Jenna Alburger

Only 26% of Companies with ABM Motions Actually Measure It Properly 😰 This means the other 74% are measuring its effectiveness by standards like total lead volume or click-through rates. Whereas effective metrics are more like: 🎙️Influenced pipeline from ABM activities 🙇‍♀️ Number of engaged ICP accounts Both of these are only being tracked by 1 in 3 marketing teams as well! Most of the time, not measuring ABM effectiveness isn’t down to ignorance but the challenges in doing so. Three ways that anyone can make it easier to start tracking: 1️⃣ Use tools that seamlessly share data between marketing and sales. This allows you to easily track leads, accounts, their activities, and ABM's influence. 2️⃣ Establish clear definitions and data governance practices. Regularly clean and validate your data to ensure high quality. (Big alignment needed between sales and marketing here). 3️⃣ Invest in specialised ABM tools. These deeply track account journeys across channels and will identify high-propensity accounts. I’m definitely missing some others from this list too so please add below!

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Monster checklist + Mega cheat sheet = All the ABM advice and questions in a single post.📌 💡ICP  1. Are the target accounts listed beyond the basic technographic and Firmographic data? 2. Is there a fitting market segmentation for your product/service? 3. Are all the buying committee members included along with the account blockers? 4. Have you mapped out the buying committee's hierarchy and influence? 🏆Narrative & UVP 5. Did you lay out the demand mapping from the buyer's perspective? 6. Their context, actions, learnings, and objections. 7. Where are your buyers looking for options? 8. What can attract their interest? 9. What do they struggle with most? 10. What can persuade them? 11. What objections do they have? ✨Engagements 12. Do you have any Industry research reports? 13. Are you hosting a podcast/community to invite your ICP? 14. How many micro-events can you do each quarter? 15. Do you have PR articles to submit to reporters? 16. Do you have a plan for marketing on Events? 17. Have you identified any vendors/partners for content collaboration? 18. Can you conduct your industry poll/Survey? 🎉Outreach and Activations 19. Do you have the email nurturing sequence for the most engaged accounts? 20. Have you strategized ABM playbooks for the High Fit and High Intent accounts? 21. Have you personalized your outreach messages for the most engaged accounts? 22. Are you leveraging intent data to time your outreach? 23. Do you have a multi-channel approach for your outreach strategy (email, social media, direct mail, phone)? 24. How are you warming up your target accounts before reaching out? 25. Are you using account-specific content in your outreach? 26. Do you have a Hyper-personalized pitch and the relevant case study for a Direct mail campaign? 27. Have you set up your Marekting+Sales+Calling cadence? 28. Have you established a follow-up cadence and strategy? 29. Do you have the right Search+LinkedIn+Retargeting Strategy? 🙌Sales 30. Have you aligned your sales and marketing teams on account priorities? 31. Are your sales reps equipped with account-specific insights and content? 32. Do you have a clear handoff process from marketing to sales? 33. How are you handling objections specific to each account? 34. Are you leveraging case studies and testimonials that resonate with your target accounts? 35. Do you have a strategy for engaging accounts that have gone cold? 36. Are you continuously nurturing accounts post-sale to drive renewals and upsells? 🚩Metrics & KPI 37. Are you tracking the engagement metrics of your outreach efforts (open rates, response rates, meeting set rates)? 38. Can you calculate your Visitor to opportunity ratio? 39. Do you know the total percentage of accounts engaged? 40. Have you identified any new verticals or markets? 41. Have you considered existing customer renewals & High-Value Accounts? 42. Can you track the Deals moving from opportunity to Sales Qualified?

