Client Onboarding Guide
How a DRIVE engagement works
This guide walks you through every phase of the engagement — what to bring, what you'll be asked, exactly what to click, and what the system will produce. Read it before your first session.
Accessing the platform: You'll receive a magic link by email — click it to sign in. No password required. Your workspace is at drive.brittbowman.ai — bookmark this URL so you can return directly between sessions. Your central engagement dashboard is called Hub (Hub is your central engagement dashboard — access it at drive.brittbowman.ai); all deliverables and session history live there.
Your data is private and secure: Your data is stored securely in Supabase and is only accessible to you and your consultant. Files you upload are used only for your engagement and are not used to train AI models.
Engagement tracks — time to budget
Use this table to budget calendar time before the engagement begins. Session lengths vary; total duration depends on complexity and how quickly your team can review and approve each phase.
| Track | Total duration | Sessions |
|---|
| Vector Sprint | ~3–5 weeks | 2–3 sessions |
| Growth Sprint | ~4–8 weeks | 3–5 sessions |
| Foundation + Strategy | ~6–10 weeks | 4–6 sessions |
| Strategy + Execution | ~6–10 weeks | 4–6 sessions |
| Full DRIVE Engagement | ~10–16 weeks | 6–10 sessions |
| Enterprise Governance | ~12–20 weeks | 8–14 sessions |
Why this matters: DRIVE is only as good as the inputs you give it. Vague or missing materials produce generic outputs. Specific, honest materials — even if they're messy — produce outputs that are actually usable.
Org basics — know these before the session
Legal entity name and DBA (if different)The name you operate under publicly — what goes on your website header.
Primary industry / verticale.g. "B2B SaaS — HR Tech", "Professional services — financial advisory", "E-commerce — outdoor goods"
Team size (approx.)Total headcount, not just marketing. The system uses this to calibrate recommendations.
Annual revenue rangeBest estimate is fine: <$500K / $500K–$2M / $2M–$10M / $10M–$50M / $50M+
Your website URLThe system will fetch and analyze it automatically — just have it ready.
Your primary growth challenge right nowPick one: Not enough inbound leads / Referral network is inconsistent / Positioning is unclear or generic / Content exists but doesn't convert / No system — everything is ad hoc / Scaling what's already working / Breaking into a new market or segment
Marketing state — be honest, not aspirational
Annual marketing spend (approximate)All-in: paid ads, agency fees, tools, events, contractor costs. "Unknown" is a valid answer.
Every active marketing channel, and your honest read on eachList them: Google Ads, LinkedIn, email newsletter, SEO, cold outbound, events, referrals, podcast, etc. For each one: Working / Mixed results / Not working.
Which metrics you actually track todayCheck all that apply: CAC, close rate, lead volume, SQLs, NPS, website traffic, email open rate. If you track nothing formally, say so — that's useful data.
Your current CAC (customer acquisition cost)e.g. "$4,200 blended" or "we don't track it" — both are fine.
Close rate on qualified leadse.g. "22%" or "roughly 1 in 5"
Active pipeline value (approx.)Total value of deals currently in your pipeline.
MRR or ARR if subscription-basedMonthly or annual recurring revenue.
What's not working — in your own wordsWrite 2–3 sentences. This becomes the "in their words" section of your baseline report and directly shapes what we prioritize.
Files to gather and bring to session 1
Format note: PDF is preferred. DOCX and TXT also work. Spreadsheets: export as CSV. Slides: PPTX or PDF both accepted. VTT/SRT files work for call transcripts.
