I was early Marketing at Uber spending 5 years building Brand, Performance, and Lifecycle Marketing Data Science teams. I got to work with & learn from world-class marketing, data science, and martech leaders. Over the course of my career there I've measured over $1Bn in Marketing Spend and estimate that I've helped drive $200M+ in incremental revenue and cost savings . 

Then I moved on to a few early stage startups and scaleups (both as a FTE and Consultant) where I learned how to be even scrappier when building Marketing. 

Now I help Marketers access those same playbooks top Consumer Tech Marketers use to prove, optimize, and scale ROI by sharing frameworks, processes, and analyses. 

I'm doing this because I love the Marketing stories and people behind it in a world where Product seems to get most of the credit. There's so much magic in Marketing and I want to share more about it. 

Check it out here → https://experimental.beehiiv.com/

Outside of my newsletter and podcast, I love spending time with my 2 beautiful kids and my incredible wife in Amsterdam. We used to love traveling and eating out but you know... kids ...  so now I love cooking and exploring all the fun things little kids can do!

Sundar Swaminathan

CEO: We're using 7-day click attribution. 

New CMO: What's your average purchase cycle?

CEO: Probably 30 days from first awareness to purchase.

CMO: Then our attribution window is cutting off 75% of the customer journey.

CEO: Wait, what?

CMO: We're only giving credit to touchpoints in the last 7 days. Everything that happened before that gets ignored.

CEO: So we should use a 30-day window?

CMO: Maybe.

CEO: This is confusing. How do we pick the right window?

CMO: There is no right window. There's the window that matches your business reality, but more importantly reflects incrementality. 

CEO: What does that mean?

CMO: If you're selling impulse purchases, 1-day windows probably work. If you're selling considered purchases, you need longer windows but also need to acknowledge the attribution is fuzzy.

CEO: So what should we do?

CMO: Test different windows and see how channel performance changes. If Facebook looks amazing at 7 days but terrible at 28 days, that tells you something.

CEO: What does it tell me?

CMO: That Facebook is getting credit for conversions close to the purchase, but it might not be the thing that started the journey.

CEO: How do other companies handle this?

CMO: The sophisticated ones stop relying on attribution windows alone and run incrementality tests instead.

CEO: So attribution is useless?

CMO: It's useful for directional insights. Just don't make million-dollar decisions based on which arbitrary window you picked. 

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👋 I’m a former Uber Head of Marketing Science where I optimized $1Bn+ across Brand, Performance, and Lifecycle Marketing

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Former Head of Marketing Science at Uber who optimized $1Bn+ across Brand, Performance, and Lifecycle → Sharing weekly playbooks used by top Marketers to measure and scale ROI.

CEO: Need to cut Brand Marketing budget by 30%.

CMO: Why Brand Marketing?

CEO: We need to preserve cash now. Brand Marketing feels like the safest place to cut.

CMO: Why does it feel safe?

CEO: Because we can turn it back on when things improve. Engineering headcount we can't.

CMO: You're right that we can turn it back on. But you're wrong that it's safe.

CEO: Explain.

CMO: When you cut Perf Marketing, you see the impact immediately. Revenue drops in weeks. And when you cut Brand Marketing? You won't feel it for months, but it'll come.

CEO: So we should cut Performance instead of Brand?

CMO: I'm saying both have consequences. Performance cuts hit revenue fast. Brand cuts hit revenue slowly, which makes them feel safer but they're actually riskier.

CEO: How is slow worse?

CMO: Because by the time you realize brand cuts hurt, your competitors have filled the void. Customers forgot about you. And it takes twice as long to rebuild than it did to build initially.

CEO: We're not cutting all of marketing. Just 30%.

CMO: Where's the 30% coming from?

CEO: I was hoping you'd tell me.

CMO: Well, it's not coming from me and it's not what I'd recommend, but I know I'm not going to win this fight, but I do have a recommendation. 

CEO: What do you recommend?

CMO: Cut performance by 15% and brand by 15%. Spread the pain. Don't kill either completely.

CEO: Why not just cut the one that's less important?

CMO: Because Brand Marketing is not less important! They work together. Brand makes performance cheaper. Performance capitalizes on brand equity. Kill one and the other suffers too.

CEO: How do other companies handle this?

CMO: The smart ones actually do the opposite of what you're saying. They protect Brand Marketing during downturns because that's when competitors are cutting. You can gain share cheaply. The desperate ones cut everything and wonder why recovery takes years.

CEO: That's a tough call.

CMO: It is. But cutting Marketing always feels safe because the damage is delayed. That's what makes it dangerous. 

–
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CEO: Brand campaign doesn't look it's working! 

CMO: What metrics are you looking at?

CEO: The usual. New customer acquisition, conversion rate, revenue growth. All flat.

CMO: Good :) 

CEO: What do you mean? You said this campaign would drive growth.

CMO: It will. In two to three months. 

CEO: Two or three months? Why so long?

CMO: Because of how our customers actually buy. Walk me through how you decided to buy those shoes you're wearing. 

CEO: Hmm...I saw ads for it, ignored them for a while, then a colleague mentioned it, then I researched it, then maybe a month later I finally bought it.

CMO: Why'd you buy it a month later?

CEO: I needed shoes and I saw another ad for them which .... OH! I get it! 

