Eddie Reynolds’ Post

“How are we going to use this data?”    This is a question I have asked frequently in my career - that has seriously saved me time, work, and headaches. There’s a wish to have an abundance of data in a quest to fix and scale. And while I pride myself on being a data-inspired marketer, this is a question I constantly have to ask myself, especially when the “we need more data” statement arises. Because, again, less headaches, the better. Having more data isn’t linear to higher performance. It’s just that, more data.    Or, to get technical: it’s the data noise instead of the signal. The signal is the juicy story that will help provide context to fix or scale. But the noise, all of the other data points we often try to grab in an effort to slice and dice, is often where we tend to get lost, especially in today’s digital marketing world, where attribution is over-analyzed. So how do you find the signal, and how do you get disciplined with asking the “how am I going to use this data” question? Simplify. Simplify. Simplify. At the core of your business/function, what’s important? I’m going to guess that net or gross revenue is going to be at the top of this list. Cool. Now work down from there in marketing. While this seems rudimentary, it’s an exercise to get back to the basics and realign what’s important to create a magnet for the signal. Is having a lead source report for every single one of your high-level content "subscriber" opt-ins important, or is it noise? How are you going to use that report? OR, is a lead source report for deals created more important to see if your brand and content efforts are paying off by watching an uptick in direct/organic sources? Asking yourself how you’ll use this data (and how you'll use it to make future decisions) is also a great way to identify what type of reports, data points, and visualizations you need so you’re not staring at a blank report wondering where to begin to get the answers you’re looking for. So while, yes, you may need more data in certain circumstances, knowing how you’ll truly use the data first is what you need.

A quick recap of AWL #29 - How to 3x your SQLs in HubSpot | Part I: the data audit I'm hosting a webinar next Tuesday (6th Feb) about this success case, make sure to check that out (in the comments) 👇 I'm offering a free HubSpot Data Audit for all attendees :) #audit #data #marketing #hubspot

When it comes to hitting revenue targets, do you have enough pipeline visibility? In order to maximize and optimize your opportunities, you need the right data. We share insights into what those data points are and how to optimize them. Learn More: https://lnkd.in/dxSwftir #FullFunnelVisibility #RevenueTargets

I love data. I could geek out on data all day long. More specifically, I love to use data to support what we should AND shouldn’t be doing. And that’s exactly what we’re going to do here with your leadership team. Instead of blindly guessing at what we should be doing, following the current “best practice”, or mirroring what our competitors are doing, let’s use our own data to inform what we should do. To blend or not to blend, that is the question If Shakespeare was a marketer in 2024, I fully believe he would’ve asked his leadership team that question. Most companies use a “blended” story for each team (and sometimes even the entire company 😅): Marketing produced X at Y%, generating $Z.ZZ return Sales produced A at B%, generating $C.CC return The problem with this approach is that you’re using an average of a series of averages. This is a BIG no-no. And this plays into exactly what we should be doing - looking at the full story to understand what’s going on. So that means taking the Marketing “bucket” and breaking it down by the core channels, such as lead gen, inbound, events, referrals, etc. I’m going to keep it simple here and focus on the first two, but you can and should do this for as many channels that you currently use or historically used. This is where the fun begins as you’re now able to see how the different channels play out for driving new business. And this is where you’ll likely start to see some questions like the ones in the yellow text boxes of the image come up from your leadership team: *Lightbulb moment initiated* Congratulations, you’ve now shown that not all marketing efforts and channels are equal at driving new business. The strategy and tactics you use will all play out differently not just based on a binary yes/no if you use certain channels, but will vary based on the investment level in each, how well they’re executed, and so on. This example is VERY common. With this data, you are able to show your leadership team exactly how your current marketing strategy + channels are (or aren’t) performing. If you continue to focus on lead gen, you’ll simply see the above lead gen results on a larger (read: inefficient) scale. But if you focused more on inbound, what would that look like with 2x, 3x, or 5x the resources applied? The beauty is they don’t need to be net new resources, but can be reallocated from lead gen, meaning you spend the same amount, but each dollar goes drastically farther in driving qualified pipeline and future revenue.

