Conversion Rate Optimization in ABM

I analyzed 12 months of ABM campaigns that actually worked. Here's the data: Most Account-Based Marketing fails before it starts. After analyzing 12 months of successful ABM campaigns (and plenty of failures), I've identified the patterns that consistently drive pipeline. Here's what the data shows: 1. Timing matters just as much as content Accounts that received 3+ touches within 48 hours of showing buying intent converted 4x better than those that received the same content a week later. 2. The magic number is 6.2 (for this brand at least) The average closed-won deal had 6.2 stakeholders involved. Yet most ABM campaigns only target 1-2 personas per account. Expand your reach. 3. The "champion experience" is everything The accounts where we delivered a memorable experience to a single champion (personalized video, custom research, direct exec outreach) had 3x higher conversion rates. 4. Sales and marketing misalignment kills ABM Our most successful campaigns had sales activity within 24 hours of marketing touches. When this alignment slipped to 72+ hours, conversion rates dropped by 48%. 5. Personalization at scale actually works But not how most people do it. We tested 4 levels of personalization: - Generic (18% engagement) - Industry-specific (27% engagement) - Company-specific (42% engagement) - Individual + company-specific (63% engagement) 6. Direct mail isn't dead But swag is worthless (or at least it didn’t work for this audience 🤷♀️). Our highest ROI direct mail: Personalized research reports addressing the account's specific challenges. $250 spend → $45K in pipeline (average). 7. The "Double-Down Effect" When an account engages with ANY marketing touch, immediately increasing the frequency and personalization level produces a 3.5x lift in conversion rates. The companies getting ABM right understand it's not a campaign—it's a complete go-to-market strategy. P.S. I'm working on a new episodic ABM show in collaboration with Clay, so stay tuned 🤗

A VP of Demand @ $50M+ ARR company asked me this week: “What's the average Past Champion > Opp conversion rate?' The answer = 9.81%! (Range is between 5-12%. Source: last 12 months, 350+ customers from start-ups to public companies.) 1 out of 10 of your Past Champions (customers, users, closed/lost contacts who recently changed their job) you reach out to become a new opp! I’m not talking Reply Rate, or Meetings. I’m talking Sales Opportunities! There aren't many programs that convert this high (outside of inbound demo requests) Honestly, it should be illegal not to run it. It should also be illegal if you don't run it correctly. At UserGems 💎, at least 2-3 meetings are booked from this program literally every day. Here's how we do it: 1) Job changes: Gem-E (our AI Agent for Outbound) tracks thousands of Past Champion job changes each month, filtered for ICP and Persona 2) Stack additional signals: Gem-E captures other signals daily (New exec hire, CRM data, Gong transcripts, Email exchanges, Funding, Website Visits, News + 100 more) 3) AI emails: Gem-E combines all data for highly contextual & personalized email sequences. Reps focus on calls, replies, and social selling. Example: 'Hi Joe, you might have remembered us from → acknowledge relationship We talked to Jane from Sales last year about using AI to automate outbound, ABM and improving efficiency. She liked what she saw but timing was off. → CRM research of past interactions & closed lost notes + building the buying group Not sure if you knew, [Competitor] shared how they use Gem-E to 2X team's capacity. [Link to story] → External social proof & competitive intel Curious if this is interesting in your new role? PS. Congrats on the new role! Hope you enjoy this small celebratory gift!' 4) Multi-touch sequence: Buyers need time to build a business case, even the warmest ones. We recommend at least 5 touches & multi-channels (email, call, ads) For cold calls: our reps use Gem-E Chrome extension as a cheat sheet to know why they're calling this account & this person. They've booked 3X more meetings from calls now. (check out Sara Angell's posts with a screenshot of this cheat sheet) For ads: we run signal-based contact-level campaigns to surround buyers with similar messaging that our SDRs and AI are sending. 5) Rep Accountability: If reps don’t action these signals within 7 days, Gem-E takes the lead back and adds it to an Autopilot sequence. This guarantees that we act on all hot signals, 100% of the time. ------- If you have > 100 customers, 5-figure ACVs, or a finite TAM, doing this play well requires research and thought. And let's be honest, humans can't execute this 100% consistently. But this is where AI shines. AI is SO much better & faster at: - capturing data & signals - researching CRM + Gong transcripts + email exchanges - combining all that into hyper-personalized emails And it executes 100% consistently. The ROI will pay for itself. Guarantee.