CMO: Exactly! That's what's happening here. Our product isn't something people impulse buy. We cant snap our fingers and make people want our product.

CEO: So we're just... waiting for them to be ready?

CMO: We're making sure that when they're ready, they think of us first instead of our competitors.

CEO: But how do we know it's working if we can't see results for months?

CMO: We track leading indicators like search volume for our brand terms. Those move first. Revenue moves later.

CEO: What are those showing right now?

CMO: Search volume for our name is climbing. 

CEO: Why didn't you lead with that?

CMO: Because you asked about revenue. But revenue is a lagging indicator. It's like planting a tree and asking why there's no fruit after six weeks.

CEO: That's a good analogy.

CMO: Thanks. Now, stop texting me and go back to bed. It's 3:30 AM.

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CMO: Our MMM is crazy. It changes all the time. 
.
Me: How often are you refreshing the model?

CMO: Monthly. We want the latest insights.

Me: That's your problem.

CMO: Why? Shouldn't we use the most recent data?

Me: MMM needs long time horizons to detect patterns. Monthly refreshes are too frequent. You're picking up noise, not signal.

CMO: How long should we wait?

Me: Quarterly at minimum. Ideally every six months. You need enough data to see through seasonal fluctuations and campaign variability.

CMO: Okay, what else could be causing the instability?

Me: Are you changing variables between runs?

CMO: Sometimes. We add new channels or remove ones we stopped spending on.

Me: Every time you change the model structure, you're asking a different question. The answers will change because the question changed.

CMO: So we need to keep the structure consistent?

Me: As consistent as possible. If you must add variables, retrain the full history with the new structure. Don't just append.

CMO: This is frustrating. I thought MMM would give us definitive answers.

Me: MMM gives you directional guidance, not precision. It's better at telling you "brand is underinvested" than "spend exactly $47K more on brand."

CMO: Then why did we spend six figures on this?

Me: Because it's still valuable for strategic allocation decisions. Just don't expect it to be as precise as an A/B test.

CMO: How should we be using it then?

Me: Use incrementality tests for precision. MMM for strategy. Attribution for daily steering. 

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CEO: Our ROAS is at 8x! Best it's ever been.

New CMO: Why do you celebrate ROAS?

CEO: Because it's a good metric! 

CMO: But ROAS doesn't tell you if you're growing. It tells you how efficient your spending is.

CEO: Aren't those the same thing?

CMO: Not even close. We could have 20x ROAS and be shrinking as a business.

CEO: Give me an example.

CMO: We're spending less on acquisition and only targeting our highest-converting audiences. 
ROAS looks amazing because we're cherry-picking easy wins.

CEO: But we're being more efficient.

CMO: We're being more efficient at reaching fewer people. Our total customer volume is down because we've narrowed our focus so much.

CEO: So high ROAS is bad?

CMO: Not always, but ROAS alone doesn't always tell the whole story and if we optimize to just ROAS, we might be missing the picture. 

CEO: What should we be optimizing for?

CMO: Well like most things in Marketing, it's triangulating across a few pictures:
1. Total new customers
2. ROAS (ideally incremental if we have it)
3. LTV / CAC 

CEO: Why do all the dashboards show ROAS then?

CMO: Because platforms want you focused on efficiency, not growth. It makes their reporting look good even when your business isn't growing. ROAS is useful for comparing high level channel efficiency, but it shouldn't be the only goal.

CEO: How do we fix this?

CMO: Stop celebrating ROAS improvements in isolation. Always pair it with growth metrics. If ROAS is up but then new customer revenue  is down, we're headed in the wrong direction. It just means we likely cut ad spend or perhaps focused on retargeting already warm leads. 

CEO: That's counterintuitive.

CMO: Most good marketing metrics are. 

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CMO: Test showed zero lift. Let's cut the channel.

Me: Hold on. Let me see the test setup first.

CMO: We turned off the ads for a month. Revenue didn't change. Seems pretty clear.

Me: Did you account for delayed conversions?

CMO: What do you mean?

Me: Buyers don't convert immediately. They hear about you, research later, maybe buy weeks after exposure.

CMO: We ran the test for a full month though.

Me: Right, but if your average time-to-conversion from exposure is 6 weeks, a one-month test won't capture the full effect.

CMO: So we should've run it longer?

Me: At least 8 weeks for a product like yours, but really 12 at the minimum. Better would be me to actually use sample sizes. 

CMO: So the test is useless?

Me: Not useless, but potentially not representative. We should also check if the impact shows up in brand search lift instead of direct conversions.

CMO: Why would it show up there?

Me: Because that channel can build awareness. People hear about you, then search for you later. If branded search went up during the test period, that's a signal ads are working even if direct conversions didn't move.

CMO: We didn't track that.

Me: Then we're not capturing the full impact. Let me redesign this test with the right metrics and timeframe before we kill the channel.

CMO: How much will that cost us?

Me: Way less than cutting a working channel because we measured it wrong. 

–
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CEO: Just saw that CAC dropped 25%! Nice!

CMO: Meh, I am not happy. 

CEO: Why? Lower CAC is always better.

CMO: Not if we're acquiring fewer customers overall.

CEO: Wait, are we?

CMO: New customer volume is down 15% versus last quarter.

CEO: But our CAC improved.

CMO: Right. We got more efficient at a smaller pool. It's like bragging about catching fish faster while fishing in a shrinking pond.

