗱"

Phase 4 is my territory, but I like to oversimplify things a bit to create some data-appetite with the 'fresh to data' PMs I work with. 


📢 Looking to pick the brains of 𝗕𝗮𝗰𝗸𝗲𝗻𝗱 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀, 𝗗𝗲𝘃𝗢𝗽𝘀 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀, and 𝗦𝘆𝘀 𝗔𝗱𝗺𝗶𝗻𝘀 who are heavy terminal users (30-minute call).

Specifically, I'm looking for users who want a terminal to just work out-of-the-box, without extensive configuration, seamlessly integrating with the tools you use. 

Background: I'm doing target audience discovery work for Wave Terminal, an open-source, AI-native terminal built for seamless workflows. 

I'll put a link in the comment where you can schedule a call, feel free to DM me for more information ✉️ 

Thanks a million in advance, your insights help me A LOT ❤️ 🧠 



There's a lot of noise around 'what data skills a good PM needs'. Rather than rambling off an intimidating list of tools and abbreviations, we should ask ourselves:


𝗪𝗵𝗮𝘁 𝗮𝗿𝗲 𝘄𝗲 𝘁𝗿𝘆𝗶𝗻𝗴 𝘁𝗼 𝗮𝗰𝗵𝗶𝗲𝘃𝗲 𝗯𝘆 𝘄𝗼𝗿𝗸𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗱𝗮𝘁𝗮?

I dive into this question in my latest article "Unpacking data skills for product managers" (link to Substack in the comment)  ✍️ 

In short: Working with qualitative and quantitative data is in service of two things:

👉  𝗙𝗼𝗿𝗲𝗰𝗮𝘀𝘁𝗶𝗻𝗴: Making predictions about future outcomes. We need decent forecasts to be able to prioritize the right ideas
👉  𝗠𝗲𝗮𝘀𝘂𝗿𝗶𝗻𝗴: Evaluating the outcomes of activities and initiatives against our predefined objectives of benchmarks

We measure to find out how far off our forecasts were. The next step it to try to figure out 𝘸𝘩𝘺 we were wrong or right about certain things. All in service of creating better forecasts in the future.

Building your data skills for the sake of having data skills misses the point, if you don’t know how to apply these to 𝗳𝗼𝗿𝗲𝗰𝗮𝘀𝘁 and 𝗺𝗲𝗮𝘀𝘂𝗿𝗲 impact. Being able to answer questions on your own with data is useless if you don’t know what the right questions to ask are, or how to interpret the data you uncover.

On the flip side, if you have the strategic context and are asking the right question, it’s possible to create a rudimentary forecast with basic data skills. 

If it’s between having a perfect dashboard that answers a useless question, or a high-level forecast answering a question that matters, I’d pick the latter every time.

Hope you like the article, feedback (and conflicting opinions!) is very welcome! ❤️ 



Are you a Berliner DevOps, SecOps, or Infrastructure engineer, or an engineer who wears the hat of 'dev on duty' (dealing with things breaking down)? I'd love to buy you breakfast  🥐 ☕ 

(If you're not in Berlin, a virtual coffee might have to suffice)

I'm trying to understand the job of 'managing infrastructure' (from designing it to troubleshooting it) with Kubernetes or Docker, and the pain points or wishes that arise in this process. 

Curve ball: I'm nowhere near as technical as you are, so it will be a nice exercise in explaining complex things in simple terms 😇 

I promise I'm a good hang. 

Read my Idea Discovery & Validation guide here: https://eu1.hubs.ly/H054V9Y0

Who I am
I’m an interim Product Lead/Advisor with a knack for strategic thinking. I love SaaS, and especially product-led growth. I base my decisions on a healthy mix of customer discovery, data analytics, and gut feeling. 
My mission is to help tech companies build products that their customers love, and want to tell others about. 

Who I’m not
I’m not a feature shipping machine. I’m not the voice of the stakeholder/customer (they say ‘jump’, I ask ‘how high’). I don’t code. 

What I believe
Great products put the (niche) target audience first.
Great products rely on leadership alignment on who it’s for, and what it does (core value).
Great products drive customer acquisition, activation, retention, and monetization.

Background
I spent 10+ years working for startups and scale-ups in Berlin, Germany (in a mix of Product & Strategic roles). I saw successes, but also many failures. I definitely drank the startup-life Kool-Aid. 

Work with me
You can hire me for workshops, advising, or as an interim product lead. Check out more details on the Value Rebels website (www.valuerebels.com) or DM me. I’m excited about both short- and long-term projects and can offer up to 30/hrs per week (so don't get scared off by the term ‘interim’).

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