Our demos from ABM spiked nearly 100% month over month (yes, doubled), and of course I got attribution questions 😅 Here are 3 things we changed in March that have spiked the conversions - and it wasn’t our budget: 1) We fixed our audience targeting - the 90% matched audience match rate on LinkedIn turned out to be only…43%. There were a lot of false positives - accounts that had the same (or very similar) company names, and that LinkedIn matched. How we fixed it: uploading all the fields in the matched audience template rather than just required fields, and then downloading the audience once it’s built and cross-referencing it with the original target list - this gave us 87% actual match rates. 2) We added 24,942 new good fit companies to our target audience. Average Deal open rate from one-to-many ABM sits only at 0.58%* I know some people are going to object (that’s not ABM!) but it works for us - increasing audience size not only maximises our conversion chances, but usually makes the CPMs cheaper as our ads enter more auctions and we have more chances to win cheaper clicks. Goes without saying - the accounts still need to be a good fit. 3) We made a big bet on TLAs - and shifted our LinkedIn ads budget allocation per format accordingly. In April so far, we spent +65.3% more on TLAs than in March - going from 41.2% to 52.8% in budget spend (+28.2% increase). Meanwhile - we decreased our single image ad spend by –32.5% - from 46.4% to 31.3%. Previously - we were spending more on image ads than TLAs. Now our TLAs consume 40% more budget than our image ads. And literally most of the deals that were ABM-influenced in April had ABM touchpoint before the deal was opened. You can see below (LinkedIn ads data parsed by ZenaAI from ZenABM - you can use it for free to do this for 37 days btw: https://lnkd.in/dp-Ym6Wj) how overwhelmingly more engagements and clicks did these accounts (only the ones with deals open) have with TLAs compared to other ad formats in the screenshots below. I kept seeing TLAs as the top performing LinkedIn ad format but we’ve honestly never did them proper justitce. So in late March we decided to do it properly: - interview internal stakeholders - collaborate with influencers via Passionfroot - do a Customer Advocacy program (rewarding our customers for posting on LinkedIn about their positive experiences.) Would you guess which type of TLAs had the highest engagement rate? 😉 Customers - 4.71% CTR, 0.84% CTR to Landing Pages Influencers - 4.87% CTR, 0.78% CTR to Landing Pages Internal stakeholders - 6.09%, 0.58% CTR to Landing Pages TL;DR - with the same budget, our campaigns became 2x more effective in driving demos. Don’t judge the book by its cover - it pays off to be data-driven.