CEO: I don't understand. How is lower CAC bad?

CMO: CAC is an efficiency metric. It tells you how well you're converting. It doesn't tell you if you're growing.

CEO: So what should I be looking at?

CMO: CAC and total new customers. I want new customer growth to outpace CAC growth. If CAC drops but we're acquiring fewer customers, we're optimizing ourselves into irrelevance.

CEO: What's driving this?

CMO: We tightened our targeting so much that we're only reaching people ready to buy right now. We're ignoring the 95% of the market that isn't in-market yet.

CEO: But those people have terrible conversion rates.

CMO: Today, yes. But if we don't reach them now, our competitors will. And when they're ready to buy, we won't be on their radar.

CEO: So, what are we going to do?

CMO: We need to balance efficiency and reach. Some campaigns for high-intent, low CAC conversions. Others for building future pipeline, even if CAC looks worse.

CEO: How do other companies think about this?

CMO: The smart ones track both CAC and total customer growth. If both are improving, you're winning. If only CAC improves while volume drops, you're in trouble.

CEO: Got it. Thanks for explaining that. I feel much better. 

CMO: Good. Now stop reading reports and slacking me at 2:30 AM.

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CEO: We need to be sending more emails! 

New CMO: Why? What data are you seeing?

CEO: Email open rates correlate perfectly with revenue.

CMO: I believe you, but that doesn't mean email is driving revenue.

CEO: What else would be driving it?

CMO: Could be anything. Seasonality, product improvements, word of mouth, other marketing channels.

CEO: But they move together. That has to mean something.

CMO: Likely, but that might not be what's happening. 

CEO: So what's actually happening with email?

CMO: My guess? When people are already interested in buying, they open more emails. Email isn't creating demand. It's capturing attention from people who already have intent.

CEO: How do we know for sure?

CMO: Run a holdout test. Stop sending email to a random part of the audience for a month. Then we can split it by segment and If revenue drops in that segment, email is causal. If it doesn't, it's just correlated.

CEO: What if revenue does drop?

CMO: Then we know email matters and we can invest more confidently.

CEO: And if it doesn't drop?

CMO: Then we just saved a ton of money on a channel that wasn't actually working. We can reinvest those resources into more testing and be more aggressive at iterating on the campaigns we thought were working. 

CEO: This seems like a lot of work to validate something that looks obvious.

CMO: The expensive mistakes are the ones that look obvious but aren't true. Would you rather spend $500K scaling email based on a correlation or spend $20K on a test to know for sure?

CEO: When you put it that way, the test seems cheap.

CMO: It is cheap. Way cheaper than scaling the wrong thing. 

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CEO: What's our marketing efficiency?

CMO: What do you mean by efficiency?

CEO: You know, how well is marketing performing?

CMO: That depends. Are you asking about ROAS? CAC payback? LTV ratios?

CEO: Aren't those all the same thing?

CMO: Not even close. They measure completely different aspects of marketing performance.

CEO: Can't you just give me one number that tells me if marketing is efficient?

CMO: I could, but it would be meaningless.

CEO: Why?

CMO: Because different channels work on different timelines. Performance marketing pays back in weeks. Brand takes months. Combining them into one number hides everything useful.

CEO: So what should I be asking for?

CMO: Depends on what decision we're trying to make.

CEO: I want to know if we should increase marketing budget.

CMO: Then you need incremental ROAS. 

CEO: Why not use Blended ROAS? 

CMO: Blended ROAS might be 5x. Looks great. But if we're maxed out on our best channels, incremental ROAS might only be 2x. Adding budget would actually hurt efficiency.

CEO: So I can't just ask "what's our marketing efficiency?"

CMO: You can. But I need to know what you're trying to decide first. Then I'll give you the right metric.

CEO: This is way more complicated than I thought.

CMO: Marketing measurement is. That's why one-number answers are usually wrong. 

–
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CEO: Finance says you drove $2M. You say $2.3M?

CMO: We're both right. Here's why...

CEO: It's revenue. How can there be different #s?

CMO: Finance measures when cash hits the bank. I measure when the customer converts.

CEO: Why does that matter?

CMO: I bring in signups, and often they buy the same day. But sometimes, they buy that week and sometimes a few week laters, but the revenue is attributed to my signups.

CEO: Can't you just align on one definition?

CMO: We could, but then one of us is optimizing for the wrong thing.

CEO: Explain.

CMO: If I optimize for recognized revenue, I'll ignore user behaviors where they are still valuable but might purchase later. We'd be optimizing towards same day purchase events. 

CEO: And if Finance uses your number?

CMO: They count based on dates so signups that happened this week but haven't shown revenue yet will not count for them. Their job is different than mine.

CEO: So we just accept having two different numbers?

CMO: We accept that different functions need different metrics. The key is we both understand what the other is measuring and why. 
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CEO: AI is my #1 priority!

New CMO: Yeah... it's like my 7th...

CEO: What?! We need to be AI first and fast! 

CMO: Here's whats more important for me :
1. Our Marketing data is an insane mess
2. We have ZERO organic social presence
3. Our landing pages tell a disjointed story
4. I have no idea what channels are incremental
5. Our users don't know about half of what we do
6. Oh and retention is 30% below where it should be

CEO: Okay, great, but our competitors are using AI! 

