Hi! How are you holding up? Hopefully it isn’t too hot where you are. 🥵
This week, I’m taking you along with me as I refresh on paid media. I’m bullish on paid media, especially on social channels like LinkedIn and TikTok…that’s where the attention is, and that’s where I learn about new products. Especially products I don’t need to be buying on Instagram, LOL. 🫠
Before we dive into the main content, please check out a quick word from our sponsors, who are kind enough to support the creation of this free-to-you MOPs content 💖:
I just worked with a client to replace Typeform and Calendly with HubSpot and Default, and Default was the easiest part of the migration. 😍 And I’m not the only one saying that! Read how Liza Dukhova, RevOps Manager at Rootly, orchestrated Salesforce and HubSpot to 2x inbound with Default.
Next month, I’ll be defending a spicy 🌶️🔥 position on AI in RevOps live, in person — and I’d love to have you debate me (or just listen in). Spots are limited for this session and it will not be recorded. 😎 Zapier is also offering other really interesting RevOps and marketing content in the larger ZapConnect event. Join us live on September 25 as we show how Zapier turns AI’s raw power into real-world results — lighting the way from cool demos to scalable reality.
Okay, now my guide on paid media for MOPs! 👇 By the way, I do not claim to be a paid media expert…these are notes from my experience in marketing ops, as well as what I’ve learned through online courses. Please do send any feedback you have, I want to make this as useful of a resource as possible!
Tl;dr, the key takeaways I want you to focus on:
Paid media is a data system, not just an ad channel
MOPs owns the technical, attribution, and compliance infrastructure that powers ad performance and reporting. If the backend breaks, the front-end results will likely go haywire.Attribution starts with setup, not reporting
UTM hygiene, campaign naming, and system syncs are foundational. Attribution issues aren’t fixed in dashboards after the fact…they’re prevented during planning and QA. Don’t skip pre-launch setup.Every channel has unique ops requirements
From native forms to DSP uploads, MOPs needs custom QA flows, tracking validation, and lifecycle logic tailored to each source. Basically…you can’t copy and paste from channel to channel, sadly.Content alignment multiplies performance
Ads that map to journey stages, mirror organic content, and reuse winning assets reduce CAC and increase engagement. The paid media needs to fit into your overall customer journey and strategy.Test content syndication!!!
Get a sample lead file and thorough test your content syndication before launching. Also, nurture these leads, don’t send them straight to sales.
Compliance is NOT optional
Consent, data quality, and field-level documentation should be built into every channel and campaign. The last thing you want is an audit of a complete mess, not to mention it’s disrespectful to your audience to not respect their consent and privacy rights.Don’t only report on top-line metrics
Build your metrics stack around business impact, like CPL, SQL rate, ROAS…not just clicks and impressions. Align definitions across MAP, CRM, and BI.Templates and QA are your secret weapon
Your ops stack — UTM builders, first-24 checklists, campaign briefs — will help you make things as seamless as possible and will keep your team from getting buried in manual campaign tickets. If you notice something is painfully manual but could be repeatable/templatized, templatize it!MOPs is the translator between strategy and execution
You’re the one turning campaign ideas into executable, trackable, and reportable systems. Don’t take a back seat and deal with the mess afterwards! This guide helps you prevent as much chaos as possible.
By the way, the guide is a living doc for the community. Please send any feedback you have!
What I’m up to/what I’m studying 💭
Lately, I’ve been catching up on the latest in ads, which is what inspired the topic this week!
By the way, I’m planning on attending (and speaking at/helping run) at least 3 events this year:
Exit Five Drive in Vermont (September) 🌲
ZapConnect online (September) 🧡
Mopza in Anaheim (October)! ☀️
Please do come up and say “hi” (or say hi in the chat!) if you see me there! 👋😁
Dear Sara ✍️
New to marketing operations? On a team of one at your company? Shy/introverted? Wish you could ask a question to an experienced marketing operations professional, without them knowing who you are? Here’s your chance! Submit an anonymous question to me here and I’ll answer a new question in every issue.
Here’s my answer to a question from last week:
How does a company that does not collect consumer records today but would have access to an enormous amount if they did, find value in collecting and utilizing consumer records. Let’s pretend the product is cereal or bread. The cost to store the amount of consumer records associated with those types of products is huge, prohibitive even. Any advice on a starting point to find value and justify collecting consumer records?
This is a great question. When it comes to data, I think about it this way:
What will I use this data for? If there isn’t a clear use case, I’d either keep it safe in a secure data warehouse or not collect it at all. This is great for compliance and also privacy — data should only be visible on a need-to-know basis.
Who needs to see it or use it? I’d keep the visibility permissions as tight as possible, to avoid potential leaks and also to save money. If a tool has data and not everyone needs a license, that’s a money saver.
How will I move the data? At a top-line level, if there is too much data to move around efficiently, I need to rethink my data strategy. A great example of this is when PLG companies try to port every single product usage field into their CRM — CRMs are not designed for that amount of data, so it will slow down your system. BUT even if it doesn’t, the chances you’ll be actually using every single field is low. Make sure the data load is not too huge to action.
As you’ve mentioned, the price of storing data can be massive. I’d personally avoid AWS, it tends to be the costliest, and they trap a lot of startups by offering steep discounts early and getting them locked in. Compare your options and look for other later-stage customers to speak with.
Some data IS really useful. I told you about the PLG company that tried to port in every single field — on the flip side, I’ve worked with companies who didn’t have any product insights, and that really harmed our customer retention efforts. We could have seen negative indicators earlier and saved revenue if we had better insights into how an account was using the product. It’s a balance, and typically the best place to land is somewhere in the middle.
👆 I say all of this to say: yes, you could collect the data. But should you? If you aren’t sure the data will be profitable (when including the cost of storing and actioning it), start small and track your results before going all-in. Maybe just look at customers on certain tiers or certain profiles, as a test group.
To make an argument, I’d:
Find case studies or examples of similar businesses using that data
Lay out a clear plan and trackable metrics for using the data
Make sure I succeed in a small pilot or experiment, so I can use that to justify scaling out the effort
As with most things in business, it’s a fun ROI calculation — do I get more dollars back with this effort than I spend on it? What does the profit margin look like when compared to other ventures? Those kinds of questions will help you decide. 🙂
If you have a moment, will you let me know if you enjoyed this edition of the newsletter? Thank you!
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Thanks for reading,
❤️ Sara