Scale content and intelligence without scaling headcount.
SEO audits, social content, trend analysis, email sequences, blog articles — theywork365 marketing agents produce and research at a pace no team can match, inside your M365 environment.
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10x
Content production capacity
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Weekly
Market intelligence briefings
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€0
Upfront to deploy
Marketing teams are expected to produce more content, cover more channels, and deliver better insights — with the same headcount. theywork365 marketing agents take over the production and research workload, letting your team focus on strategy, creative direction, and campaign management.
What Marketing agents can do for you.
Each agent is built specifically for your processes and data. Pricing is per action — you pay only for the value delivered.
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Audits your website pages, identifies keyword gaps and technical SEO issues, generates optimized content briefs for each target keyword, and monitors ranking changes week over week.
Before
SEO audits happen quarterly, done by an agency at high cost. Optimization recommendations sit in a report nobody has time to act on.
After
Pages are audited continuously. The team receives prioritized, actionable briefs every week. SEO becomes an ongoing operation, not a quarterly project.
How the agent works — step by step
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Agent crawls target pages and extracts on-page SEO signals
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Identifies keyword gaps: terms competitors rank for that you don't
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Flags technical issues: missing meta, slow pages, broken links
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Generates content brief for each gap: target keyword, intent, outline
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Monitors ranking changes weekly and sends a delta report
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Posts weekly SEO digest to Marketing channel in Teams
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Generates platform-specific posts for LinkedIn, Instagram, and X from your content strategy, blog articles, and campaign briefs. Adapts tone and format per platform and schedules for review.
Before
The social team spends hours adapting a single piece of content for multiple platforms. Posting frequency drops when the team is busy with campaigns.
After
Every blog post, event, and campaign generates a ready-to-publish set of social posts automatically. The team reviews and approves in minutes.
How the agent works — step by step
- 1
New content published to SharePoint or blog triggers the agent
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Agent reads the content and extracts key messages
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Generates 3 platform variants: LinkedIn (professional), Instagram (visual hook), X (punchy)
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Applies brand voice guidelines stored in SharePoint
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Posts drafts to Marketing approval channel in Teams
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Logs approved posts to the content calendar
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Monitors market signals, competitor activity, search trends, and industry news. Delivers a structured weekly briefing to the marketing and leadership teams with actionable implications.
Before
Market monitoring is ad hoc — someone checks competitor websites occasionally. Emerging trends are spotted weeks late. The team reacts instead of anticipating.
After
The team receives a structured market briefing every Monday. Trend-led campaign ideas emerge earlier. Leadership is better informed for strategic decisions.
How the agent works — step by step
- 1
Agent monitors defined sources: competitor sites, industry publications, search trends
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Extracts signals: new product launches, content themes, keyword movements
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Identifies emerging trends and categorizes by relevance and urgency
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Drafts structured briefing: this week's signals, implications, recommended actions
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Posts briefing to Marketing Leadership channel every Monday
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Archives all briefings in SharePoint for longitudinal trend analysis
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Writes personalized email sequences for campaigns, nurture flows, and event promotions — based on audience segment, product positioning, and brand voice. Delivers HTML-ready drafts for review.
Before
Writing a 5-email nurture sequence takes a copywriter 2–3 days. Campaigns are delayed or emails are rushed and off-brand.
After
The agent produces a complete sequence in hours. The copywriter focuses on refinement and strategy, not drafting from scratch.
How the agent works — step by step
- 1
Marketer provides brief: audience segment, goal, product, tone
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Agent reads brand voice guidelines and past top-performing emails
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Drafts the full sequence: subject lines, preview text, body, CTA
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Adapts personalization variables for each segment
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Posts drafts to Marketing channel for copywriter review
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Delivers final HTML-formatted output ready for ESP import
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Produces long-form, SEO-optimized blog articles from a brief. Researches the topic, structures the argument, writes the draft, and formats it for your CMS — ready for editorial review.
Before
One blog article takes a writer 4–8 hours. The content calendar is always behind. SEO opportunities are missed because there aren't enough articles.
After
The team produces 3–5x more articles per month. Writers focus on editing, positioning, and subject matter expertise rather than drafting.
How the agent works — step by step
- 1
Content manager provides brief: topic, target keyword, audience, angle
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Agent researches the topic using approved sources and internal knowledge
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Creates outline and gets implicit approval via structure in the draft
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Writes full article: introduction, body sections, conclusion, meta description
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Formats with headers, bullet points, and internal link suggestions
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Posts draft to Content channel in Teams for editorial review
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Dynamically creates and updates audience segments based on behavioral data, demographics, engagement history, and purchase intent — enabling precise targeting for campaigns and content.
Before
Audience segments are built manually from static lists and updated quarterly at best. Campaigns target broad groups with low relevance scores and poor conversion rates.
After
Segments are dynamic, data-driven, and updated continuously. Each campaign targets a precise, current audience. Conversion rates improve and ad spend efficiency increases.
How the agent works — step by step
- 1
Agent connects to CRM, marketing automation, and analytics platforms
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Reads behavioral signals: page views, content engagement, email responses, purchase history
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Applies clustering to identify natural audience groupings with shared characteristics
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Labels segments with descriptive profiles and estimated size
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Publishes segments to marketing automation platform for immediate campaign use
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Monitors segment evolution and alerts when significant audience shifts occur
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Monitors paid media campaigns in real time and recommends budget reallocation, bid adjustments, and targeting refinements to maximize ROI — replacing hours of manual campaign management.
Before
Paid media campaigns are managed manually. Budget allocation decisions are made weekly based on delayed data. Ad spend is wasted on underperforming audiences and placements.
After
Campaigns are monitored continuously. Budget shifts to what's working in real time. The team gets recommendations they can act on in minutes, not days. ROAS improves.
