Applied AI for Marketing
Give us the marketing workflow.
We put AI to work on it.
Signals are not the problem — acting on them at account level is. Next Quarter reads market and account movement, decides which segment it belongs to, and produces the play, the message and the routing that follows from it.
Manufacturing · Cloud consolidation segment
Signal cluster · 34 accounts in motion
Consolidation mandates named in 9 recent earnings calls
Research spike on migration and cost-per-workload
14 target accounts registered for the same summit
- 1Run the consolidation economics play across the 34-account cluster.
- 2Lead persona: CIO. Secondary: VP Operations, with an ops-cost proof point.
- 3Sequence the summit registrants first — highest intent, shortest path to a meeting.
Human review
Campaign owner reviews the play
Activated
Content variants briefed and target list routed to sales
Live loop: an account signal becomes an approved play with content and routing in place.
3x
more qualified meetings from the same target account list
Comparison of meetings booked from prioritised segments versus prior list-based campaigns.
60 days
to measurable adoption inside existing campaign workflows
Typical elapsed time from kickoff to sustained weekly use in existing marketing operations.
18%
average lift in qualified pipeline coverage on prioritised accounts
Median change over the two quarters after rollout, aggregated across enterprise deployments.
The gap
Marketing sees the signal. The play still gets built by hand.
Intent data, event lists and account scores all arrive. Translating them into a specific message for a specific committee is still weeks of manual work per campaign.
How it works today
- Signals land in one tool and campaigns are built in another, weeks later.
- Segments are static lists, refreshed when someone remembers to refresh them.
- Content is written for a persona in the abstract, not for the account's actual situation.
- Follow-up after events depends on whoever has capacity that week.
With applied AI on the workflow
- Signals are clustered into segments continuously, with the reason attached.
- Each segment arrives with a recommended play and the evidence behind it.
- Message and content variants are drafted against the account's real situation.
- Routing to sales happens with context, so follow-up is not a cold hand-off.
Workflows we take on
The marketing workflows we take on
Each one follows the same grammar: a signal arrives, context is applied, an agent reasons, a business output is produced, and a person decides what happens next.
Signal to segment
Turn scattered signals into segments worth acting on
Signal
Intent research, earnings language, hiring, funding and event registrations.
Context applied
ICP definition, existing pipeline, historical response and account ownership.
Agent reasoning
The agent clusters accounts by shared situation rather than by firmographic bucket.
Business output
A named segment with its size, its trigger and the accounts already in pipeline.
Marketing confirms the segment is real and worth budget before anything is built.
Play and message selection
Pick the play the evidence supports
Signal
A confirmed segment and its trigger.
Context applied
Past campaign performance, competitive positioning and product proof points.
Agent reasoning
The agent matches the trigger to the play and persona with the strongest response history.
Business output
A play brief: primary persona, angle, proof points and the sequence to run.
The campaign owner approves or replaces the play — the recommendation is a starting point.
Account-based content
Draft to the account's situation, not the persona in the abstract
Signal
An approved play and its target account list.
Context applied
Account initiatives, stakeholder language, current usage and prior touchpoints.
Agent reasoning
The agent adapts the approved narrative to each account's stated priorities.
Business output
Content variants and outreach drafts with the account-specific reasoning shown.
Brand and campaign owners review and edit every asset before it goes anywhere.
Event and field follow-up
Convert attendance into pipeline while it is warm
Signal
Registrations, attendance, session interest and on-site conversations.
Context applied
Account ownership, open opportunities and pre-event engagement.
Agent reasoning
The agent ranks attendees by real opportunity potential, not badge scan volume.
Business output
A prioritised follow-up list with the reason and suggested opener per account.
Field marketing and sales agree the split before follow-up is routed.
Pipeline attribution and feedback
Learn which plays actually produced revenue
Signal
Meeting, opportunity and closed-won outcomes on touched accounts.
Context applied
Play history, segment membership and sales activity after routing.
Agent reasoning
The agent ties outcomes back to the play that preceded them.
Business output
A play-level view of what produced qualified pipeline and what did not.
Marketing leadership decides what gets retired, repeated or expanded.
Why it works
Context is the reason the output is usable
Generic AI summarises. Applied AI reasons against the specific reality of your accounts, your positioning and your numbers.
Signals in context
Market movement is read against your accounts, not scored in isolation.
Your positioning
Agents work from your approved narrative, proof points and brand rules.
Segments that stay live
Membership updates as accounts enter and leave the situation that defined them.
Routed to the owner
Plays and lists land in the CRM and campaign tools your team already runs.
Human control
Nothing reaches a customer without a marketer approving it
Agents draft, cluster and prioritise. People own the narrative, the brand and the decision to spend.
Every recommendation carries its sources, so the owner can judge it instead of trusting it.
Nothing reaches a customer, a CRM record or a board pack without a named human approving it.
Agents operate inside your permission model — people see what their role already allows.
Outcomes feed back in, so the workflow gets sharper without anyone rewriting a prompt.
Where it is used
Where marketing teams put it to work
Every engagement starts with one workflow. These are the ones teams bring us most often.
ABM programme design
Tiers are built from accounts in motion rather than from last year's list.
Demand routing
Inbound interest reaches the right owner with the account context attached.
Event monetisation
Pre-event targeting and post-event follow-up run as one coordinated motion.
Competitive campaigns
Displacement narratives are built from observed dissatisfaction signals.
Expansion marketing
Installed-base whitespace becomes a campaign with a named internal sponsor.
Sales and marketing alignment
Both teams work the same prioritised accounts from the same evidence.
How we engage
Give us the workflow. We put AI to work on it.
This is a service-led engagement, not a licence and a login. We do the mapping, the building and the review with your team.
Workflow session
We sit with your team and map one marketing workflow end to end — the trigger, the judgement calls and the output that matters.
Context connection
We connect the systems that already hold the truth: CRM, documents, meeting history, product and finance data.
Agent build and review
We build the agents against your definitions, then review the reasoning and outputs with the people who own the work.
Run and expand
The workflow runs in your existing tools. Once it holds, we take on the next one.
The rest of the family
Applied AI across the revenue organisation
The same context layer, pointed at a different function's workflows.
Applied AI for Sales
Turn account movement into a specific next move for the owner, inside the CRM.
ExploreApplied AI for Finance
Explain variance, reconcile the forecast and act on what the numbers are telling you.
ExploreThe products
KAM Q, Sales Q, ABM Q, Events Q and Fin Q — the software behind the workflows.
ExploreGive us the workflow
Bring us one marketing workflow that is stuck in manual translation
We map it with your team, build the agents against your positioning, and run it inside your existing stack.