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Stealth Brands Lose RFPs
By Jasmine Gruia-Gray
A 40 brand : 60 performance Marketing Plan for Life Science Tools
I once worked at a company that flipped the switch on for pure performance marketing and turned the brand lights off. Overnight, our marketing calendar turned into a series of emails and a dashboard of open rates (OPR), click-thru rates (CTRs) and endless A/B tests that differed by “a comma and a color”. We cut anything that didn’t have a last-click line in the spreadsheet: PR gone, contributed articles gone, our KOL series gone, well you get the point. It was all in the name of cutting anything that didn’t have a direct tie to the sales pipeline.
The outcome … our key competitor leveraged and mocked our absence in a fear, uncertainty and doubt type of campaign. Competitors framed our narrative before we got in the room and request for proposals (RFPs) started dropping off...
What changed, so we’re clear on definitions
Brand Marketing
|
Performance Marketing
|
---|---|
Everything that makes scientists remember you with confidence before they’re shopping: PR, thought leadership, KOL collaborations, off-site explainers, community presence, distinct voice and visuals |
Everything that turns active demand into pipeline: paid search/social, retargeting, email nurtures, offers |
PR, advertising and contributed bylines in trade journals |
Paid search, email nurtures |
KOL collaborations (poster walk-throughs, co-authored notes) |
Conversion rate optimization, landing page testing, lead scoring |
Community sponsorships |
Bottom-funnel offers (demos, trials) and bid automation |
Primary KPIs: unaided/aided recall, branded search, direct traffic, off-site mentions/citations, RFP longlist inclusion, win-rate lift. |
Primary KPIs: CTRs, pipeline volume/velocity by channel, Sales Qualified Leads (SQLs). |
What we analyzed (so you can stress-test the conclusions)
In the spirit of learning from history and to understand how the conversation shifted, I “partnered” with ChatGPT to do an industry agnostic, retrospective analysis of global discussions across industry blogs, marketing news, and public forums (Reddit, LinkedIn, Quora, Twitter) for each year from 2020 to 2024. Mentions were counted for four categories, ensuring at least 100 mentions per category per year for reliability.
- performance marketing,
- brand marketing,
- AI + performance marketing
- AI + brand marketing
Sentiment was scored on a –1 to +1 scale, and common variations such as “growth marketing” for performance and “awareness marketing” for brand were included. Early year data for AI topics were sparse, so interpret those year one scores with caution.
What this data is, and isn’t. The conversation and sentiment trends below show what marketers talked about most from 2020–2024, not how budgets shifted or what performed best. Think of it as a weather vane, not a P&L. Use it to sense interest and mood, then validate mix decisions with your own recall, branded search, direct traffic, and RFP inclusion metrics.
What the data say: 2020–2024
Annual conversation volume and share by category
Year – Context | Performance Marketing | AI + Performance Marketing | Brand Marketing | AI + Brand Marketing |
---|---|---|---|---|
2020 – pandemic | 1,000 (55.6%) | 100 (5.6%) | 600 (33.3%) | 100 (5.6%) |
2021 – pandemic | 1,300 (60.5%) | 200 (9.3%) | 500 (23.3%) | 150 (7.0%) |
2022 – AI early adopters | 1,400 (56.0%) | 300 (12.0%) | 600 (24.0%) | 200 (8.0%) |
2023 | 1,200 (37.5%) | 800 (25.0%) | 800 (25.0%) | 400 (12.5%) |
2024 – AI increasingly incorporated in martech | 1,000 (27.8%) | 1,000 (27.8%) | 1,000 (27.8%) | 600 (16.7%) |
What is the “so what” for tools marketers?
- Performance dominated the conversation through 2022.
- AI discussion exploded in 2023. By 2024, AI + performance hit parity with standalone performance, and AI + brand held a meaningful slice.
- Brand regained equal footing with performance in 2024 at 27.8% share each. My POV is that in life science tools, solutions with long sales cycles, achieving this balance could favor what you need for mental availability, branded search, and RFP inclusion.
Sentiment rounds out the brand and performance marketing story
The tone around pure performance (blue circles) cooled from positive to near‑neutral by 2023 as teams hit diminishing returns and creative fatigue. Brand (red squares) sentiment climbed by 2024 as marketers re‑weighted for mind-share equity and resilience. AI + performance (teal triangles) drew the most enthusiasm late in the period, while AI + brand (yellow diamonds) stayed positive but more cautious, reflecting concern about sameness and authenticity.
The takeaway: “Brand marketing drives sales but performance doesn’t build brand,” as professor Mark Ritson succinctly put it on marketingweek.com. Use AI where it is strongest, but be careful not to outsource brand voice (part of building a relationship with your customers) as it represents the human side of your brand.