How the agent works — step by step
- 1
Agent connects to paid media platforms: Google Ads, Meta, LinkedIn
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Monitors campaign performance in real time: CTR, CPC, ROAS, conversion rate per audience
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Identifies underperforming ad sets and high-performing opportunities to scale
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Generates specific recommendations: budget shifts, bid adjustments, audience exclusions
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Posts daily optimization brief to Marketing channel with prioritized actions
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Tracks the impact of applied changes over the following 48 hours
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Designs, runs, and analyzes A/B tests on creative, messaging, subject lines, and landing pages — automatically identifying winning variants and recommending when to scale the winner.
Before
A/B testing happens occasionally when someone has time to set it up. Tests run too long or too short. Results are interpreted inconsistently. Learning isn't captured systematically.
After
A/B testing is continuous and systematic. Every major asset has a test running. Winners are identified at statistical significance and scaled automatically. The team learns faster.
How the agent works — step by step
- 1
Marketer defines the element to test and hypotheses via a simple brief
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Agent designs the test: control, variant, audience split, success metric, and minimum sample size
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Monitors the test in real time for statistical significance and anomalies
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Alerts when a variant reaches significance thresholds or when the test should be stopped
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Generates a structured results report: winner, lift, confidence level, recommended action
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Archives all test results in a learning repository for future reference
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Analyzes audience behavior, recent interactions, and campaign history to recommend the most effective next marketing action for each segment — ensuring every customer receives the right message at the right moment.
Before
Marketing campaigns follow a fixed editorial calendar regardless of audience behavior. Customers receive irrelevant messages at the wrong moment. Engagement and conversion rates suffer.
After
Every campaign decision is informed by what each audience segment needs to hear next, based on their actual behavior. Engagement rates improve and the customer journey feels coherent.
How the agent works — step by step
- 1
Agent reads full interaction history for each audience segment: emails, ads, web behavior
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Identifies where each segment is in the customer journey and what signals indicate readiness
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Evaluates past campaign performance by segment and message type
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Recommends the next best action: email campaign, retargeting ad, event invite, or content piece
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Generates a prioritized campaign brief with audience, message direction, channel, and timing
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Posts weekly recommendations to Marketing channel for team review and activation
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Maps and analyzes the full customer journey across touchpoints to identify drop-off points, high-friction moments, and conversion opportunities — giving the marketing team actionable data to optimize the funnel.
Before
The customer journey is a black box. The team can see traffic and conversion numbers but can't see where and why people drop off. Optimization is based on guesswork.
After
Every stage of the customer journey is visible and measurable. Drop-off points are identified with context. The team knows exactly where to invest to improve conversion.
How the agent works — step by step
- 1
Agent collects data across all touchpoints: website, email, ads, events, CRM
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Reconstructs individual customer journeys from first touch to conversion or drop-off
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Aggregates journey data to identify common paths, drop-off stages, and conversion accelerators
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Flags high-friction touchpoints where significant audience volume is lost
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Generates a monthly journey analysis report with prioritized optimization recommendations
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Alerts when a previously healthy journey stage shows a sudden increase in drop-off
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Adapts website content, email messages, and ad creative in real time based on visitor behavior, segment membership, and contextual signals — making every interaction feel individually relevant.
Before
Every visitor sees the same website and receives the same emails regardless of their profile or behavior. Content feels generic. Conversion rates are below potential.
After
Returning visitors see content tailored to their industry, role, and past behavior. Email content adapts to engagement history. Conversion rates improve across all channels.
How the agent works — step by step
- 1
Agent reads real-time visitor signals: traffic source, browsing behavior, CRM membership
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Identifies the visitor's segment and journey stage from behavioral and demographic data
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Selects the most relevant content block, CTA, or message variant for each visitor
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Applies personalization dynamically to website components and email content
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Logs personalization decisions for attribution and optimization analysis
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Reports weekly on personalization performance: lift in engagement and conversion by segment
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Forecasts the expected ROI of planned marketing campaigns before launch, using historical performance data, audience characteristics, and market conditions — enabling smarter budget allocation decisions.
Before
Campaign budgets are allocated based on last year's spend or executive intuition. ROI is only measured after the campaign ends — too late to change course.
After
Before any campaign launches, the team has a data-backed ROI forecast to evaluate. Budget goes where it's expected to return the most. Post-campaign variance is reduced.
How the agent works — step by step
- 1
Marketer submits a campaign plan: audience, channel, budget, and objective
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Agent retrieves historical performance data for similar campaigns
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Applies predictive model: expected reach, engagement rate, conversion probability, and cost per outcome
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Adjusts forecast for current market conditions and seasonal factors
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Generates ROI forecast report: expected leads, pipeline contribution, estimated revenue return
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Compares forecast to post-campaign actuals to improve future prediction accuracy
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Continuously monitors campaign performance, market signals, and competitive activity to surface real-time insights, emerging trends, and anomalies — keeping the marketing team ahead of what's happening.
Before
Marketing reviews happen weekly at best. Emerging trends or performance drops are spotted days after they start. The team is always reacting rather than anticipating.
After
The team receives continuous insight on what's working, what's changing, and what competitors are doing. Trend-led decisions happen early, when they still have impact.
How the agent works — step by step
- 1
Agent monitors marketing performance dashboards, competitor activity, and market sources daily
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Identifies performance anomalies: sudden drops or spikes in key metrics
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Tracks emerging content themes, keyword trends, and competitive positioning shifts
- 4
Correlates anomalies with external events: competitor launches, market news, seasonal factors
- 5
Delivers a daily highlight for critical alerts and a weekly structured trend briefing
- 6
Posts all insights to Marketing channel with recommended responses
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