CMO: Let them. I know for a fact they're building on a foundation of sh*t. It'll come tumbling down. I promise you that I will make AI my H2 priority but you need to let me focus on H1 on getting things right. And that's an accelerated timeline. I'm not even adding the fact that I just joined and need to ramp up.

CEO: Okay, I see your 6 months timeline and I raise you 2.

CMO: No! Give me 6 months. Let me do what you hired me for.

CEO: Okay, 4 months?!

CMO: ** closes Zoom meeting **

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CEO: Do we need an MMM?

CMO: That's not the question we should be asking...

CEO: Ohhh, what is?!

CMO: Are we ready for one?

CEO: What do you mean?

CMO: First, an MMM is not a holy grail. It's one part of a holistic measurement strategy.

CEO: That doesn't sound so bad...

CMO: Agree. The problem is that it might tell us something we weren't expecting. That channel A isn't contributing as much. 

CEO: Okay... still not seeing an issue...

CMO: Will you let me finish!

CEO: Haha oops... too excited.

CMO: Okay, so it might tell us something we don't know and we have to be prepared to then test that and validate it. That could mean we turn off 50% or even 100% of our "best" channel.

CEO: Oh boy... really?!

CMO: Yes. That's why the question we should be asking is "Are we ready for one?". Are we culturally and operationally ready to act on one or are you just asking because you heard that's what we need.

CEO: Definitely the latter, but this is really helpful.

CMO: Good. Don't worry, you'll ask me this 10x more times and I'll say the same thing 😞 

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Marketing alone should NOT own CAC. 

That's the equivalent of saying:

- Product alone owns LTV 
- Ops alone owns conversion rate
- Finance alone owns payback period 

Sure, it's easy to silo these metrics and "assign" an owner but we do that to create an illusion of control. 

The only time CAC should be considered a Marketing metric is when all of the levers to drive CAC fall under Marketing.

This means:
1. Activation experience
2. Landing pages
3. Signup flow
4. Pricing

Otherwise, Marketing can really only influence CPM, CTR, and traffic which hamstrings their impact and influence. 

There's no perfect solution but the best orgs understand 3 things:

1. The customer doesn't care who owns what
2. You can't keep top talent this way 
3. Silos just lead to inefficiencies

It's why so many Marketers get frustrated when they're asked to reduce CAC but hit a ceiling in terms of what they can deliver.

If you want Marketing to own a metric, give them ownership.

It's pretty straightforward. 

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My next guest raised $6M to fix Marketing Measurement after being frustrated with the tools he had available at Dropbox, Pilot, and Adobe 🤑  

Pranav Piyush, CEO & Founder at Paramark (and Reforge's course instructor on Marketing Measurement) joined experiMENTAL Newsletter & Podcast to break down why marketing feels like a "foreign language" to the C-suite and how to fix it.

We chatted in depth about:
⮑ Why MMM is now table takes
⮑ How to make marketing metrics CFO-friendly 
⮑ Why brand and performance teams are dysfunctional 

My favorite discussions:
⭐ Most marketing leaders feel anxious before board meetings because there's a massive communication gap between CMOs and the C-suite. It feels like they're speaking a different language.

⭐ If you're doing $10-50M in ads stop wasting time on holdout tests. You likely don't have enough data and should focus on pulse-up testing and new channels. 

⭐ Pranav wishes he could remove all decimals from marketing dashboards. Saying "17% incrementality" creates false precision. The reality is that It's probably somewhere between 13-19%, and that's okay.

If you're a marketing leader struggling to prove ROI to your CFO or CEO, or you're tired of attribution tools that don't actually help you make better decisions, this conversation is for you!

Pranav brings an engineer's rigor and a marketer's empathy to one of the most broken parts of modern marketing. 

Tune in wherever you love listening to podcasts using the links in the comment!

CEO: Are we measuring ROI of our Super Bowl Ads?

CMO: No, for 3 important reasons.

CEO: Oh boy, I'm nervous. 

CMO: Haha I figured, but trust that it's not so bad:
1. We can't measure ROI in a traditional sense

It's a national TV campaign and the US is our largest market so there's no real opportunity of a holdout

2. If we try to measure business impact around the time of our ad, we'll be concentrating all the "impact" into a short window and it'll make the ROI look poor

3. All other proxy metrics like search volume, traffic, etc. are going to be metrics you think are "soft" and don't represent business value.

CEO: Okay all good points, but we're spending a sh*tload

CMO: Yes, I agree, and to be clear there is an ROI. I just won't see it for months and so I can't share the ROI with you.

CEO: Okay, fair. What ROI are you expecting.

CMO: Great question. Let's get into this!

1. It's a launch of our new product. We're getting in front of hundreds of millions of our target demographic. Many of them won't be ready to buy today but they will be in a few months and we'll be there because...

2. It's the launch of our new campaign which is rolling out across 8 different channels over the next few months. Everyone is going to see us everywhere!

3. It's a competitive bet too. Our competitors are also showing up and obviously I think our team is better than theirs so people will compare us and we're going to win. Plus if we don't show up, that's just another void they'll fill 

For the campaigns we do rollout over the next couple months, we will be using our standard measurement framework of Attribution + Incrementality tests + MMM to triangulate ROI. 

Overall, there's an ROI and I believe it's huge but it'll take time to materialize

CEO: Okay. We have trusted you this far and you have not led us astray. Forgive me. I was wrong to despair.

