Roos Reitsma’s Post

I’m not at all against measuring touchpoints in a customer journey. But you need to be careful with the value you attach to this data. If someone clicks a branded paid search ad before filling out a form, it means just that. It doesn't mean branded paid search "performs better than..", "has X ROI", or "generates X pipeline". 

Was this an inbound or outbound opportunity? Ah, the dreaded discussion. And the dreaded honest answer: a bit of both. There is a solution for this. A good GTM team has sales, marketing, CS, and product working closely together. This makes fighting over who takes credit for an opportunity counterproductive. We all know this. But what’s the alternative? First, the goal. Why do you need to know if it’s inbound or outbound? Two reasons: 1️⃣ Sales commissions: we reward sales reps for creating an (outbound) opportunity 2️⃣ Budgeting decisions: leaders need to know what’s driving incremental revenue, so they can invest in what works. Now for the alternative: double funnel + incrementality tests. How it works: 1️⃣ 𝗨𝘀𝗲 𝗮 𝗱𝗼𝘂𝗯𝗹𝗲 𝗳𝘂𝗻𝗻𝗲𝗹 𝘀𝘆𝘀𝘁𝗲𝗺. One funnel is for target accounts, and the other is for all other prospects. Sales reps team up with marketing, CS, and product to pursue high-value ICP accounts. That’s the target account funnel. If these accounts become an opportunity, the account owner gets a commission even if the opportunity came through an inbound demo request. Other prospects can only come inbound, that’s the “other” funnel. Sales reps don’t get a commission for these. They don't chase these accounts. These aren’t target accounts. In Salesforce, manage the target account funnel in accounts/contacts and the inbound funnel in leads. Hubspot has a specific target account funnel built in. 2️⃣ 𝗗𝗼 𝗶𝗻𝗰𝗿𝗲𝗺𝗲𝗻𝘁𝗮𝗹𝗶𝘁𝘆 𝘁𝗲𝘀𝘁𝘀. Yes, it’s hard. But it is the best basis for budgeting decisions. If you’re doing ABM/outbound, you likely have a manageable number of ICP accounts. Get them all in the CRM or CDP and you can start testing. To find incremental revenue, hold out some accounts. Important: sales is not off the hook! This isn’t just about marketing’s added value. Do you face challenges separating inbound and outbound opportunities? 

🧪 LinkedIn experiment update 🧪 I’m 2 out of 6 months in, and… I have 7 learnings and observations to share. In random order: 1️⃣ 𝗜 𝗺𝗮𝗱𝗲 𝘁𝗵𝗲 𝗰𝗹𝗮𝘀𝘀𝗶𝗰 𝘂𝗻𝗱𝗲𝗿𝗽𝗮𝗻𝘁𝘀 𝗴𝗻𝗼𝗺𝗲𝘀* 𝗺𝗶𝘀𝘁𝗮𝗸𝗲🙈. Step 1: post and comment on LinkedIn. Step 2: 🦗 …Crickets… 🦗. Step 3: 25 valuable connections. I made 4 valuable connections. I forgot about step 2! Working on it. Advice is welcome 🙏🏻 2️⃣ 𝗬𝗼𝘂𝗿 𝘄𝗲𝗮𝗸𝗻𝗲𝘀𝘀 𝗺𝗮𝘆 𝗯𝗲 𝘆𝗼𝘂𝗿 𝘀𝘂𝗽𝗲𝗿𝗽𝗼𝘄𝗲𝗿. I always thought having ‘only’ 5 years of GTM/ops experience at B2B tech scaleups was a weakness, but the other 10 years doing everything everywhere else gave me a unique perspective I should lean into more. 3️⃣ 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴, 𝘁𝗿𝘆𝗶𝗻𝗴, 𝗮𝗻𝗱 𝗳𝗮𝗶𝗹𝗶𝗻𝗴 𝗶𝗻 𝗽𝘂𝗯𝗹𝗶𝗰 𝗶𝘀 𝗮𝗻 𝗲𝘅𝗰𝗲𝗹𝗹𝗲𝗻𝘁 𝗺𝗲𝗻𝘁𝗮𝗹 𝗲𝘅𝗲𝗿𝗰𝗶𝘀𝗲. Shipping - taking action - is important. But also hard. Especially if you have perfectionist tendencies. Posting on LinkedIn has helped me overcome this in other areas as well. 4️⃣ 𝗖𝗼𝗻𝘁𝗲𝗻𝘁 𝗺𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 𝗶𝘀 𝗵𝗮𝗿𝗱! Deep respect for those who can do this well. Before posting, I’d see the ‘broetry’ on LinkedIn and think it looks lazy (sorry). But writing a good post is a lot harder than it looks! I’m not trying to perfect this, but I am having fun trying to improve. 5️⃣ 𝗖𝗼𝗺𝗺𝗲𝗻𝘁𝗶𝗻𝗴 𝗶𝘀 𝗺𝗼𝗿𝗲 𝘁𝗶𝗺𝗲-𝗰𝗼𝗻𝘀𝘂𝗺𝗶𝗻𝗴 𝘁𝗵𝗮𝗻 𝗽𝗼𝘀𝘁𝗶𝗻𝗴. This surprised me, but it makes sense. You can write any post anytime, but commenting needs (1) a post worth commenting on, (2) thinking of something valuable to add, and (3) writing the comment. 6️⃣ “𝗜𝗻𝘀𝗽𝗶𝗿𝗲” 𝘀𝗵𝗼𝘂𝗹𝗱𝗻’𝘁 𝗯𝗲 𝗮 𝘃𝗲𝗿𝗯, “𝗯𝗲𝗶𝗻𝗴 𝗶𝗻𝘀𝗽𝗶𝗿𝗲𝗱” 𝘀𝗵𝗼𝘂𝗹𝗱 𝗯𝗲. A few people told me I inspired them. That’s great, but I wasn’t actively inspiring, it happened without me doing or knowing anything. The person who is inspired is actively taking inspiration, like learning. So whatever you're doing, you never know who you might inspire. 7️⃣ 𝗟𝗶𝗸𝗲 𝗼𝗿 𝗰𝗼𝗺𝗺𝗲𝗻𝘁 𝗶𝗳 𝘆𝗼𝘂 𝗳𝗶𝗻𝗱 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝘃𝗮𝗹𝘂𝗮𝗯𝗹𝗲: I used to read a post, learn from it, and move on. Hitting 'like' is 0 effort and shows appreciation. I now try to do this more on other platforms too. And: likes and comments are a bad measure of who appreciates your posts (see also 6). *For those confused by 1️⃣, see video

