Meet [NAME_GIVEN_1]Durva.
Your demand gen hire, already on the job.
Every line of the job post, done once, as if I'd started Monday: a full integrated campaign, a landing page and form, the email sequence, the webinar program end to end, LinkedIn ads, list building, events, case studies, rep assets, an ABM pilot and the report that ties it all to pipeline.
Facts about Limina come from getlimina.ai. Targets and numbers marked SAMPLE are illustrative.
My plan for the first 90 days.
The marketing function is young, so the first job is to make campaigns repeatable. By day 90, every program on this page runs on a calendar, a template and a number.
Sit next to the buyer
- Shadow the MDR and 5 sales calls; log every objection
- Audit HubSpot: lists, forms, UTMs, lifecycle stages
- Read every guide, blog and case on getlimina.ai
- Launch webinar #1 promotion (it's 4 weeks out)
Output Buyer question bank · HubSpot fix list · webinar #1 live
Turn one-offs into systems
- Integrated campaign live: page, form, 5 emails, ads
- Case study pipeline: 3 customers in motion
- LinkedIn audiences + first A/B tests
- ABM tier 1 list agreed with the MDR
Output Campaign live · case pipeline · ABM list
Tie it to pipeline
- Monthly report: leads, MQLs, pipeline by program
- First case study published, cut into rep assets
- Shift budget to what's converting
- Webinar #2 and #3 on the calendar
Output Pipeline report · first case · budget shifts
One big campaign, start to finish.
Campaign name: “Every prompt is a data transaction.” A quarter-long campaign built on Limina's own line. One idea, one webinar, one guide, run across email, LinkedIn, syndication and the MDR, with every touch tracked to pipeline.
Campaign brief
SAMPLE TARGETS| Goal | Net-new leads from regulated enterprises building AI, converted to MQLs and MDR meetings |
| Audience | CPOs, DPOs, CISOs, Heads of Data/AI at financial services, insurance, healthcare and pharma, 1,000+ employees |
| Insight | Teams want to use their best data in AI. Compliance says no. Cloud tools miss too much, DIY costs too much. |
| Offer | Webinar “Governing every prompt” + the guide “De-identification for AI Training Data” |
| Proof | 99.5% accuracy (Providence Health) · 48 hours to minutes (Boehringer Ingelheim) · runs in your VPC |
| Channels | Email · LinkedIn (organic + paid) · content syndication · partner co-marketing · MDR sequences |
| Targets | 600 registrations · 40% attendance · 180 net-new leads · 60 MQLs · 15 meetings |
| Owner | Durva (campaign) · MDR (follow-up) · VP Marketing (approval) |
Message house
For technical + compliance buyersUse your most restricted data in AI, without it ever leaving your environment.
Audit-ready outputs for HIPAA, GDPR, CPRA and PCI-DSS. Expert determination your auditors accept.
Deploys in your VPC or on-prem. No third-party processing, no outbound calls.
Context-aware, 50+ entity types, 52 languages. De-identified data that stays useful.
Stop maintaining DIY scripts. Most customers are running in days, not months.
Launch timeline · 10 weeks
Week 6 = live webinarThe sign-up page. It is live. Try it.
I built the real page, in Limina's look, with a working form, a live demo and a calendar invite. Open the live page ↗
Governing every prompt: how regulated enterprises put sensitive data to work in AI
Every prompt is a data transaction. Learn how privacy, security and data teams at banks, insurers and health systems de-identify PII and PHI across RAG pipelines and agentic workflows, without slowing AI down.
- Where PII and PHI leak in RAG and agent workflows
- What “audit-ready” looks like for HIPAA, GDPR and PCI-DSS
- Why context beats pattern matching (with a live demo)
Form spec
| Field | Rule |
|---|---|
| Work email | Block free domains; enrich company + size |
| Job title | Map to persona: Privacy / Security / Data-AI / Other |
| AI governance stage | Drives nurture branch + MDR priority |
| Hidden | utm_source, utm_medium, utm_campaign, utm_content, page_url, campaign_id |
| On submit | Add to campaign · send confirmation + calendar invite · notify MDR if tier 1 account or “In production” |
Launch QA
0 / 10Page
Form
Tracking
The 5 emails we send.
Invite, reminder, last call, then a split follow-up: attendees get the next step, no-shows get the recording. Written for people who read privacy law for fun, and people who don't.
How I run every webinar, start to finish.
Topics, speakers, promotion, registration, the live session and follow-up, each with an owner and a date. The same runbook, every time, so quality goes up and effort goes down.