Why this matters in life science tools
RFP reality. Procurement and scientific evaluators often pull product candidates from memory, perceptions and their own reference community. If you are dark on brand, you are absent from longlists even when your specs are strong.
Cycle math. Brand exposure works on conference calendars, KOL cadence, and publication windows. It raises recall before budgets open (part of the 95:5 rule, although brand marketing isn’t just advertising). Performance tactics then harvest demand more efficiently.
Risk reduction. A credible brand compresses perceived risk… “nobody ever got fired for buying ABI”. It reduces price sensitivity and smooths validations, especially in regulated-adjacent workflows and critical assays.
Where AI helps, and where it hurts
AI + performance marketing
Use AI to scale the operational work: iterations, checklist reviews, attribution model analysis, persona to critique campaign content, ideal customer profile selector, etc. It helps you respond to signal faster, protects customer acquisition costs (CAC), frees time for strategic thinking and frees budget for brand assets.
AI + brand marketing
Use AI to assist, not define, brand voice. Treat it like a power tool for drafts, formats, and personalization at scale. Keep humans in charge of narrative, taste, and governance so the work remains distinctive and on brand.
The 40:60 rescue plan
Assessment (weeks 1 - 2)
- Pull the last 12 months of spend, pipeline, and channel performance.
- Calculate your current brand vs performance ratio.
- Quick VOC: Run a quick unaided and aided recall pulse among 50 scientists in your category.
- Baseline branded organic search, direct traffic, and inclusion rate on RFP longlists. Capture off-site mentions/citations (press, trade pubs, webinars, posters) and KOL map (who talks about your category, where).
Success looks like: a validated baseline mix and three benchmark metrics to track.
Reallocation towards 40:60 (weeks 3 - 12)
- Shift 10–15% (start smaller if the appetite isn’t immediately there) of performance spend into brand.
- Brand bets: one tight problem–solution narrative, an evergreen 90-second workflow explainer for your top assay or flagship instrument, a monthly KOL video poster walkthrough.
- Performance hygiene: keep the best CAC channels on, apply AI for creative testing and bidding, and lock brand voice guidelines so AI can’t change tone or claims.
Success looks like: pipeline holds or improves while branded search and direct traffic rise.
Compounding (weeks 13 – 24)
- Publish one “hero proof” asset each month: a third-party validation, a mini case with quantified outcomes, or a coauthored technical note.
- Build a simple content automation routine so every asset fuels performance (retargeting, email nurtures, conference followups).
- Keep AI focused on scale and speed. Guard against the temptation to let it set strategy or voice.
Success looks like: higher inclusion on RFP longlists, stronger midfunnel engagement, and more efficient retargeting.
Review and Lock (weeks 25 – 36)
- Rerun recall pulse, compare branded search and direct traffic, check RFP hit rate and cycle time.
- If CAC is stable and recall is up, lock the 40:60 mix for two more quarters. If CAC rises, tune spend by channel before touching the brand allocation.
Guardrails that prevent backsliding
- Separate roles, share goals. Brand = memory, emotion and preference. Performance = capture and conversion. Both share a revenue target tied to pipeline quality and RFP hit rate.
- Measure what matters. Replace vanity metrics with unaided recall, branded organic search, direct traffic, RFP longlist inclusion, and win rate.
- Document brand voice. Provide simple rules for tone, claims, and visual systems. Allow room for scientific specificity without jargon walls.
- AI governance. Use AI for production, not for strategy. People should focus on content quality.
Explain “the why” with familiar math, don’t go dark:
Brand isn’t a vibe, it’s math you can show.
Brand raises base conversion by increasing familiarity and perceived safety, which lowers CAC at the same media spend.
Brand lowers price sensitivity, protecting gross margin.
Brand reduces time to shortlist, which shortens cycle time.
Performance then captures the increased demand more efficiently. The two are not in conflict; they compound.
The story comes full circle
Remember the team that flipped the lights off on brand? Here’s what I wish we’d done differently:
- A 40:60 guardrail baked into planning so brand couldn’t be zeroed out during a rough year.
- A single “proof calendar” with one off-site asset per month e.g. a KOL poster walk-through, a contributed article. High value content that peers and models can cite.
- Just four KPIs alongside CAC: unaided recall, branded organic search, direct traffic and RFP longlist inclusion.
- While AI didn’t exist at the time, a voice/claims sheet for AI would have been helpful so that speed never rewrote our tone or promises.
Thanks to budget guardrails, a lot of patience from KOLs to create new high-value data-based content, an aligned commercial strategy, and product innovation we were able to recover and grow.