| File type | What to bring | Goes to |
|---|
| Taxonomy / CRM export | A CSV or PDF of your CRM field list, contact properties, deal stages, or HubSpot/Salesforce schema. Even a screenshot is useful. This is the most important file if you have it. | Resolve |
| Brand / style guide | Any document that defines how your brand communicates — voice, tone, visual rules, naming conventions. PDF preferred. | Resolve Vector |
| One-pager / pitch deck | The thing you send to prospects. What you currently use to explain what you do. | Resolve Vector |
| Case studies or win stories | Any written customer stories, testimonials, or detailed deal narratives. Even rough internal write-ups. | Intelligence Vector |
| Sales call transcripts | Written call notes or any call recording. Gong, Fireflies, or Otter exports work great — but even a rough typed summary works. Export as .vtt, .txt, or paste directly. | Intelligence |
| Win/loss notes | Any internal notes from deals you've won or lost — what the buyer said, what pushed them over the line, why you lost. | Intelligence |
| Competitor examples | URLs or PDF exports of 2–3 competitor websites, pricing pages, or positioning pages you're watching. | Intelligence |
| Industry research | Any market reports, analyst briefs, or category research you've saved. G2, Gartner, industry association PDFs. | Intelligence |
| Past campaign samples | Email campaigns, LinkedIn ads, paid search copy, or any marketing you've actually sent. Screenshots or PDFs. | Vector Engine |
Don't over-curate. Bring what you actually have, not what you think you should have. A messy CRM export is more useful than nothing. A rough transcript is better than no transcript. The AI will extract signal from imperfect material.
Section 1 — Org Profile
The first screen asks for basic org info. Fill it in completely — it populates the header of every downstream report and sets the context for all AI analysis.
Enter the organization name
Click the Organization name field. Type the name as it appears publicly — this becomes the header of the scoping report. Keep it short: "Clearfield Advisory", not "Clearfield Advisory Group LLC".
Select the primary industry
Click the Primary industry dropdown. Choose the closest match. If you're between categories, pick the one that describes your buyers, not your internal function.
Click your team size
Click one chip: 1–5 6–20 21–50 51–200 200+. This determines whether micro-track adjustments apply (the 1–5 track skips some steps).
Click your revenue range
Click one chip: <$500K $500K–$2M $2M–$10M $10M–$50M $50M+. Best estimate — it's used for calibration only, not shared externally.
Select your primary growth challenge
Click the Primary growth challenge dropdown. Options: Not enough inbound leads / Referral network is inconsistent / Positioning is unclear or generic / Content exists but doesn't convert / No system — everything is ad hoc / Scaling what's already working / Breaking into a new market or segment. Pick the one that's most urgent right now — not the one that feels most strategic.
Click "Capture baseline →" to continue
The footer button becomes active once org name and team size are filled in. Click it to move to the baseline section.
Section 2 — Baseline Snapshot
This section captures where you are right now — before any engagement work begins. It becomes the "before" state in your final report and shapes what we prioritize.
Click your annual marketing spend
Choose one: $0–$25K $25K–$100K $100K–$500K $500K–$2M $2M+ Unknown. Include everything: paid media, agency retainers, tools, events, freelancers. If you genuinely don't know, click Unknown.
Add each active marketing channel
Click + Add channel. Type the channel name (e.g. "Google Ads", "LinkedIn organic", "Email newsletter", "Outbound SDR", "Partner referrals"). After adding, click the status buttons to rate each one: Working Mixed Not working. Add one channel at a time and rate each before adding the next.
Click every metric you actively track
Multi-select: CAC Close rate Lead volume SQLs NPS Website traffic Email open rate Nothing formal. "Nothing formal" is a valid, useful answer.
Fill in key numbers (whatever you know)
Four fields: CAC e.g. "$4,200" · Close rate e.g. "22%" · Pipeline e.g. "$380K" · MRR/ARR e.g. "$85K MRR". Leave blank what you don't track — don't guess.
Write 2–3 sentences: what's not working?
Click the In their words textarea. Write honestly — this becomes a verbatim quote in the final engagement plan. "We're generating leads but close rate is terrible and we don't know why" is far more useful than "we need better marketing."
Click "Begin scoping →" to continue
Moves you into the four readiness questions that determine your engagement track.
Section 3 — Materials Intake
This is where you upload everything you gathered in Phase 0. The system reads it all — taxonomy files go to Resolve, documents and transcripts go to Intelligence, web URLs are fetched automatically.
Answer the taxonomy question
The first thing on this screen: "Do you have an existing CRM taxonomy or field export to upload?" Click one: Yes — upload it No — Resolve will propose one Not sure yet. If you have any CRM export at all — even a screenshot or rough list — choose "Yes."
Upload taxonomy files (if you have them)
Drag files into the Taxonomy files drop zone, or click it to browse. Accepted: PDF CSV XLSX DOCX TXT. What to upload: CRM field export, contact property list, deal stage documentation, naming convention doc, any spreadsheet with field definitions.