CMO: Did you just quote Lord of the Rings?

CEO: Did we just become besties?!

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CEO: CAC keeps climbing. Should we shift to brand?

CMO: It's not an either/or decision.

CEO: But, we have a fixed budget. If we spend more on brand, we need to spend less on performance.

CMO: True. But the real tradeoff isn't "performance" versus "brand". We need to decide on whether we prioritize today's revenue or tomorrow's efficiency.

CEO: Explain.

CMO: Performance marketing captures current demand. Brand Marketing creates it and at higher volumes. When we only do Performance, we're competing for the same pool of high-intent customers as everyone else.

CEO: Why is that bad?

CMO: Well, you run out of high intent customers eventually. By layering in Brand, we increase the pool of higher intent customers.

CEO: But brand takes FOREVER to show results.

CMO: Six to twelve months to show business results but much sooner to show that we're moving in the right direction. But once it kicks in, our performance channels get more efficient without changing anything.

CEO: So Brand makes performance cheaper?

CMO: Exactly. Strong brand means higher consideration, which means more people searching for you, which means lower CPCs and better conversion rates.

CEO: So we need both?

CMO: You need both working together. Performance capitalizes on brand equity. Brand reduces performance costs over time. They're complementary, not competitive.

CEO: How do other companies balance this?

CMO: The good ones don't see it as balance. They see it as sequencing and investing. 
Scale performance → Build Brand → Scale performance → Build Brand in ongoing loop. 

Eventually there's a cap, but we're not even close. 

But by then we'll have much better unit economics.

A rare few can survive on just performance marketing but they'll have insane AOVs and LTV / CACs which is not realistic. Also, they're in a market where they might not be looking to win market share and are happy with their current growth rates. 

CEO: So, we don't want to make the same mistake most companies do? 

CMO: Right. They wait until performance stops working to start Brand Marketing. By then, they're desperate and impatient. Brand Marketing needs time. We should start before we need it. 

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CMO: Hey, engagement is up but revenue is flat. 

Me: What's your hypothesis on why?

CMO: Honestly? I'm stumped. The funnel looks healthy. Everything we're tracking is improving.

Me: Can I ask you a different question? What drives someone to purchase from you?

CMO: Product quality, pricing, trust in the brand. The usual stuff.

Me: Right. Now, how closely do your engagement metrics correlate with any of those?

CMO: Hmmm... not sure. 

Me: That's the issue. We're measuring what's easy to track, not what predicts outcomes.

CMO: So what should we be doing differently?

Me: Start by working backwards. What's the customer action that leads directly to revenue for you?

CMO: Completing their first transaction. Once someone buys our retention is strong.

Me: Perfect. So what predicts first transaction? Not correlates. Predicts. 

CMO: How quickly they experience value in the product. And whether they trust us enough to enter payment info.

Me: Now we're getting somewhere. Are any of your current metrics measuring speed to value or trust?

CMO: No. We're measuring clicks and time spent.

Me: Which is why engagement is up but revenue isn't. Those metrics aren't connected to what drives purchasing behavior.

CMO: This makes sense, but how do we figure out what actually matters?

Me: If you've got the data, then look at it and see what it says. If not, then another test you can do is change your optimization metric. Play around with what happens if you use X instead of Y to optimize. 

CMO: This is going to be uncomfortable. The team loves celebrating engagement wins.

Me: They'll love celebrating revenue wins more. And once you show them the connection between the right metrics and business impact, they'll never go back.

CMO: Alright. Let's do this. Where do we start?

Me: Make a list of every metric you track. Then next to each one, write down why you believe it predicts revenue. If you can't articulate it, cut it.

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In 2025, I wrote 38 articles on Marketing. 

Here are my top 10 by open rate (60%+):

Oh and they're all free to read 😃 

1. How to write a measurement brief 
https://lnkd.in/gPrr-tAF

2. How I build Uber’s Brand Science Team
https://lnkd.in/evJDr2wc

3. Why analyzing Marketing feels impossible
https://lnkd.in/gqNagEBr

4. How to calculate LTV
https://lnkd.in/gxUqcxcw

5. 7 Brutal truths about CAC
https://lnkd.in/gVjh-YRK

6. How to measure when you can’t A/B test
https://lnkd.in/gcHsSpqy

7. How to build better Marketing targets
https://lnkd.in/gmH8VV8T

8. How to create more impactful analyses
https://lnkd.in/esmGEWmk

9. Why startups shouldn’t spend a $ on Paid Ads
https://lnkd.in/e8kFYYU5

10. How Data Scientist should use AI
https://lnkd.in/expdRfFZ

Let me know which one was your favorite!

Every startup at every stage needs a data leader, but the engagement model evolves:

Pre-product market fit → Advisor

Especially if you're a marketplace or E-com, they can help you with what to analyze, track, and prioritize.  

Even just an hour or two a week is huge! 

Scaling → fractional head of data 

Assuming you have 1-4 data folks (engineers, analysts etc), a Fractional data leader can be a game changer. 

You’ll need someone to mentor your data team and help the executive team scale. 

Scaling is about building systems and having the right data leader will help you build that.

Beyond → Coach / Consultant

Once you’re bigger, you’ll likely have a full time Head of Data but the truth is they’ll need help. 

Going from scale to “corporate” has different demands and most data leaders aren’t prepared for it. 