1 · Topic bank (next 7 webinars)
Built from Limina's own guides + buyer questions| Webinar | For | Hook | Speakers | Repurpose into |
|---|
2 · Runbook: T-28 to T+14
Owner in brackets3 · Live session run sheet (45 min)
| Min | Segment | Who |
|---|---|---|
| -15 | Tech check, slides locked, polls loaded, backup host ready | Durva |
| 0 | Welcome, housekeeping, poll 1: “Where are you with AI governance?” | Moderator |
| 3 | The problem: where PII/PHI leaks in RAG and agents | Limina SME |
| 15 | Live demo: context vs pattern matching | Limina SME |
| 25 | Customer story: what changed, in numbers | Customer |
| 35 | Q&A (seeded with 3 questions from registration) | All |
| 43 | Poll 2: “Want a 20-min data review?” + close | Moderator |
4 · Follow-up, split by behaviour
| Segment | Within | What happens |
|---|---|---|
| Said yes to poll 2 | 1 hour | MDR call + calendar link; marked hot in HubSpot |
| Asked a question | 24 hours | Personal answer from the SME + relevant guide |
| Attended | 24 hours | Recording, slides, guide; nurture branch by persona |
| No-show | 24 hours | “Sorry we missed you” + recording in 3 clips |
| Tier 1 account, any | Same day | MDR + AE get a summary of who came and what they asked |
5 · Speaker kit
Sent at T-21- One-page brief: audience, 3 takeaways, what not to pitch
- Slide template in Limina brand, 12 slides max
- Social card with their photo + a ready-to-post line
- Tech check invite at T-3 and a 15-min dry run
- Thank-you note + clip of their best moment within 48 hours
6 · How I'd judge each webinar
SAMPLE TARGETSAds on LinkedIn, shown to the right people.
Who sees our ads, four ads to test (one idea each), and tracking that counts cost per MQL, not cost per click.
Audience: who
- Titles: CPO, DPO, CISO, Head of Privacy, Head of Data, AI/ML lead, Compliance Director
- Seniority: Director, VP, CXO
- Industries: Banking, Insurance, Hospitals and Health Care, Pharmaceuticals
- Size: 1,000+ employees
Audience: smart layers
- Matched audience: ABM tier 1 + 2 accounts
- Retarget: pricing, product and guide visitors (90 days)
- Lookalike off closed-won (when volume allows)
- Exclude: customers, competitors, students
Tracking
- Insight Tag + conversion API on form submit
- UTMs on every ad, one naming rule
- Offline conversions: MQL and SQL back to LinkedIn
- Weekly: CPL, cost per MQL, pipeline per $
4 ads to test, one idea each
Single image · 1200 × 1200 · same audienceWhere we share each piece of content.
Every guide and webinar gets a promotion plan across owned, earned and paid, plus one partner angle. Here's the plan for the AI training data guide.
| Channel | Type | What we ship | Measure |
|---|---|---|---|
| Email newsletter | Owned | Feature + 3 key takeaways, segmented by industry | Click-to-download rate |
| LinkedIn company page | Owned | Document carousel of the 5 rules; native video clip | Engagement, follower growth in target titles |
| Exec + employee posts | Owned | Share kit: 3 ready posts, 1 graphic per person | Reach, profile visits |
| Privacy communities | Earned | Answer real questions with the guide's frameworks, no hard sell | Referral traffic |
| Trade press | Earned | Pitch a data story from the guide (e.g. “where PHI hides outside the EHR”) | Coverage, backlinks |
| Content syndication | Paid | Guide on 1-2 B2B networks with persona + industry filters | Cost per lead, lead-to-MQL rate |
| LinkedIn Document Ads | Paid | First 3 pages free, gate the rest with a lead form | Cost per MQL |
| Partner co-marketing | Partner | Joint piece with a stack partner Limina plugs into (AWS, Azure, Snowflake, NVIDIA NeMo): “de-identify before you load” | Partner-sourced leads |
Growing our list of buyers, and keeping it clean.
A segment model sales trusts, a list-building routine, and a weekly hygiene check, because list cleanup is part of the craft.
Segment grid · persona × industry
SAMPLE COUNTS| Fin. services | Insurance | Healthcare | Pharma | |
|---|---|---|---|---|
| Privacy | 420 | 310 | 380 | 190 |
| Security | 510 | 260 | 290 | 140 |
| Data / AI | 640 | 330 | 350 | 270 |
| Compliance | 380 | 290 | 240 | 160 |
Each cell gets a target (net-new per quarter) and a nurture track. Thin cells become list-building priorities.
Weekly list hygiene
0 / 8Import
Clean
Check
Book meetings before the event starts.
A pre-show play for any privacy, security or health data event: prospects know we'll be there, and the MDR fills the calendar before the booth opens.