Upload all other documents
Drag into the Documents drop zone, or click to browse. Accepted: PDF DOCX TXT VTT PPTX. Upload everything: pitch deck, one-pager, case studies, sales transcripts, win/loss notes, brand guide, old campaign samples, industry research. More is better. There's no upload limit — the AI reads all of it.
Add web URLs
Click the https://… field. Paste a URL and press Enter. The system fetches the page automatically — you'll see a preview appear within a few seconds. Add: your website homepage, a competitor's homepage, a competitor's pricing page, an industry publication you follow. Add one URL at a time and wait for the preview before adding the next.
What happens after you upload: Files are stored and passed to downstream tools automatically. You don't need to re-upload in Resolve or Intelligence — they pull directly from what you added here.
Sections 4–7 — Readiness Questions
Four short questionnaires — one for each DRIVE tool. Each has 4–6 questions. Answer based on where you are right now, not where you want to be. The system uses these scores to build your engagement roadmap.
Section 4 — Taxonomy Readiness (feeds Resolve)
Questions about how clearly defined your language is: Do your teams use consistent terms for segments, products, and deal types? Does your CRM field naming match how you actually talk about deals? Is there a single source of truth for contact and campaign taxonomy? Low score = Resolve is urgent foundational work. High score = Resolve is a refinement pass.
Section 5 — Intelligence Readiness (feeds Intelligence)
Questions about data availability: How much engagement data do you have? Are you tracking what happens after a lead comes in? Do you have call recordings or transcripts you can pull from? Low score = Intelligence works from competitive and market analysis. High score = Intelligence can mine your own pipeline and engagement data.
Section 6 — Strategy Readiness (feeds Vector)
Questions about positioning clarity: Can you name your ideal buyer in one sentence? Do you have a one-liner that consistently resonates? Do you have a defined offer stack? Low score = Vector is urgent core work. High score = Vector is activation and systematization of what already works.
Section 7 — Execution Readiness (feeds Engine)
Questions about infrastructure: Do you have a content production process? Do you have someone who creates content regularly? Do you have a publishing calendar? Low score = Engine will be used later, after strategy is stable. High score = Engine can begin running immediately after Vector.
Final step — Save your results
Click the Save button in the top bar
After completing the readiness sections, look for the Save to record button in the top bar. Click it before navigating away from Discover. This syncs your scoping results to Hub (Hub is your central engagement dashboard — access it at drive.brittbowman.ai) and unlocks the downstream tools with your data pre-loaded. Don't skip this step — Resolve, Intelligence, and Vector will open without your context if you do.
After the last readiness section, the results screen appears automatically. It shows:
- Your named engagement track — e.g. "Foundation + Strategy" or "Full DRIVE Engagement", with duration, stakeholders, and deliverables
- Which tools are included and which are not yet (with explanation)
- The recommended sequence — which tool to open first
- First 30 days action items — specific tasks to start immediately
- A CTA button — "Open Resolve →" or "Open Vector →" depending on your track
Click Save to record in the top bar before leaving Discover. This saves your scoping results so all other tools can read them automatically.
Who should be in this session: The person who actually manages your CRM or marketing ops. Not just a marketer — someone who knows what the fields actually contain and how they're used. In smaller teams, this is often the founder or ops lead.
Step 1 — Source files
Check what was pulled from Discover
When Resolve loads, it automatically pulls in any taxonomy files and documents you uploaded in Discover. You'll see them listed as source cards in the left panel. Review the list — these are the files the AI will read.
Upload any additional taxonomy files here
If you have more CRM exports or field documentation that wasn't in Discover, upload it now. Click the + Add source button or drag files into the upload zone. Accepted: PDF CSV XLSX DOCX TXT. There's no limit — upload every system you use: HubSpot, Salesforce, Marketo, Outreach, whatever has field definitions.
Click "Analyze taxonomy →" to start the AI run
The system reads every source file, extracts all field names, picklist values, and naming patterns, detects conflicts across systems, and produces a draft canonical taxonomy. This takes 2–4 minutes. A progress indicator shows what stage it's on — you'll see messages like "Reading source files…", "Detecting conflicts…", "Building canonical model…". Do not close the tab.