data > insights > action Early-career baby Roos had a manager at Microsoft - the one and only Jurrien Bruijns - who always ensured this concept was front and center on my mind. It’s a cycle. Or it should be. Action produces data that provides insights, that leads to new action. My job was to make sure the cycle didn’t break. Sounds simple right? I quickly found putting data>insight>action on a slide is easier than doing it. At Microsoft they let you sink a bit so you’ll learn to swim. I was sinking deep into campaigns, territories, and stakeholders. I needed to apply a healthy dose of Pareto principle to start swimming! I learned: 80% of the impact comes from the 20% effort you put in just before ‘ACTION’. You need to make sure: ✅ All initiatives have a clear, measurable goal ✅ Flexible budget is kept aside for optimizations ✅ The tracking to measure the goal is set up correctly ✅ Decide upfront what you'll do if you don't meet the goal ✅ There's a central place for results and learnings for future initiatives ✅ Schedule regular check-ins to track your progress and plan next steps ✅ Have a ‘holdout’ group (even if it’s a benchmark or past) for comparisons ✅ Most importantly, ensure career growth comes from learning quickly and improving, not from framing the initiative as a success. Are any of the above points holding back your team's ability to keep learning?

You can stare at spreadsheets all you want, but without TRYING anything you’ll often end up with nothing more than ideas and hypotheses. So, let’s cook up some real insights! 👩🍳 Ingredients: - An idea, hypothesis, or belief - A test group - A control group - A target variable - A way to only expose the test group to the idea - A way to measure the target variable separately for the two groups Tools: - Test/learning cards - Significance calculator (google it) Now you may have heard people say that A/B testing doesn’t work. You need enormous volumes to reach significance. Or that significant results can become the complete opposite when you try again. This might be true when you test button colors or subject line variations. But I'm talking about your big initiatives. Hold out a control group whenever possible to understand the incremental revenue impact. Would you like to try this recipe? Ask me for the test/learning card templates!

I learned a valuable lesson about data from a sales manager. She told me how she had the BDR’s update a few numbers in a dashboard manually every week before their meeting 🧑💻. I said that I could easily automate that for her using CRM data. Just give me an hour and it’s done! No thanks, she said. For 3 reasons: 1. She wanted BDRs to prepare and examine their weekly numbers. She made sure they did that by having them manually input the data. 2. She didn’t want to get into any discussions about data validity during the meeting. 3. She checked these numbers with the CRM data. Differences meant something was off in the CRM. Dashboards and reports are useless if nothing changes. And too often that’s what is happening. Discuss the numbers regularly. Tie actions to them. Review and validate before meetings. If manual entry helps you achieve this, why not?