Attendee list + ABM accounts + open opportunities, agreed with the MDR
Booth, talk time, 20-min meeting slots; one ask
Company post + targeted ads to the event's attendee audience
3 touches: email, LinkedIn, call; personal reason to meet
Where to find us, what we'll demo, a small gift for booked meetings
Badge scans tagged by conversation quality, same-day notes
Personal email per conversation; hot ones to AE within 24 hours
Event shortlist
- IAPP Global Privacy Summit (privacy leaders)
- RSA Conference (security)
- HIMSS (health data)
- AI and data governance summits for financial services
Meetings, not badge scans
Success = pre-booked meetings, then meetings held, then opportunities in 60 days. Scans are a by-product.
“20 minutes, your data, our engine.”
Offer a live test on a sample of their messy text (call transcripts, notes, chats). The product does the selling.
Getting happy customers to tell their story.
I'd own the logistics: source willing customers with CS and Sales, schedule interviews, manage approvals, and make the customer feel their time was well spent. Six customers already praise Limina in public on getlimina.ai; that's the candidate list. The other columns show example stages.
The ask (via CS)
“Hi Sam, your team's results with Limina have been impressive, and we'd love to share them. It's a 30-minute call, we write everything, and you approve every word before anything goes live. Would you be open to it? Happy to work around your schedule.”
Interview guide (30 min)
- What were you trying to do with this data?
- What did you try before? What broke?
- Why Limina? What did the evaluation look like?
- What changed, in numbers? Time, accuracy, cost
- What would you tell a peer in your role?
Approval path
- Draft to champion (5 business days)
- Champion to their legal / comms (we track it)
- Logo + quote approval in writing
- Publish, then thank-you note + their own copy
- Cut into rep assets the same week
Tools the sales team can send today.
Campaign content and case studies, adapted for each industry and use case, in formats reps use in follow-up.
“Detect payment data the way customers say it”
One-pager: PCI in call transcripts, legacy archives, AI on communications data. Proof: banks that tested competitors found 15-30% of PCI data went undetected.
“Unstructured PHI, outside the EHR”
One-pager: physician conversations, medical inquiries, expert determination. Proof: 99.5% accuracy for Providence Health; 48 hours to minutes for Boehringer Ingelheim.
“Enable AI on claims data”
One-pager: claims notes, adjuster calls, documents. Proof: runs in your environment; audit-ready outputs for compliance.
MDR follow-up after the webinar
TemplateObjection cards
From Limina's own siteGoing after our top target companies.
A small, measurable pilot: the MDR and I agree the accounts, I build the lists and materials, we review together every two weeks.
Built for one account
- Account brief: AI initiatives, data types, regulators, buying group
- Personalised landing page + a tailored data-review offer
- Exec-to-exec note; invite to a private roundtable
Built for an industry
- Industry one-pager + case study
- LinkedIn ads to the buying group
- MDR sequence with industry proof
Built for a persona
- Webinar invites + guide promotion
- Intent-based retargeting
- Move up a tier on engagement
Account selection criteria
| Fit | Regulated industry, 1,000+ employees, active AI programme |
| Pain | Large unstructured data: calls, notes, documents, chats |
| Signals | Hiring AI/privacy roles, AI announcements, our content engagement |
| Access | Known contacts in privacy, security or data |
Pilot scorecard
SAMPLE TARGETSHow we know it is working.
Exactly the measures in the job post, every month, with one recommendation: where to shift effort next.
Marketing report · October
SAMPLE DATAMQLs by program
Shift 20% of syndication budget into webinar promotion.
Webinar MQLs convert to meetings at 3x the rate of syndicated leads at a similar cost. Keep syndication for the healthcare segment only, where it's still beating the average.
Sample reasoning on sample data, the shape of every monthly note.
About Durva.
The job post asks for 0-2 years in B2B marketing, execution, an analytical mind, clear writing and technical curiosity. Here's where I stand.
Durva Thakkar
Content Marketer · B2B campaigns, SEO and outreach · Ontario, Canada
- Outreach Specialist, Bsquaree: ran targeted outreach campaigns, managed pipelines and follow-ups, reviewed results to improve response rates
- Content Writer, Missive Digital: SEO content and keyword research; content that helped drive a 73% increase in inquiries
- Content Writer, freelance: content calendars, SEO blogs, LinkedIn and email for B2B clients
- Sales & Marketing Intern, Rewynd Snacks: campaigns that contributed to a 40% increase in sales
Why this role, why Limina
- Execution: I built this page, the campaign, the emails and the systems on it myself
- Analytical: postgrad in Information Systems Business Analysis; I like knowing why a number moved
- Tools: HubSpot Marketing Hub certified; Excel, UiPath, AI-assisted workflows
- Technical curiosity: I read Limina's guides on HIPAA expert determination and AI training data to write this page, and I want to understand the product deeply
- Timing: every company building AI has to govern the data inside it. That's a category I want to grow with.