Step 2 — Review the AI output
After the AI run completes, the taxonomy editor loads. This is the core of Resolve — you're reviewing and refining a proposed canonical structure, not building it from scratch.
Review each taxonomy category
The taxonomy is organized into categories (e.g. "Segment", "Product", "Campaign Type", "Deal Stage"). Click any category to expand it. Each entry shows the canonical field name, its type (enum, boolean, freetext), and the proposed picklist values.
Edit any field name or value that's wrong
Click any field name or picklist value to edit it inline. If the AI proposed "Enterprise" but you call it "Mid-Market", change it. If a value is missing, click + Add term inside that category and type the missing value, then press Enter.
Delete anything that doesn't belong
Click the ✕ next to any field or value to remove it. The AI will sometimes propose things from your source files that are internal legacy values or duplicates — clean those out now.
Review and edit the naming convention
Below the taxonomy is the Naming Convention section. The AI proposes a pattern — e.g. [segment]_[product]_[region]_[date]. Edit this directly in the text field until it matches how you actually want things named across all systems.
Add governance rules
About governance rules: Governance rules define how your team uses taxonomy consistently. Think of them as naming agreements — e.g., always use the full product name, never abbreviate. If you don't have a CRM admin, start simple: one or two naming rules you'll actually follow.
Click the Add a governance rule… input and press Enter after each one. These become the operating rules for how the taxonomy is maintained. Examples: "All contact records must have a Segment value before moving to Opportunity stage" / "Campaign names must follow the naming convention exactly — no abbreviations" / "The 'Other' segment value is not permitted in reporting". Add as many as are relevant.
Step 3 — Send for stakeholder approval (optional but recommended)
Click "Send for approval" in the toolbar
Once the taxonomy is in good shape, click the Send for approval button in the top toolbar. A modal appears asking for the stakeholder's name and email.
Enter the stakeholder's contact info
Type their name and work email. This is whoever needs to sign off on the taxonomy — typically the RevOps lead, marketing director, or whoever owns the CRM (skip if you're the sole decision-maker — use the Approve button in the toolbar instead). Click Send.
What the stakeholder receives
They get an email with the full taxonomy table, naming convention, and governance rules. Two buttons: ✓ Approve and → Request Changes. Clicking either button records their response — no login required. If they request changes, their notes come back to you in the Hub.
Don't skip this. Taxonomy decisions affect every downstream system. Getting explicit sign-off before implementation prevents the most common source of rework in marketing ops engagements.
Solo operator or small team? You are the stakeholder — click Approve in the toolbar directly instead of sending an external approval email. The "Don't skip this" warning above applies to teams with multiple stakeholders who need explicit alignment before CRM changes are made.
- Canonical taxonomy — all field names, types, and picklist values, approved and ready for CRM implementation
- Naming convention — a documented pattern for campaigns, contacts, and assets
- Governance rules — operating rules for how the taxonomy is maintained going forward
- Conflict report — what the AI found that was inconsistent across your source systems
- Stakeholder approval record — timestamped, stored in your engagement history
Step 1 — Upload documents
Intelligence works from the documents you upload. The more complete and specific your materials, the higher-quality the extracted signals.
Check what was pulled from Discover
Intelligence automatically loads all documents and web sources from your Discover materials intake. You'll see a file list in the left panel. Files are marked "From Discover" so you can tell them apart from new uploads.
Upload additional files
Drag files into the upload zone on the left, or click it to browse. Accepted: PDF DOCX TXT VTT PPTX. Best files to add: call transcripts (.vtt from Gong/Fireflies/Otter or .txt), win/loss write-ups, customer interview notes, competitor teardowns, analyst reports, industry surveys. Each file is processed independently — you'll see a signal count appear per file once it's analyzed.
Click "Extract signals" to run the AI
Click Extract signals (or the equivalent run button). The system processes each file in sequence — reading, extracting, and categorizing signals. You'll see a status update per file: "Reading…" → "Extracting signals…" → done with a signal count. Each file takes 30–90 seconds depending on length.