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😳 In Go-To-Market, you always hear "iterate", "test"... Ok.. But what? How? Many marketers actually play lottery (you know what I mean)... Because GTM is not about being good with paid ads... And "test and learn" is great... But if you go around testing random things on top of your mind... You will always end up feeling unclear on what to write, who to target, how... GTM is a business discipline. The secret about GTM success is in the research, analysis and business interpretation... This preliminary work makes or breaks your strategy since it brings clarity and structure in your testing. The right way to approach GTM is: /// 1 - Insights gathering \\\ + Queries Analysis: ↳ what people are actively looking for? ↳ In what volume? ↳ What are the underlying trends in the queries? + Competitive Analysis: ↳ Who are your competitors? ↳ What people say about them (the good / the bad)? ↳ Who do they serve / who they don't? + Social listening ↳ What people say on socials (frustrations, verbatim, level of awareness)? + ICP Definition: ↳ What are the market segments that suffer and are underserved? /// 2 - Data-Driven Hypothesis \\\ + Positioning: ↳ How to adapt your perception to these addressed segments? + Messaging: ↳ What are the USP and angles to test BASED ON THAT DATA? + Channels: ↳ What are the channels to test BASED ON THAT DATA? /// 3 - Data-Driven Hypothesis \\\ + Iterative testing ↳ Test all your hypothesis. That way you can have structured hypothesis based on actual intent and observations which DRAMATICALLY improve your odds of success. This research work takes up to 1 or 2 weeks... Now you can follow this process, or: I have built a tool that will do all of part 1 and 2 for you in under 4 minutes. It is based on the process I used with Fortune500 companies and some other startups. It is for you if you: → Launch new markets; → Launch new products; → Do GTM or acquisition for clients; Here you go: https://lnkd.in/gf7HmBVU Go Get It 🤟 #gotomarket #ai #marketing

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Too many #GTM teams are mistaking interest (intent) for fit as Markus Ståhlberg at N.Rich mentions in his post below. But because a company is showing interest - it doesn't mean that they will actually buy. More important;y, it doesn't mean that they will land and expand at a high ACV. As I've been debating Kerry Cunningham at 6sense, #intent data is not predictive of accounts that will actually land and expand. If you define your ICP using the dark attributes (those that go beyond firmographics and technographics and actually include the operational, executional, cultural characteristics of the accounts that give you the greatest revenue growth & are getting the most value) - then you can match signals that will give you the greatest predictability of an account moving forward in a big way. If you layer on business problem profile signals, personality signals and account intelligence then you will have a predictive model that will give you the greatest chance of targeting accounts where you will have the lowest chance of losing and the highest chance of expanding after the deal is closed. While intent signals are not predictive like ICP signals, business problem profile signals and personality signals -- it can help you prioritize the accounts that you should be focusing on now. This is why it's important that you define your ICP in a predictive way vs. using intent data as the basis of your ICP. In the article below, I discuss the signals and account insights you should be adding on top of intent data: https://lnkd.in/ewtpg2xS You can sign up for tomorrow's account insights webinar at: https://lnkd.in/efFuQ-8V You can learn about our #ICP management solution here: https://lnkd.in/eCzP5Gbs You can schedule a time to discuss your ICP here: https://lnkd.in/et6GhHFu

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Ask your marketing / growth agency this asap. If they don't have a good answer, you're in trouble.   I call it The Table Test -   "If your agency sat at a table with 10 other agencies, what could you say no one else can?"   In an era of AI, copycats, and few leaders, marketing is becoming commoditized.   Marketing's become a sea of sameness.   Most brands are blending in vs. standing out.   A total blow for growth.   But your marketing / growth partner is a huge opportunity to change this.   But most don't have what it takes.   To find out, run The Table Test.

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Today’s read: the *emerging* playbook behind the next crop of breakthrough startups 👇

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The biggest mistake you can make in D2C is not to have an AOV roadmap. A consistent theme I see in brands that are shrinking or flat are AOVs that not growing. The reason is really simple: Ad costs are going up. They'll never come down for Meta and Google. Its a tax that keeps growing for any D2C brand. The easiest way to mitigate this is by moving upmarket consistently every year.

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💰 GA4 is the most underutilized tool for profitable growth. Yet 90% of brands set it up wrong with useless data. Do this asap if you ❤️ free money:   1. Future-Proof Your Tracking: Use tools like Elevar or Blotout.   2. Create Micro-Conversions: Track views, adds, etc., beyond your main conversion.   *This gives you a 100% server-side, full-funnel view of performance.   3. Push Data to GA4: Send your new, clean, bullet-proof data set to GA4.   4. Analyze Your Funnel: Go to Reports > Business Objectives > Purchase Journey in GA4.   5. Compare each step in your funnel to industry benchmarks.   6. Focus on CRO: Identify the weakest funnel step and go all-in on CRO.   7: Study Competitors: Look at equivalent pages from proven competitors and adjacent companies.   *Find what they're doing that you're not.   8: Use Qualitative Tools: Tools like Clarity can help identify what's driving bad UX.   9: Deploy New Versions: Use no-code tools to roll out new versions of the problematic page template.   10: A/B Test: Test the new version against your Control.   11: Watch conversions soar.   Bonus: Segment by device, traffic source, etc., if you have enough data.   Free money, anyone? 🚀

