Most GTM teams can detect when an account is in-market. After completing Use Case 2,
you can identify which accounts are showing buying activity and what they’re researching.
What most teams can’t consistently answer: What should we say to them, and are we all
saying the same thing?
Without a shared answer to that question, signals get interpreted differently by every team
that touches them. The result is a fragmented buyer experience where an account might
see a brand awareness ad, receive a generic SDR sequence, and get called by a rep who
has a different take on what the buying group needs.
This use case closes that gap. It takes the keyword strategy and intent signals you built in
Use Case 2 and translates them into a shared messaging framework your entire GTM
organization executes from, based on a shared understanding of what each buying group is
trying to solve.
The central concept for this use case is the Inferred Buyer Need, a signal-derived
statement of what a buying group is likely working on, based on their research activity. It
translates clusters of signals into buyer context.
Until signals are consistently translated into shared messaging, every execution use case
in Transform operates below its potential. Teams that skip this step often find their
Transform use cases stalling between Walk and Run. The signal capture technology is
working, but because the resulting messaging it isn’t coordinated.
The maturity progression breaks down like this:
Crawl
Your keyword strategy has been reorganized into thematic clusters, defined by what a
buyer is trying to solve:
- Marketing, Sales, and Ops have aligned on what each cluster means and how it
should inform their work. - This alignment happened in a working session where assumptions were reviewed,
challenged, and validated. - Sales, especially, have provided feedback based on their conversations with
prospects, and explicitly bought into how keyword clusters are mapped to buyer
needs. - You’ve documented the framework and assigned a single owner responsible for
maintaining it as signal patterns evolve.
At Crawl, you’re also conducting an honest audit of your existing messaging. Look at what
Marketing is currently running in campaigns, what Sales is using in sequences, and what’s
on your website. Map it against the buyer problems you’ve now defined. In most
organizations, you’ll find that existing messaging is organized around product capabilities,
company personas, or campaign themes — not buyer problems. That gap is what you’re
building toward closing.
Walk
You’ve moved from defining the messaging framework to using it in the market:
- At least one GTM use case — advertising, SDR outreach, or inbound — is running
with messaging built around buyer problems rather than buying stages alone. - For each buyer problem, the framework specifies what to say at each phase of the
buyer’s research journey. - Segments in your platform have been rebuilt. The filter logic is ICP fit + keyword
group cluster activity, not just ICP fit + predictive stage. - You’re measuring engagement at the account level and tracking early pipeline
signals to ensure problem-based messaging is improving results before you scale it
across the rest of your GTM motion. - Sales reps know which buyer problem a given account has been mapped to, and
have messaging guidance specific to that problem rather than a generic talk track.
If reps are rewriting the message from scratch every time they engage a priority account,
Walk isn’t complete.
Run
Aligned messaging is no longer a framework that lives in a document — it’s embedded in
how your GTM system operates.
- Segments, orchestration workflows, advertising campaigns, sales sequences, and
inbound experiences all reflect buyer problems consistently. - The system connects signals to buyer problems to messaging to activation
automatically, so that when an account’s signal pattern shifts, messaging shifts. - Messaging variants exist for the different roles within a buying group — because the
CFO evaluating a purchase has different Inferred Buyer Needs than the VP of
Operations or the technical evaluator, even at the same account. - Content exists to support buyers at each research phase for each buyer problem.
- The framework is governed and continuously refined.
Watch out for these common traps
Routing this through brand or comms without involving Sales and Ops is the most common
failure mode. Teams that treat this as a messaging or positioning exercise end up with
something that reads well in a deck but doesn’t hold up in the field.
Skipping the validation step with sales produces a framework grounded in marketing
assumptions rather than buyer reality. Before activating the framework in any use case,
reps need to pressure-test every Inferred Buyer Need against what they actually hear in
discovery.
Keeping keyword clusters structured the way they were organized for signal detection
misses the point of this use case. Keyword groups built for Use Case 2 are often organized
around product features, content topics, or broad categories. For this use case, they need
to be reorganized around specific challenges buyers are trying to solve. The cluster name
should communicate buyer context so clearly that a rep seeing it in their sales intelligence
tool understands the context at a glance.
Analysis paralysis. Some teams spend months trying to build a comprehensive framework
that covers every buyer problem before testing anything in the market. That’s the wrong
sequence. Start with one or two high-signal clusters where you have strong account
activity and clear messaging hypotheses. Activate, measure, and learn.
Letting the framework go stale. Signal patterns shift as markets evolve, competitors
change positioning, and buyers’ priorities move. The Inferred Buyer Needs you define today
will need to be refreshed as performance data reveals which narratives are resonating and
which aren’t.
Measuring only activity metrics rather than account progression. Email open rates and ad
click-through rates can improve even when messaging isn’t actually better. Subject line
optimization, send timing, and audience targeting all affect those numbers independently
of message relevance. The metrics that actually tell you whether aligned messaging is
working are account-level progression rates, 6QA conversion from problem-based
segments, opportunity creation and win rates from aligned versus non-aligned motions.
What you’ll need to make this work
- A completed keyword strategy from Use Case 2, with keywords reorganized into
thematic clusters built around buyer problems - A cross-functional alignment session that brings Marketing, Sales, and Ops
together to validate the Inferred Buyer Need for each cluster - A documented messaging framework that maps each buyer problem to messaging
guidance across early, mid, and late research phases - Platform segments rebuilt with a buyer problem dimension
- Content coverage across research phases for each buyer problem
- A single named owner for the framework, with a defined review cadence and a clear
process for updating Inferred Buyer Needs - Sales enablement resources that make the framework usable day-to-day
Measuring success
At Crawl, measurement is primarily about completeness and alignment rather than
performance. The framework either exists or it doesn’t. You either have agreement on
definitions or you don’t.
At Walk, shift to engagement and early pipeline metrics, but measure them at the account
level rather than the individual level. Track how accounts engaged through problem-based
segments progress compared to accounts in stage-only segments.
At Run, connect messaging performance directly to pipeline and revenue outcomes. The
metrics that matter most are opportunity creation rates from messaging-aligned segments
versus non-aligned segments, and average deal value for aligned versus non-aligned
opportunities. Deal value is a particularly useful comparison because problem-specific
messaging tends to attract accounts with clearer, more urgent buying intent, which often
correlates with deal quality and size.
The temptation is to treat this use case as a shared responsibility across Marketing, Sales,
and Ops given how cross-functional it is. Resist that. Diffused ownership produces the
same outcome here as it does in every other use case: a framework that everyone
contributed to and nobody maintains. One owner with clear accountability, supported by
active participation from the other functions, is the structure that works