Step 2 — Review and curate signals
After extraction, signals appear in the right panel organized by type (e.g. "Buyer Pain", "Competitive", "Market Trend", "Proof Point"). Your job is to star the signals that matter most — these drive Vector.
Read each signal
Each signal card shows a title, extracted text, and source file. Read them. The AI pulls things verbatim and categorizes them — it doesn't editorialize. Some will be obvious keepers; others won't be relevant.
Star the signals that matter
Click the ★ (star icon) on any signal that represents a genuine insight — something specific enough to influence messaging. Starred signals are the ones that appear in the Client Export and get passed to Vector. You're curating, not approving everything. Aim for 10–20 starred signals total, not 100.
Delete signals that are noise
Click the ✕ on any signal that's a false positive — boilerplate, generic, or wrong. You want the signal list to be high-signal by the time you go to Vector.
Add signals manually if needed
If you know something that didn't make it into any document — something a customer said in a call, or a competitor move you're watching — click + Add signal and type it in. Give it a type and title.
When curation is complete
Starred signals are automatically available in Vector. No re-import needed. You can return to Intelligence at any time to add or remove signals.
What makes a good starred signal: Specific buyer language ("they kept saying they didn't want another tool to manage"), a concrete competitive move, a market number with context, or a proof point that's differentiated. Generic observations ("customers want ROI") don't qualify.
- A categorized signal library — all extracted insights organized by type (Buyer Pain, Competitive, Market Trend, Proof Point, etc.)
- Starred signals — the curated subset that appears in the Client Export and feeds Vector's positioning work
- Per-file signal counts — so you can see which source materials were richest
Before you open Vector: Make sure Discover is saved and Intelligence signals are starred. Vector reads from both automatically. If you open Vector before completing those steps, you'll be working without context and the outputs will be generic.
Step 0 — Diagnostic overview
Review what was loaded from Discover
The first screen shows a summary of your Discover readiness scores (taxonomy, signal, strategy, execution). These scores determine which Vector sections are active vs. flagged. Read it — it tells you what the system already knows about you.
Note any flagged areas
If a readiness score is low, that section will be flagged as "priority" in the diagnostic. That doesn't mean you skip it — it means you go deeper there. Low strategy score = Positioning step needs the most time. Low execution score = Plan step is where you'll build the most infrastructure.
Click "Begin diagnostic →" to start
This moves you into the six-step Vector diagnostic.
Step 1 — Positioning
The most important step. You're defining who you serve, what you solve, and why you're the right answer. Be specific — generic answers produce generic outputs.
Define the ideal buyer
Fill in the Ideal buyer field. Be specific: not "marketing leaders" but "VP of Marketing at Series B SaaS companies with a 3-person team and a $400K budget." One persona only — the one that represents your best customers.
Name the core constraint you solve
The Core problem solved field. What is the constraint this buyer has that you eliminate? Not a feature list — one underlying problem. "They can't figure out why their MQL-to-SQL rate is 4% when it should be 20%" is better than "they need better marketing."
State the key differentiator
The Key differentiator field. What do you do that others don't, won't, or can't? Not "we really care" or "we're boutique." Something structural: a method, a constraint you operate under, a result you've earned the right to promise.
Add your strongest proof point
The Proof field. One concrete result: a client outcome with a number, a case study headline, or a track record claim. "12 of our last 14 clients exceeded pipeline goals in their first quarter" is proof. "We've helped hundreds of companies grow" is not.
Click "Generate positioning one-liner →"
The AI synthesizes your inputs into a positioning one-liner — a single sentence that captures who you serve, what you solve, and why you. It will make multiple passes and show you the strongest version. You can edit it directly in the output field.
Steps 2–6 — Referral Engine, Credibility, Intake, Plan, Practice OS
Each subsequent step builds on the positioning you just defined. Here's what each covers:
Step 2 — Referral Engine: How do you systematize word-of-mouth? You'll define who your referral partners are, what the trigger for a referral is, and what you give them to make referring easy. The AI proposes a referral sequence.
Step 3 — Credibility: What proof do you have, and is it being used? You'll catalog your proof points — case studies, testimonials, awards, publications, partnerships — and the AI identifies gaps and suggests what to build next.
Step 4 — Intake & Stack Setup: What tools are you actually using, and are they configured correctly? You'll walk through your current stack — CRM, email, ads, analytics — and the AI flags misconfigurations and missing connections.