We inherited a Google Ads account burning £4K/month with zero attribution. Here's what we found. A B2B technology company came to us, spending £4,000 per month on Google Ads. They had been running the same campaigns for 14 months. When we asked what pipeline those campaigns had generated, the answer was: we don't know. Here is what the audit uncovered: 1. 62% of spend was going to broad match keywords that attracted unqualified traffic 2. Landing pages had no clear call to action for enterprise buyers 3. The same ad copy was shown to every visitor regardless of company size, industry, or buying stage 4. No remarketing sequences for accounts that showed initial interest 5. Zero integration between Google Ads data and their sales pipeline The total spend over 14 months: £56,000. The attributable pipeline from that spend: £0 confirmed. Not because Google Ads does not work for B2B. It does. But only when it is built into a system that targets the right accounts and tracks the right outcomes. The ABM Paid Media Restructure (what we built in 30 days): 1. Replaced broad keywords with intent-based search terms mapped to their target account list 2. Built account-specific landing pages with messaging aligned to each stakeholder's priorities 3. Created remarketing sequences triggered by account engagement signals, not just page visits 4. Integrated Google Ads conversion data directly into CRM pipeline stages 5. Set up weekly pipeline attribution reports so every pound of spend was accountable The lesson is consistent across every account I audit. Paid media in B2B is not a lead generation tool. It is a pipeline acceleration tool. And it only works when it is connected to named accounts, personalised messaging, and closed-loop attribution. If your Google Ads or LinkedIn Ads spend cannot be traced to specific pipeline, you have an attribution problem before you have a performance problem. DM me "PAID" and I will run a 15-minute review of your paid media setup and tell you exactly where the leaks are. --------------------------------------------------------------------------- Who am I I'm Lukas, founder of LDS Digital. What I do I help businesses build steady lead and revenue systems. What LDS Digital does We turn interest into real enquiries and booked calls using account-based marketing and AI automation. Who we help B2B operators who want growth without guesswork. The outcome A clearer pipeline, better lead quality, and more predictable revenue. Why this works This approach works because it focuses on fundamentals, clean execution, and systems that keep performing over time. If this resonates, feel free to DM me.

This LinkedIn ad strategy from last year still drives high-quality leads for 83% of the cost for one of my clients. It's been so successful, my Linkedin rep called me to ask questions. 👀 It's now part of our holistic demand gen playbook. The experiment? Running impactful ABM ads. It's not an earth-shattering concept. But a ton of marketers struggle to make LinkedIn ABM ads work. You’re not alone. Many marketers find themselves: ❌ Targeting the wrong accounts. ❌ Using generic messages that don’t resonate. ❌ Creating audiences that are way too small to make an impact. It doesn’t have to be this way. With this focused ABM approach, my client saw: 🔥 Decreased cost per lead by 83%  🔥 2.5x higher form conversion rate (3.50% vs. 1.41%) 🔥 4% higher lead quality leads Here are 5 tactics (with real examples!) that helped achieve these results: 1. 𝐈𝐝𝐞𝐧𝐭𝐢𝐟𝐲 𝐡𝐢𝐠𝐡-𝐑𝐎𝐈 𝐚𝐜𝐜𝐨𝐮𝐧𝐭𝐬. Focus on accounts with high revenue potential and strategic GTM alignment. Margins need to make sense.  2. 𝐂𝐫𝐞𝐚𝐭𝐞 1:1 𝐜𝐚𝐦𝐩𝐚𝐢𝐠𝐧𝐬. For this motion, make sure each campaign is targeting only one account.  3. 𝐁𝐮𝐢𝐥𝐝 𝐚𝐮𝐝𝐢𝐞𝐧𝐜𝐞𝐬 𝐰𝐢𝐭𝐡 𝐞𝐧𝐨𝐮𝐠𝐡 𝐬𝐢𝐳𝐞. Focus on targeting 300 min contacts matched, but ideally 1,000+ contacts. Using skills OR job titles helped us unlock more scale without sacrificing lead quality.  4. 𝐂𝐫𝐚𝐟𝐭 𝐡𝐢𝐠𝐡𝐥𝐲 𝐫𝐞𝐥𝐞𝐯𝐚𝐧𝐭 𝐦𝐞𝐬𝐬𝐚𝐠𝐢𝐧𝐠. Everyone says this, but actually do it. Go beyond just adding the account logo in your ads. Try using specific messaging, pain points, & stats that are unique to each target account.  5. 𝐋𝐞𝐯𝐞𝐫𝐚𝐠𝐞 𝐬𝐨𝐜𝐢𝐚𝐥 𝐩𝐫𝐨𝐨𝐟. Build trust and credibility fast with each account by using testimonials from similar users. Or, if you're expanding users on an account, use testimonials from existing users! Check the full guide below to help you create ABM campaigns that convert. Have you experimented with ABM ads? What's worked for you?