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5 CRO mistakes brands need to stop making: (Unless you're OK with mediocre conversion rates) 1️⃣ Treating CRO as a side project Most brands run sporadic tests with no overarching strategy. By not prioritizing CRO, you're missing out on massive growth. my Hypothesis: Implementing a structured testing program will increase conversions by identifying and solving customer pain points. 2️⃣ Focusing on conversion rate over revenue Conversion rate is a vanity metric in isolation. It doesn't matter if more people convert if they're spending less. Instead also focus on metrics that impact your bottom line: revenue, contribution margin, return rates, and so on. 3️⃣ Not segmenting results to learn more After a test ran, you should segment the results to figure out what was learned and where it worked. New vs. returning customers have different needs & behavior. By putting them together, you water down your results and come up with new insights & ideas for follow-up tests 4️⃣ Ignoring qualitative data Numbers alone don't tell the full story. Pair quantitative data with customer feedback & user recordings. Get the why behind the what. 5️⃣ Not having a post-test plan The test isn't over when you have a "winner". You need to analyze results & share learnings with your team. Develop a plan for iterating on the outcome. P.S. Since you read the entire thing, I guess you could use some ideas... I handpicked 94 ideas for online shops and added what data points to look at to prioritize them. Want it? Like & Comment "Sharing Is Caring" & I'll DM it to you!

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7 Traits of a great SEO: ‌ → Doesn’t refresh rankings every day → Loves links → Open minded → Collaborates with paid team → Networks with SEO’s → Loves failed tests → Analytical What have I missed?

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Don't even THINK about A/B testing your 7-figure site without reading this first. So many agencies get enterprise CRO wrong. They make 2 critical mistakes: ❌ Running site-wide tests without proper tracking ❌ Making huge changes to the entire site at once The results? Confused customers, tanked conversion rates, and lost revenue. After helping over 3500 brands capture $100M+ in revenue, here's what we've learned: ✅ Base test ideas on solid data, not just best practices ✅ Start with smaller, incremental tests ✅ Monitor results daily & filter by audience segment ✅ Only scale tests that are clear winners See the difference? If you want enterprise CRO that WORKS, you need an agency that gets it. And when it comes to optimizing for peak performance... Last year, many Ecom brands scrambled at the last minute to optimize their sites for the Q4 rush, with mixed results. Those who started their CRO efforts early saw the biggest gains. The time is now! Don't make the mistake of waiting until Q4 hits. Start optimizing now for a successful end to the year. DM me if you need any help

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💡 Rethinking CRO: It’s Not Just About the Numbers 💡 Conversion Rate Optimization is often seen as a game of numbers—more clicks, more conversions. But the truth is, effective CRO isn’t only about chasing percentages; it’s about understanding human behavior. Here’s what’s lies beyond the data in CRO: 1️⃣ Intent vs. Expectation: Users land on your site with an intent, but their expectations evolve as they navigate. Bridging that gap between intent and the unexpected rewards at every touchpoint is where the magic happens. 2️⃣ Micro-conversions Matter: Too often we obsess over the final conversion. Pay attention to smaller commitments—clicking a button, viewing a product, signing up for a newsletter. These micro-conversions tell the real story of user trust and engagement. 3️⃣ Emotional Triggers: Data doesn’t capture everything. Sometimes, it’s the subconscious cues—color, phrasing, timing—that tip the scale. Optimization isn't just about function; it’s about emotion. 4️⃣ Friction Isn’t Always Bad: A little friction can actually heighten anticipation and perceived value. Not all optimizations should make the path smoother; some should add just the right challenge to engage users more deeply. For one client, we added an additional step to customize a product selection, which surprisingly increased conversion by 12%. The extra friction made users feel more in control of their choices and boosted confidence in their purchase. If you’re only tweaking headlines and buttons, you’re missing the deeper layers that drive meaningful connections and loyalty. What are you focusing on beyond the obvious in your CRO efforts? #CRO #UserExperience #ConversionPsychology #MarketingInsights #WebOptimization #CustomerJourney