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Data overload? Struggling to decode your marketing analytics? You're not alone. Here's the issue.  We live in a world where data is everywhere. But, all that data is useless if you don't know how to interpret it. 𝐒𝐨, 𝐰𝐡𝐚𝐭'𝐬 𝐭𝐡𝐞 𝐚𝐧𝐬𝐰𝐞𝐫? You need to turn those numbers into a narrative. - Start by identifying your key metrics.  - Then, break them down into smaller, easier chunks. 𝐓𝐡𝐢𝐬 𝐞𝐥𝐢𝐦𝐢𝐧𝐚𝐭𝐞𝐬 𝐜𝐨𝐧𝐟𝐮𝐬𝐢𝐨𝐧 𝐚𝐧𝐝 𝐡𝐞𝐥𝐩𝐬 𝐲𝐨𝐮 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝: What's working and what's not. Next, correlate your data.  Identify patterns and trends, and Use that information to make better decisions. Lastly, share your findings.  Make sure everyone in your team understands your data narrative. Yes, it's not easy.  But remember, it's not about the amount of data you have.  It's about how well you can make sense of it. Agree with me? Share your thoughts in the comments. --- 𝐑𝐞𝐩𝐨𝐬𝐭 𝐭𝐡𝐢𝐬 𝐬𝐭𝐫𝐚𝐭𝐞𝐠𝐲 ♻️ 𝐟𝐨𝐫 𝐲𝐨𝐮𝐫 𝐧𝐞𝐭𝐰𝐨𝐫𝐤! 𝐒𝐭𝐚𝐲 𝐭𝐮𝐧𝐞𝐝 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐮𝐩𝐝𝐚𝐭𝐞𝐬 𝐛𝐲 𝐜𝐥𝐢𝐜𝐤𝐢𝐧𝐠 𝐭𝐡𝐞 🔔 #𝐦𝐚𝐫𝐤𝐞𝐭𝐢𝐧𝐠𝐚𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 #𝐝𝐚𝐭𝐚𝐦𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 #𝐛2𝐛𝐦𝐚𝐫𝐤𝐞𝐭𝐢𝐧𝐠 #𝐥𝐞𝐚𝐝𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧.

So, You Have A Problem… With Top-Of-Funnel Data, Processes & Reporting

Supermetrics held a very informative webinar last night. Some key thoughts that were called out: 🔸The “marketer” role has become a technical role. 🔹in large organizations there is often a disconnect between Marketing and IT departments - for this reason, often Marketing embarks on getting an expensive tool or somewhat duplicate capabilities that already exist somewhere in the company. (So instead, some little help is needed in finding the internal capability and bringing them up to speed with some light consulting and training.) ◾Good guidance around how to embark on data driven marketing use cases (from finding use cases through scoping out the data sources, where data will be stored, how the results will be used) ◽ A more “nerdy” thing: Marketing Mix Modelling is gaining popularity and is now becoming easier due to the release of several open-source libraries dedicated to this - and it’s also easier to gather the required data than it used to be previously. Companies have multiple ways of going about it, but a hybrid approach might work well by drawing mainly on internal resources, while getting some external help to bridge the gaps. 🔺 B2B is a bit of an “orphan” area in the sense that most marketing tools started out with B2C focus, so there isn’t really anything inherently tailored to B2B marketing. (Of course, there is a lot that one can do, but it’s full of challenges due to multiple factors, e.g. sales cycles sometimes exceeding 16 months). There is probably more: I didn’t take notes so these were the ones that stayed with me. I also didn’t manage to watch all the sessions, so will have to look back later to check the rest. Many thanks to Zach Bricker, Igor Skokan, Khrystyna Grynko and Emily Gustin - and all the organizers from Supermetrics.  — Follow me for posts on #digitalmarketing #data #analytics, #BigQuery and #eprivacy, and hit the bell on my profile to receive updates.

I like data and analytics, but many marketers see it as the boring part of the job. Okay, perhaps they are not entirely wrong. But the thing is: data is important. Without it, you don't know how successful your campaigns really are, and where you can optimize. Our latest blog post is about how CMOs can help their team nail data and analytics, and get the desired ROI from your hard work ⬇️ https://hubs.ly/Q026Yq880 #MarketingAutomation #DataAnalytics #CMOTips #MarketingStrategy

If you are only tracking volume metrics for your funnel you are missing out big time. Because the two better pieces of data are conversion and velocity. Who cares if the MQL (Sales Ready) volume is at 100% goal? (besides you if you are comped on it but usually the whole team isn't!) It matters more on how sales-ready leads are moving through the funnel to create revenue! And it’s much easier to pick out insights to create action for improvement. Showing what the data tells you for volume versus conversion rate is a good example of this: >Data: Volume goal is not attained >>Takeaway: You need to figure out why you aren’t hitting that goal >Data: Conversion rate from Meeting Booked to Opportunity is 50% >>Takeaway: You need to dive in and see if there is a quality issue for meetings, if AEs are trained to convert those to pipeline, or if the definition/fit criteria for a meeting is not defined well enough. See which one is more useful and drives immediate action? But still many companies are only reporting on their volume goal attainment for each funnel stage. Why? Well, a lot of that has to do with maybe their data structure and method of reporting doesn’t allow them to do full funnel conversion reporting. If this sounds like your org and want some advice/resources dm-ed to you just comment "funnel" on this post and make sure we are connected! #revenuegrowtharchitecture #funnelmetrics #funnelarchitecture #marketingoperations