Milena Traikovich has dedicated her career to dismantling the silos that traditionally separate marketing engines from sales results. As a leading expert in demand generation and account-based marketing, she has navigated the complexities of enterprise-scale alignment at some of the most data-driven organizations in the world. Milena understands that in 2026, the distance between a marketing campaign and a closed deal must be measured in shared steps rather than handoffs. By blending rigorous analytics with a deep empathy for the daily grind of a sales representative, she helps businesses transform “alignment” from a boardroom buzzword into an operational discipline. Today, she shares insights on how to bridge the perception gap between executives and ground-level teams, the evolution of signal-based selling, and why the most successful teams treat their partnership like a continuous relay race.
The most recent data highlights a staggering disconnect: 82% of C-level executives believe their sales and marketing teams are perfectly in sync, yet 65% of the professionals actually doing the work report a significant lack of alignment. Why does this perception gap persist in 2026, and what does it take to move alignment from a concept to a weekly discipline?
The reason we see this massive chasm between executive optimism and the reality on the ground is that leadership often views alignment as a strategic destination—a checkbox marked after a successful kickoff meeting or the signing of a shared SLA. However, for the people in the trenches, alignment is an exhausting, high-friction process of resolving conflicting data points and competing priorities every single day. When 65% of your workforce feels out of sync, it is usually because the “alignment” hasn’t moved past a shared spreadsheet that everyone ignores by the third week of the quarter. To bridge this, we have to stop treating alignment like a one-time event and start treating it as a rigorous operating discipline. This means moving away from quarterly check-ins and toward weekly synchronization where every account movement is scrutinized and every campaign is adjusted in real-time. It requires a level of transparency where marketing doesn’t just show “results” to executives, but proves its utility to the reps who are trying to hit their numbers. True alignment is only achieved when the sales team feels that marketing is actually in the foxhole with them, rather than just lobbing leads over a wall.
A primary source of failure in many organizations is the mismatch between the marketing target list and the accounts sales is actually working. How can teams effectively reconcile these lists within the first two weeks to ensure campaigns are launching against the right targets?
Many marketing leaders walk into their roles assuming the CRM is the ultimate source of truth, only to find out months later that their expensive campaigns have been targeting accounts the sales team hasn’t touched in a year. To prevent this, you have to perform a brutal, line-by-line reconciliation within the first fourteen days of any new initiative. You sit down with sales leadership—not just their lieutenants—and pull the accounts they are actively pursuing, then map them directly against your marketing list to identify every single discrepancy. It isn’t enough to just send a file back and forth; you need to physically or virtually sit in a room and resolve the “why” behind the differences. This is also the time to formally document the Ideal Customer Profile (ICP) and, more importantly, specify exactly who owns the authority to change that list when the market shifts. By setting specific re-alignment triggers, such as a change in sales leadership or a major pivot in company strategy, you ensure that the list remains a living document rather than a stagnant artifact. If you can’t deliver something useful in that first interaction by demonstrating you understand their patch, you have to step back and sharpen your value proposition before you ever ask for a rep’s time again.
You’ve advocated for replacing the traditional “handoff” with a “relay” model, particularly in ABM. How does this change the way marketing prepares an opportunity before it ever reaches a sales representative’s desk?
The traditional MQL handoff is where many great opportunities go to die because marketing feels its job is done once a lead hits a certain score, while sales feels like they’ve been handed a cold list with no context. In a relay model, the baton is never truly dropped; it’s passed back and forth like a soccer match where marketing and sales are constantly moving the ball toward the net together. The core principle here is to take every action as far as marketing possibly can—doing the deep research on the buying committee, engaging executives through tailored programs, and prepping the ground with air cover—until there is a fully-formed opportunity sitting on the rep’s desk. Instead of just “passing a lead,” marketing should deliver a comprehensive package that details exactly what we’ve seen in the account, what it tells us about their current pain points, and a recommended next step for the AE. We shouldn’t just ask them to call someone; we should provide the specific executive contact, the suggested message, and a reference to the programs that have already warmed them up. You know this is working when marketing is mentioned by name in the win announcements, and the sales team admits they couldn’t have closed the deal without that preliminary work.
As intent data becomes a commodity that everyone can buy, how do you differentiate between “fit signals” and “action signals” to ensure sales is acting on the most relevant information?
In today’s market, handing a rep a data dump of raw third-party intent and asking them to find the “gold” is a recipe for frustration and ignored emails. We have to separate “fit signals,” which tell us which accounts belong in our ABM tiers and how much we should spend on them, from “action signals,” which tell us what to do right now. Action signals are those publicly observable, person-level events—like an executive taking a new role, a project announcement, or a specific initiative mentioned in an earnings call—that provide a legitimate reason for a rep to reach out. Especially in large enterprise accounts where a rep might only hold 35 accounts for the entire year, you can’t tell them there’s “no intent” just because the company isn’t searching for keywords. You have to aggregate third-party data, first-party website activity, and campaign performance into a single workspace that provides a clear recommendation rather than a raw feed. When you layer intent with white space analysis and competitive contract renewal dates, the data stops being noise and starts being a strategic roadmap. One signal is just a data point, but multiple signals pointing at the same person at the same time is what earns a busy rep’s attention.