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Let's bust a common CRO myth: You can copy someone else's "winning formula" & see instant results. The truth: ↳ What works for one site might not work for yours. ↳ Effective CRO is data-driven & unique to your brand. ↳ CRO isn't about implementing random "best practices." So, how do you build a successful CRO strategy? By focusing on these four key areas: 1. Data-Driven Decisions: ↳ Conduct thorough user research. ↳ Implement rigorous A/B testing. ↳ Analyze and interpret your data. ↳ Understand user behavior patterns. 2. User-Centric Design: ↳ Create intuitive navigation. ↳ Communicate a clear value proposition. ↳ Optimize for mobile experiences. ↳ Personalize user journeys. 3. Conversion Funnel Optimization: ↳ Refine your landing pages. ↳ Reduce cart abandonment. ↳ Streamline the checkout process. ↳ Engage users post-purchase. 4. Psychological Triggers: ↳ Leverage social proof. ↳ Use scarcity and urgency wisely. ↳ Build trust with your audience. ↳ Implement reciprocity in your strategy. Remember, it's all about finding what works for your unique audience. Test, analyze, and iterate. Create a CRO strategy that's tailored to your business and customers. Like and repost ♻️ to help other e-commerce professionals. Follow me (Samuel Hess) for more CRO insights.

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My attempt at doing something Linkedin HATES: writing a nuanced post on marketing attribution. Here goes: There are three primary forms of attribution: 1. Funnel Attribution 2. Multi-Touch Attribution 3. Self-Reported Attribution And there are three primary ways to evaluate them: 1. What they measure 2. What they do great 3. Inherent bias and issues Here is how I break them down with clients: (𝟭) 𝗙𝘂𝗻𝗻𝗲𝗹 𝗔𝘁𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻 > Measures: the 3 Vs of your sales process (Volume, Velocity, conVersion) from pre-Opportunity stages to Closed Won. Relative to the channel/offer "Tipping Point" that lead to sales getting involved. > Great at: understanding what you send for sales follow-up and conversion rates. Helps identify friction/bottlenecks in the sales process. Useful for all teams: marketing, SDRs, Sales, as the data connects marketing to the full sales process. Leading indicator and easy to analyze. > Bias/issues: single touch model will often credit certain channels/offers more than others. Really hard to execute and get a useful dataset. (𝟮) 𝗠𝘂𝗹𝘁𝗶-𝗧𝗼𝘂𝗰𝗵 𝗔𝘁𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻 > Measures: ALL the touchpoints on the buyers journey. Assigns some % of $s from related Opportunities to the touchpoints. Used for lift analysis and buyer journey mapping. > Great at: filling the gaps Funnel Attribution single touch insight gaps. Lift analysis to attempt to see the incrementality of channels/offers. Visualizing the full buyers journey of all trackable touchpoints. Pretty easy to implement. > Bias/issues: Can prove anything works, especially if including ALL Account touchpoints. Will inflate achievements of high volume activities. Hard to analyze due to so many touchpoints and complex % assignments. Usually, only useful for marketing. Lagging indicator. (𝟯) 𝗦𝗲𝗹𝗳-𝗥𝗲𝗽𝗼𝗿𝘁𝗲𝗱 𝗔𝘁𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻 > Measures: qualitative data from what our clients tell us. Through research, form fills, and interviews. > Great at: uncovering insights into channels/offers that are difficult to track. Gives a more nuanced perspective. > Bias/issues: recency bias. Client not caring enough to give useful information as it only benefits the vendor. There is so much more to dig into but that's enough for this post. So TLDR: there are 3 general types of attribution. They are all useful. They all have issues and bias. And they all measure differently. My general advice is to implement them in the order above.

