About woltam consulting

After 20+ years in commercial and cross‑functional roles at multinational pharma companies, I kept encountering the same challenge: abundant data and content, but slow, fragmented execution that didn’t consistently serve HCPs or patients.

Insight

Programs performed best when three inputs worked together: voice‑of‑customer (e.g., Medallia), peer‑to‑peer HCP insights (e.g., MedShr), and robust market data (e.g., IQVIA). Add clear governance and modular content, and you can move faster—without compromising compliance.

Why woltam

I started Woltam Consulting to deliver that operating model to pharma and healthcare teams: evidence‑led strategy, measurable digital performance (SEO/PPC), and responsible AI workflows that speed learning cycles and strengthen trust.

What we do

  • Build 90‑day omnichannel plans that align brand goals with HCP and patient journeys
  • Improve findability and efficiency with non‑branded SEO and intent‑driven PPC
  • Design AI‑assisted processes for research, drafting, and QA—always with human review and governance
  • Establish KPI ladders and dashboards so teams can scale what works and stop what doesn’t

What we stand for

  • Compliance and privacy‑by‑design
  • Accessibility, localization, and a health‑equity lens
  • Practicality: clear scopes, fast pilots, transparent reporting

What we hope to achieve

  • Help teams ship useful, compliant work faster
  • Make marketing measurably more valuable to HCPs and patients
  • Prove that ethical, evidence‑led marketing can also be the most effective

Mission: Make healthcare marketing more useful, inclusive, and measurable—so HCPs and patients get what they need, and teams can prove impact with confidence.

Our ideal client

My ideal clients are specialty pharma and biotech teams who value evidence-led, compliant marketing and want measurable wins within 60–90 days. Common challenges include fragmented omnichannel execution, low non‑branded visibility, high CPA, slow MLR cycles, weak feedback loops with HCPs, and uncertainty about adopting AI safely and effectively.