Tiering is often a contentious topic because it can feel like marketing is rationing its support rather than offering help. How can organizations reframe their tiering strategies to ensure sales sees them as an investment in their success?
The mistake most marketers make is trying to explain the mechanics of “1:few” or “1:many” to a rep who doesn’t care about tiers—they only care about their accounts. To get past the blank stares, you have to stop selling the tier and start selling the support. I always suggest starting with the “must-wins” by asking the rep which two or three accounts are essential for them to hit their quota this year. Once they identify those, marketing commits to going all-in with bespoke treatments that go far beyond standard demand programs. We should position the “1:many” programs as the foundational base layer that every account receives, which usually already doubles the standard marketing investment, rather than treating it like a “lower” tier. Decisions about who gets the highest level of support should be handled at the leadership and revenue operations level so the individual ABM marketer isn’t the “bad guy” telling a rep they didn’t make the cut. By using a rubric tied to revenue potential and leaving room for “big bets” on dream logos, you create a system that feels fair and strategically sound.
Sales representatives live in their inboxes, while marketing often lives in internal collaboration tools like Slack or Teams. How do we bridge this technological divide to ensure enablement actually reaches the people who need it?
We spend an incredible amount of time obsessing over external buyer personas, but we rarely apply that same level of rigor to our internal customer: the salesperson. If we want our enablement to work, we have to stop asking reps to log into new dashboards or check another tool and instead meet them exactly where they spend their day, which is usually their email inbox. Email is searchable, forwardable, and fits their workflow perfectly, so our account briefs need to be delivered there in a format they can actually use. These briefs should go much broader than just marketing activity; they need to include the partner and alliance footprint, who we already know in the account, recent lead activity, and the specific white-space opportunities we’ve identified. A rep wants ABM to be their window into the entire marketing organization, so we need to know enough about every channel—from field events to growth campaigns—to answer their questions on the spot. We are seeing AI agents speed this up by assembling these details from the CRM, but it’s critical that a human always checks that output to ensure the context is correct before it ever reaches the sales team.
With the rapid integration of AI into marketing workflows, there is a risk of creating “sameness” in our outreach. How can teams use AI to handle the unglamorous work while reinvesting the saved time into highly personalized, one-to-one human connections?
The pressure to adopt AI is everywhere, but the real winners are pointing it at the tedious, operational tasks that used to eat up hours of the team’s day. At organizations like Unisys and Datadog, the focus is on workflows: building custom dashboards in minutes rather than waiting weeks for an analytics ticket, or moving data between systems so campaigns can launch in days instead of months. When you automate the “clicking,” you free up the team for “creating.” For example, Snowflake uses an AI tool to analyze sales call recordings to find personal details—like a prospect mentioning a holiday barbecue—and then suggests a relevant gift, like a high-end grill set. This removes the friction of having to ask a rep for “prospect interests” while keeping the final human touch in place. However, we have to be careful, because if everyone can launch an ABM campaign in two weeks, the market gets flooded with generic content. The goal is to use those saved hours to go deeper into 1:1 work, finding the specific angles—like a project the CEO mentioned in a recent interview—that make our message stand out. We should be asking our vendors if our AI agents can actually act on their data, rather than just querying it, to ensure we are moving toward real-time responsiveness.
What is your forecast for the future of the CMO and CRO relationship as organizations move toward this model of shared goals and operational symmetry?
I believe we are moving toward a reality where the distinction between “marketing goals” and “sales goals” will completely vanish, replaced by a single, unified revenue number that both the CMO and CRO own equally. In the next few years, the most successful organizations will treat their go-to-market strategy like a high-performance product, where “product-market fit” is measured by how often sales comes to marketing asking for help, rather than marketing having to “sell” its value internally. We will see a shift where marketing is no longer a support function, but a co-architect of the sales cycle, providing the strategic intelligence and air cover that makes every deal faster and more predictable. As AI continues to commoditize basic outreach, the value of the CMO-CRO partnership will lie in their ability to orchestrate complex, human-centric experiences that a machine simply cannot replicate. The “seat at the table” will no longer be a debate because the data will prove that the most significant opportunities were surfaced, nurtured, and closed through a seamless, joint effort. My advice for readers is to stop looking for the “perfect” tool and start looking for the “perfect” alignment trigger—find that one shared metric that makes both teams feel the pain of a loss and the thrill of a win equally, and everything else will follow.