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5 Brutal GTM Mistakes Killing Your 2024 Growth (and How to Fix Them)🙂 ✔️It's time to switch your GTM in the cookieless world. ✔️The old ways of lead gen, SEO spam, and cold outreach may not be enough today. Here are the 5 FATAL MISTAKES holding you back: **Mistake #1: Demand Capture Over Community Building: ❌ Old Way: Throwing money at ads, SEO, and cold outreach in a desperate bid for leads. ✅ New Way: Invest in category creation, thought leadership, and building genuine relationships in the communities where your ideal customers gather (hint: it's not just LinkedIn!). **Mistake #2: Form Fills Over Human Connections: ❌ Old Way: Focusing on lead volume and MQLs, treating prospects like numbers, not people. ✅ New Way: Prioritize lead quality over quantity. Personalize outreach, understand customer needs and build trust through authentic interactions. ❤️ **Mistake #3: Star Performers Over Playbook Power: ❌ Old Way: Relying on a few sales superstars while neglecting to document and share best practices. ✅ New Way: Develop repeatable, scalable playbooks that empower your team to win deals, not just the "lucky few." **Mistake #4: Pipeline Volume Over Pipeline Velocity: ❌ Old Way: Getting stuck in a lead generation rut, focusing on the number of leads, not how quickly they convert. ✅ New Way: Track and optimize pipeline velocity and win rates and build a high-intent pipeline of qualified prospects ready to buy. **Mistake #5: Silos Over Synergy: ❌ Old Way: Marketing, Sales, and Customer Success operating in separate silos, leading to misalignment and missed opportunities. ✅ New Way: Foster cross-functional collaboration. Break down the walls, share data, and work as a united front to deliver exceptional customer experiences. What other GTM mistakes have you encountered?

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$1,000 says your Meta agency is NOT doing this. If your reports don’t break out by: 1. Funnel 2. Audience type You’re missing clarity. Funnel breakdown: ✅ Views ✅ Adds to cart ✅ Starts checkout ✅ Purchases Audience breakdown: ✅ New (cold traffic) ✅ Engaged (warm traffic) ✅ Existing (current customers) A 4.3 ROAS means nothing unless you know this: - New: 2.4 ROAS - Engaged: 6.2 ROAS - Existing: 12.1 ROAS An $80 CAC is misleading. The real story: - New: $140 CAC - Engaged: $56 CAC - Existing: $28 CAC To improve, do this: - Review the funnel. - Compare to benchmarks. - Fix the weakest link. TLDR: ❌ Meta’s default reporting is garbage. ✅ Better reporting = better decisions 👊

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After working with $3.5B ARR brands, here's the truth: Noobs and experts tackle CRO very differently. Here are some key contrasts: 1. Beginner: "Let's change the button color to boost conversions." Expert: "What user behavior data supports this change?" 2. Beginner: "More pop-ups will capture more leads." Expert: "How can we add value without disrupting the user experience?" 3. Beginner: "Our conversion rate is low. We need a complete redesign." Expert: "Let's analyze the data to identify specific pain points first." 4. Beginner: "Mobile optimization isn't crucial for our B2B audience." Expert: "Let's ensure a seamless experience across all devices and contexts." 5. Beginner: "Our test didn't work. CRO doesn't work for our business." Expert: "What insights can we gain from this test to inform our next hypothesis?" The key takeaway? Expert CRO is about asking the right questions, not jumping to quick fixes. It's about: - Testing methodically - Understanding user behavior - Continuously improving based on data Where do you fall on this spectrum? Are you taking a beginner or expert approach to CRO? Share your thoughts below! 👇 - - - Want more expert CRO insights? I've compiled our top 446-point CRO checklist to increase conversion fast based on 2,500 A/B tests 1. Like and repost this post 2. Comment "CRO TIPS" and I'll DM you the full list. (Follow me first)

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"Funnels are dead" "Everything is dark social, so attribution is pointless" "The buyer's journey isn't linear so who cares about buying stage data" "Marketing data is all just made up" I see this stuff on Linkedin all the time. And I get it. Marketers struggle with how hard it is to get visibility into what is working and not working. It's hard. And getting harder by the day. But all this criticism is based on a fundamental misunderstanding. "All models are wrong, but some are useful" - George Box. Yes, all the attribution models are wrong. Trying to understand why someone bought your product is very complicated and even asking them is riddled with bias (still worth asking though). But "models" are not meant to be 100% reality. They are a representation of reality to help you understand something complex. A model airplane can't actually fly you to Europe. But it sure could help someone who has never seen a plane before understand what a plane is and how it works. It's the same for marketing models. If you dig in, they are wrong in a load of ways. But when done right, they simplify reality into a more digestible format to help make important decisions. The "when done right" part is very important, though. Most companies struggle with poor data and misunderstand the questions different models can answer. But that does not mean trying is a waste of time. So when you hear the next LinkedIn "expert" who probably hasn't built a report in their life, try to tell you your reporting efforts are a waste of time, ignore them and keep at it. #gtmoperations #marketingoperations #revenueoperations  

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