Bring in advisors and coaches to help your leader scale. 

Everything from how to ask for budget to how to promote people are fundamental skills that can be coached. 

Follow Sundar for Marketing Strategy & Science

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JSESSIONID

LinkedIn App Challenge

Talks about #solopreneurship and #experimentation

CEO: I need to present marketing ROI to the board. 

CMO: How are you defining ROI? 

CEO: The ROI. How much revenue are we generating per dollar spent?

CMO: On which channels? Which timeframe? Are we including brand or just performance?

CEO: All of it. Just give me one number.

CMO: I can't do that responsibly.

CEO: Why not? Finance gives me one number for profitability.

CMO: Did Finance give you the ROI for Product?

CEO: Well... no...

CMO: Okay, exactly. My job is to help you here but it's important that we're aligned on the right story and narrative. Storytelling is kind of my job. What does the board want?

CEO: The board wants to know if Marketing is working.

CMO: That's not specific enough. Are they asking if we should increase budget? Cut budget? Shift budget somewhere else?

CEO: Probably whether we should increase it.

CMO: Then you'll want to show incremental ROI not blended ROI.

CEO: Do we know our incremental ROI?

CMO: On performance channels, yes. On our Brand Marketing efforts, we'd need to run tests to find out.

CEO: The board isn't going to like "we need to run tests."

CMO: Then we give them blended ROI with a massive caveat that it doesn't predict what happens if we scale. Their choice.

CEO: Why is this so complicated?

CMO: Because you're asking for simple answers to complex questions. Marketing isn't accounting. 

CEO: What do other CMOs do?

CMO: The good ones educate their board on what's measurable versus what's theater. The desperate ones give clean numbers that look good but don't mean anything.

CEO: I don't want to be desperate. Help me educate them. 

CMO: Let's set up a session tomorrow so I can help you understand it better first. Also, read some of the articles from the newsletter that I DM'ed you about. 

CEO: experiMENTAL? Done. 

--
🔔 Follow me for Marketing Strategy & Science 
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Sebastian Hewing 🚀

Founder Data Action Mentor | Swiss Army Knife for Data & Analytics | Ex-Rocket Internet

Over the last 18 years I have built and led data teams across all continents - except Antarctica. ☃️

But my first data leadership job almost broke me:

It was 2010.

At 29 years old, I led the data team of the world’s largest venture builder (Rocket Internet).

Rocket Internet scaled companies such as:

→ Zalando (Europe's leading online fashion platform)
→ Delivery Hero (a leading food delivery platform)
→ HelloFresh (the world's leading meal kit delivery company)
→ Lazada (the Amazon.com of SouthEast Asia, exited to Alibaba)
→ Jumia (the first African company on the NYSE).

I saw those companies and data teams grow from tiny startups into massive, global market leaders.

And even though we built data teams for 7 companies in 15 countries, I struggled...

... hard.

→ We were drowning in ad-hoc requests instead of shaping strategy.
→ We were shipping dashboards instead of outcomes.
→ And ultimately stakeholders didn’t trust what we built.
→ And my influence, impact and personal growth hit a ceiling. 

Over the following years, I became a trusted advisor to Founders and CEOs by building winning data teams for 50+ companies.

The one thing I realized over all those years after leaving Rocket Internet: 

I was lacking an operating system for building winning data teams.

So, I created it.

The Data Team Adjusted Lean Canvas Framework transforms how data teams create value based on best practices from:

- data engineering
- product management
- marketing 
- behavioral science
- and entrepreneurship.

In my Data Strategy Masterclass, I have helped hundreds of growth-oriented data experts from 40+ countries become more influential by applying my framework and by building impactful data teams in the age of AI.

Favorite testimonial: “I got more value from your $350 course than a $3,000 University of Berkeley executive education course.”

→ Find out more at http://www.dataactionmentor.com/masterclass-business-impact  ← 

P.S.: My biggest passion besides Data, AI & Entrepreneurship is traveling. After 2 years of "digital nomading", I now have a home-base in Taipei, but I typically spend 5-6 months per year traveling. I have been to 100+ countries and territories.

Founder & Mentor

Solve all your Data- & Analytics Challenges and connect with experienced Data & AI Professionals for a price and time investment that every startup can afford

One boat has all the tools.

One lonely boat knows where it's going.

Guess which one delivers business value?

Every week I meet teams drowning in the “modern data stack”:

→ dbt models piling up
→ 15 Looker dashboards per stakeholder
→ Half-built AI POCs

And when things break, no one asks “what is the business trying to achieve?”

They ask: “should we migrate to another tool?”

Meanwhile, the high-performing teams?

→ They start with a problem.
→ They talk to real users.
→ They focus on impact over elegance.

Ship.
Learn.
Adjust.

No hype cycle. No data cult. Just progress.

Data strategy isn’t a shopping list.

It’s a decision-making framework.

And until that’s in place, no tool will save you.

♻️ Repost if you've ever inherited a stack with 12 tools and zero outcomes

👉 And join 3,000+ data experts who read my free newsletter for weekly tips on data strategy: https://lnkd.in/grEH8a3c

Sebastian Hewing

Pragmatic Data Strategist → From Dashboard Factory to Strategic Partner

I used to design extremely complex data infrastructures.

Now I do the exact opposite.