Step 5 — Plan: The 90-day activation plan. Based on everything so far, the AI sequences the specific campaigns and initiatives for the first quarter. You'll define goals, owners, and launch dates. This becomes the roadmap you work from.
Step 6 — Practice OS: If applicable — how does the marketing function run operationally? Meeting cadence, reporting, content approval flow. This step applies primarily to mid-market and enterprise tracks.
If your team is 1–20 people: skip this step. Your Practice OS is simply the tools and habits you already use — revisit this as your team grows.
After each step: The AI generates Campaign DNA — a structured document capturing your brand voice, target segments, proof points, and message frameworks. It's updated automatically as you complete more steps. You don't need to trigger it manually.
- Positioning framework — ideal buyer, core problem, differentiator, proof, positioning one-liner
- Campaign DNA — brand voice, segment definitions, message frameworks, proof bank
- Offer stack — your product/service tiers and how they ladder
- Referral engine — documented partner criteria, trigger, and handoff sequence
- 90-day plan — sequenced campaigns with owners and launch dates
Solo operator? You don't need a handoff — use the approved assets directly. A simple scheduler like Buffer or Later, or an email platform like Mailchimp, is all you need to publish.
Prerequisites: Engine should not be opened until Vector is complete and Campaign DNA is saved. Content produced without a positioning foundation will be on-brand in format but off-target in message.
How Engine works
Review loaded context
Engine opens with the Campaign DNA from Vector and the canonical taxonomy from Resolve already loaded. You'll see a summary of what's been pulled in. Verify the positioning one-liner and segment definitions look right — these are the guardrails for everything Engine produces.
Define content themes
Engine asks you to define 3–5 content themes — the recurring topics your content will be organized around. These should map to your buyer's journey: awareness themes, consideration themes, and decision themes. The AI suggests themes based on your Campaign DNA; click to accept or edit each one.
Set the content types you need
Select which content formats you're producing: LinkedIn posts, email sequences, ad copy, blog posts, case study outlines, sales enablement one-pagers. Engine will produce templates and first drafts for each selected type.
Review, edit, and approve each asset
The AI generates first drafts in your brand voice (derived from Campaign DNA). Review each one. Edit directly in the text editor. When you're satisfied with an asset, click Approve — it moves to the production-ready queue. Rejected assets go back for regeneration with your notes.
Export approved assets
Click ↓ Export assets to download all approved content as a structured ZIP file — organized by type and theme, ready to publish directly or hand off to your team.
- Content theme map — 3–5 themes with rationale, tied to buyer journey stages
- Production-ready content assets — LinkedIn posts, email copy, ad creative, blog outlines, case study templates
- Brand-voice-consistent drafts — written from Campaign DNA, not generic templates
- Organized export — assets sorted by type and theme for direct handoff to your team
Client Engagement Plan
A light-theme, print-ready document covering: baseline snapshot (where you were when we started), your engagement roadmap, the canonical taxonomy, top market intelligence signals, your full positioning framework, and content architecture. Download it from Hub → ↓ Client Export. This is the deliverable you share with stakeholders.
Canonical Taxonomy
A structured reference document — all field names, picklist values, naming convention, and governance rules — ready to hand to your CRM admin for implementation. Comes with a stakeholder approval record showing who signed off and when.
Campaign DNA
A brand and message reference document — ideal buyer profile, core positioning, proof bank, voice guidelines, and segment definitions. This is the document your team (or agency) uses as the source of truth for all marketing created going forward.
90-Day Activation Plan
A sequenced campaign plan — specific initiatives with owners, timelines, and success metrics — included in your Client Export from Hub.
Content Asset Library (Engine track only)
A structured set of production-ready content assets — LinkedIn posts, email sequences, ad copy, blog outlines — organized by theme and content type, ready to hand off to your team or load into your publishing tools.
One thing to remember: These deliverables are only as good as the inputs you gave the system. If you were specific and honest in Discover and Intelligence, what you get back will be specific and usable. If you were vague or incomplete, budget time for a second pass through the relevant tools.
✦ DRIVE · Client Onboarding Guide
Questions? Ask your consultant before the first session.