I’ve worked on 3 different lead scoring and intent data setups, costing $200k+. I learned a lot from these projects. Here’s how to calculate if it’s worth the investment, AND learn which intent signals have the most value. First, let's agree on the goal. Intent data and lead scoring serve two purposes: 1. Identify and prioritize accounts to target 2. Improve how GTM teams engage with accounts Next, the analysis! 📊💃 𝟭. 𝗜𝗱𝗲𝗻𝘁𝗶𝗳𝘆 𝗮𝗻𝗱 𝗽𝗿𝗶𝗼𝗿𝗶𝘁𝗶𝘇𝗲 𝗮𝗰𝗰𝗼𝘂𝗻𝘁𝘀 𝘁𝗼 𝘁𝗮𝗿𝗴𝗲𝘁 Can the intent data predict which accounts become opportunities? Regression analysis will help you find out. Find a good analyst. Use intent data from a few months back. Correlate it with opportunities created within that time frame. In my experience, the intent data - while significant - explains only 5-15% of outcome variance. Is that enough? 𝟮. 𝗜𝗺𝗽𝗿𝗼𝘃𝗲 𝗵𝗼𝘄 𝗚𝗧𝗠 𝘁𝗲𝗮𝗺𝘀 𝗲𝗻𝗴𝗮𝗴𝗲 𝘄𝗶𝘁𝗵 𝗮𝗰𝗰𝗼𝘂𝗻𝘁𝘀 Hide the intent data from some target accounts (e.g. hold out one region). After a few months, you should see more opportunities in accounts with intent data compared to those without. In my experience, a few key signals work best. Don't overcomplicate it. How to find those key signals? (1) ask your best reps, and (2) use the regression analysis from step 1. Stop basing intent data and lead scoring decisions on opinions. Calculate incremental revenue instead.

2024 tech layoffs: >75.000 | Median cash raised (series C): ⬇️ -62% vs. Q1’21. In Q2’24, we still need to do more with less. But what does that mean? ❌NOT: do a little less of everything ✅ INSTEAD: carefully choose a few things to double down on, stop the rest Ever heard of peanut buttering? Spreading resources too thin. You'll see better outcomes focusing on a few key areas. At Microsoft, we called it ‘fewer pebbles, bigger waves’. (don't worry: that's all the tech jargon I have in me today) Why is it so hard? First, it's scary. What if pipeline completely dries up? Second, we overestimate how many different things we can do. And we underestimate the value of doing fewer things better. Here's how you do it: 1️⃣ Sit down with your team. List what you don’t think adds value. 2️⃣ Score them. Rank based on resource savings, testing ease, and safety. Pick the number 1 candidate. 3️⃣ Create a test card (DM me). Make sure there's a good measurement plan in place. Involve a smart analyst. 4️⃣ TURN IT OFF - scary, I know 5️⃣ After about 90 days, analyze the results and decide: back on, or off? Below are some ideas. Things I see clients do that appear to add value, but don’t always do. What can you stop doing?

8/10 scale-ups I work with suffer from silos and lack of focus. It’s almost inevitable. Going from startup to scale-up, all the attention goes to acquiring, onboarding, and retaining new customers. Meanwhile, the median headcount grows 10x between Series A and D (Carta). That's bound to cause some friction. There’s no magic formula to fix this overnight. But there is something simple that costs 0,00 and usually helps. ✨ 𝗔 𝗡𝗼𝗿𝘁𝗵 𝗦𝘁𝗮𝗿 𝗺𝗲𝘁𝗿𝗶𝗰 ✨ And if you are like me you now think: but over-focusing on one metric leads to other problems! And what about the roles and responsibilities of each department? Yes and yes. Not ONE metric, only a most important one. 𝗥𝗲𝗾𝘂𝗶𝗿𝗲𝗺𝗲𝗻𝘁𝘀: 1/ Makes the flywheel fly. Doing this well makes everything easier. A hint: usually it’s your customer achieving what they hoped for with your product. That leads to more proven value, more referrals, and more customers. 2/ Not revenue or profit. Chasing these may lead to short-term impacts that hurt the long term. E.g. you could simply raise prices or stop investing in better product features. 3/ Visible and alive. Have quarterly reviews about it. Award champions who impact it. Have a visual metaphor of it around the office. 4/ Everyone’s on board. Each department can explain and measure how they impact the North Star (yes, even legal, finance, HR) Do you have a North Star? Is there anything I need to add to this checklist? PS: Matt Lerner recently published a book that covers North Stars in a great way. It’s short and gets to the point. Get it!