When building data infrastructure, simplicity is king! 👑

This is true for high-growth startups AND large companies!

Here’s the exact approach for every new data infrastructure I build:

First, I talk to all stakeholders intensively.
↳ understand their use cases
↳ understand their challenges, struggles and desires
↳ understand how they are tackling these challenges today

This is typically about 25% of the WHOLE infrastructure project!

Second, I create a KPI/Dimension Map.

This is a cross-tab that captures all stakeholder challenges and use cases in an easy-to-read format.

Third, I evaluate a status quo for each KPI/Dimension combination (use case)
↳ where does the data come from?
↳ what is the data quality?
↳ are there manual processes involved in capturing the data?

Lastly, together with stakeholders, we define a data infrastructure MVP (minimum viable product).

The goal is to FULLY cover the first use cases in less than 4 weeks.

A lot of data people get the definition of a “data MVP” wrong.

A solution solving 10 use cases 50% is not an MVP.
A solution solving 1 use case 80% is.

♻️ Repost if you’ve ever built a pipeline only to find no one uses it

👉 And join 3,000+ data leaders who read my free newsletter for weekly tips on building impactful data teams in the AI-era: https://lnkd.in/gvTUPa5x

I will explain my approach in more detail in my coming newsletter this Sunday.

“Let’s define a data strategy.”

Translation: let’s argue about tools for 6 months.

Here’s the thing nobody wants to admit:

Most data strategies are just about data stacks.
Not actual strategy.

If you want a strategy that survives the next reorg, AI hype wave, or exec sponsor change - start here:

1. Problem: What are we solving?
2. Users: Who are you serving?
3. UVP: What's our data team's secret sauce?
4. Solution: What are we building and what are we NOT building?
5. Distribution: How will we get this in front of users without chasing them down?
6. Systems: What helps this scale without breaking us?
7. Outcomes: What will users actually do differently?
8. Costs: What’s the real investment? (Spoiler: it’s not just the software)
9. People: How will we grow a team that wants to stick around?
10. Vision: What guides our decisions when priorities clash?

Answer those 10?

You’ve got a data strategy.

Ignore them?

You’ve got a dashboard backlog and a stack no one uses.

♻️ Repost if you've ever watched a “data strategy session” turn into a Power BI vs Tableau debate.

👉 And join 3,000+ data leaders who read my free newsletter for weekly tips on building impactful data teams in the AI-era: https://lnkd.in/gpwGnGA2

Pragmatic Data Strategist | Outcome-driven data strategy that earns your seat in leadership decisions

For years, I thought this was the playbook:

→ Get data → Build tools → Deliver value

Spoiler: it never worked that way.

- I built beautiful dashboards that nobody used.
- I answered questions no one had asked.
- I fixed bugs in things that didn’t matter.

At some point, I realized:

→ Data doesn't create value. Action does.
→ And action doesn’t happen without buy-in.
→ Buy-in doesn’t happen without a story.
→ A good story only works if it speaks to a user problem.
→ And the only user problems that matter? Are the ones tied to business goals.

So now, I work like this:
👉 Business Goal
👉 User Problem
👉 Data
👉 Story
👉 Buy-in
👉 Action
👉 Value

It’s not about moving from data to value.

It’s about moving from understanding to action.

With data as your ally, not your starting point.

This is how you shift from builder of dashboards to creator of business impact.

Want to transform your team from dashboard factory to strategic business partner?

👉 Join 3,000+ data leaders who read my free newsletter for weekly tips on building outcome-driven data strategies: https://lnkd.in/gzDsAYYR

♻️ Repost if you've ever shipped a dashboard that even you forgot existed.

You're drowning in ad-hoc requests instead of shaping strategy.

- “Can you pull this real quick?”
- “Can we get a dashboard by Friday?”
- “Can I export this to Excel?”

You’re busy and about to burn out.

I wrote 6 data strategy pieces to help data leaders break that cycle.

From busy-work to business impact:

1/ The End of the Data Analyst
→ What happens to the data analyst role in the age of AI?
🔗 https://lnkd.in/giCNfYXy

2/ Who should lead the data leader?
→ The reporting line that shapes your whole data strategy.
🔗 https://lnkd.in/gMHwnS8g

3/ Re-thinking the Single Source of Truth
→ When one truth isn’t enough for your company.
🔗 https://lnkd.in/gPTZBXHT

4/ The Hidden Structure of High-Performing Data Organizations
→ The quiet reason business and data teams clash.
🔗 https://lnkd.in/gkZX_5QU

5/ When the Intern beats your AI model
→ How overengineered data projects lose to scrappy, useful ones.
🔗 https://lnkd.in/ga-mYAex

6/ Pragmatic Data Governance that doesn’t kill the vibe
→ Stop building what people ask for. Start solving what they need.
🔗 https://lnkd.in/gxdPYcfJ

Inside these posts, you'll learn:

💡 Why the analyst role is evolving, not ending 
💡 Simple solutions that drive real business results 
💡 How to bridge the gap between business and data teams

Want to stop being a dashboard factory and start creating real value?

👉 Join 3,000+ data experts who read my free newsletter for weekly tips on building impactful data strategies in the AI-era: https://lnkd.in/gk9AXBAH

♻️ Repost if you’ve answered “just one quick thing” more than 3 times today

18 years in data. My 10 most powerful lessons.

(aka: how to avoid 5 years of pain, firefighting, and dashboard chaos)

No fluff. No hype.

Just hard-earned truths that changed how I build data teams:

1. Build data teams like a start-up
→ Don’t fall in love with your solution. Fall in love with the problem.

2. Embrace an 80/20 mindset
→ Ask: “What’s the smallest thing we can build to deliver 80% of the value?”

3. Don’t stop at dashboarding
→ Own experimentation. Feed data into ops tools. That’s where decisions happen.

4. Self-service is real
→ But it’s not “let everyone build dashboards.” It’s “help people answer the WHY on their own.”

5. Market Risk > Product Risk
→ You can build anything. The real risk? No one needs it.

6. Outcomes > Output
→ Dashboards don’t matter if they don’t change decisions. Measure business impact, not tickets closed.

7. Ad-hoc ≠ agility
→ Reactive teams burn out and lose trust.

8. Control before agility. Always.
→ Without trustworthy and understandable data, speed is just a faster way to crash.

9. Data teams are not service desks
→ Saying “yes” to every request keeps you busy. But it won’t move the business forward.

10. Business logic does NOT belong in dashboards
→ Keep logic in your data models. Or enjoy version wars, Excel exports, and endless confusion.

If I had followed these earlier, I would’ve saved my team months of pain.

Which one hits hardest for you?

♻️ Repost if you've ever shipped a dashboard that got zero views and one confused Slack message

👉 And join 3,000+ data leaders who read my free newsletter for actionable tips on data strategy: https://lnkd.in/gsjMX856

Your org chart is not a data strategy.

But it will make or break your data team’s impact.

Here’s what happens in most companies:

- The CTO says, “We need better data infra”
- The CFO says, “We need clean numbers”
- The CMO says, “We need attribution analytics”
- The CEO says, “We need a dashboard for the board”

And just like that... the data team reports to everyone and no one at the same time.

That’s how you end up with a “data strategy” that looks like:

- 791 dashboards
- 15 AI POCs
- 3 different metrics for ‘active user’
- 1 data team stuck doing requests with no real mandate

Let’s reframe the org chart conversation:

Instead of asking “Who should the data leader report to?”, ask:

→ Where is the pain greatest?
Data teams thrive when they solve high-impact problems. Attach them to the leader who needs them most.

→ Who understands what good data work looks like?
If the CxO treats the data team like a dashboard vending machine: wrong choice.

→ Who has room to lead?
Don't put your data org under someone who’s drowning in direct reports.

→ What business are you actually in?
Data should be aligned to the business engine - not to the loudest stakeholder.

Bad reporting lines don’t just hurt morale.

They kill momentum. Slowly. Silently.

And six months later, someone’s asking,
“Why is our data team not driving impact?”

Now you know why.

♻️ Repost if you've ever had to explain for the 5th time that data doesn’t belong under the CTO "because it’s tech stuff"

👉 And join 3,000+ data leaders who read my free newsletter for actionable tips on pragmatic, outcome-driven data strategies: https://lnkd.in/gxcJYSYQ

When the boss asks:

“What are your data team’s goals for next quarter?”

Many data leaders freeze.

Then default to:

→ ship 15 dashboards
→ reduce pipeline downtime
→ close more tickets

Sounds reasonable.

But it’s also how data teams quietly turn into dashboard factories.

The real problem:
Most data teams define success in outputs, not outcomes.

If you want to be seen as a strategic partner, your goals must ladder up to the business.

In practice, almost every meaningful data goal fits into one of 5 categories:

1️⃣ Increase revenue, growth, or market share
2️⃣ Decrease costs
3️⃣ Enhance reputation or brand
4️⃣ Strengthen relationships with critical stakeholders
5️⃣ Increase organizational knowledge & decision-making capability

Dashboards, pipelines, SLAs?

Those aren’t goals.
They’re internal activities.

If your quarterly goals don’t clearly map to one of the five categories above…
… then don’t be surprised when leadership struggles to see your impact.

Outputs keep you busy.

Outcomes keep you funded.

♻️ Repost if you’ve ever defined an OKR as “uh… we’ll close more tickets.”

👉 And join 3,000+ data leaders who read my free newsletter for actionable tips on data strategy: https://lnkd.in/g36_8cRq

“I was hired to migrate old reporting into a modern data stack.”

What a huge red flag! 🚩

Here’s the painful trap I didn’t see coming 11 years ago:

I used to think modern tooling = modern impact.

But all it does is ship the same old stuff… just faster and prettier.

It took me way too long to realize:

→ Stack migrations don’t build outcomes.
→ They build artifacts.
→ New stack, same old problems.

Here is how I shifted from shipping data stacks to shipping outcomes:

- We stopped accepting “build me this dashboard”
- We started unpacking decisions and friction
- We focused on solving real problems, not fulfilling tickets

That’s when people started trusting the numbers.
That’s when we got invited upstream.
That’s when we stopped being a dashboard factory.

So when someone says
“We’re modernizing our data stack,”

I always ask:
“Cool. Are you modernizing how you deliver value too?”

Because great tools don’t change anything.

✅ Want to build a data team that drives real outcomes?

👉 Join outcome-driven data leaders from 40+ countries in my data strategy masterclass: https://lnkd.in/gN7ZHYeH

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Sundar Swaminathan

Sebastian Hewing 🚀

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