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Succession Bio works with life science/biotech companies to help drive sales, licensing, and partnership opportunities.

We do this through market research to identify the right companies and people, craft scientifically credible messages, and then perform the outbound sales and marketing tactics on your behalf to facilitate meetings with the right people at the right companies.

Succession

• Specializes in life sciences/biotech (it's all we do!)

• Provides market research, messaging, and outbound sales/marketing services

• Facilitates meetings and opportunities with the right people at the right companies for our clients

• Sales training for teams of 10+ who want to find and close more deals with biotech and pharma

So you've been prospecting. You've spent ages on the messaging, agonised over the list, and hit send feeling pretty good about yourself.

Then... nothing. A few bounces, a couple of unsubscribes, that one guy's reply asking you where you got his email from.

Your first instinct is to rewrite the emails. Better subject lines, punchier copy, stronger CTA. That's what everyone does, right? The emails must be the problem.

Except that's a bit like going to the doctor with a headache and immediately getting brain surgery. You haven't even checked if you're dehydrated yet.

Messaging is only one of about fifteen things that could be wrong, and it's rarely the first thing you should look at. But before we get into what might be broken, we need to start with a more fundamental question.

First: what are you actually trying to achieve?

Most teams treat cold email as a pipeline generation tool and nothing else. When it "doesn't work," they mean it didn't book meetings. But that's only one way to use outreach, and diagnosing failure against the wrong success metric will send you down the wrong path entirely.

There are at least six distinct outreach motions, each with different conversion logic:

1. Active evaluators: the direct ask. "We work with oncology teams running high-throughput screens. Worth 20 minutes to see if we're a fit?" This targets the ~3% of your market actively looking right now. Strong conversion rate, very small pool. Most companies build their entire outreach strategy around this and wonder why the volume isn't there.

2. Educate and nurture: lead with something relevant. Share an application note, a relevant abstract, a piece of insight. You're not pitching. You're starting a conversation with the other 97%. Longer cycle. Much larger pool. Success here isn't meetings booked, it's replies and engagement.

3. Distribution and channel partners: you're not selling direct, you're building your network. CDMOs, distributors, resellers. Almost nobody competes for this inbox.

4. Lapsed and dark prospects: "We spoke 18 months ago about your cell line development workflow. Things may have changed." Every company has this database and ignores it. Same cold email mechanics, warm-ish audience, completely different conversion expectations.

5. Scientific advisory and reference customers: you're not asking for budget, you're asking for their expertise. Scientists respond to this very differently. It opens doors a direct pitch never would.

6. Publication and co-authorship: instrument companies, CROs, and CDMOs build commercial relationships through application notes and co-authored papers. Zero inbox competition. Very high trust ceiling.

Before you diagnose what's broken, be honest about which of these you're running.

Define success first. Then diagnose against it.

The diagnostic stack: work from the outside in

Once you know what you're trying to achieve, work through these five layers in order. Don't skip ahead. Each layer eliminates an entire category of problems before you invest time in the next one.

Layer 1: Infrastructure - are your emails actually arriving?

This is the unsexy one, and it's also the one most people skip. If your infrastructure is broken, nothing else matters. You could write the most brilliant cold email in the history of life science sales and it would still sit in a spam folder being read by nobody.

What to check and the specific numbers that matter:

• Bounce rate. If it's above 3%, your list has bad data and every bounce damages your sender reputation further. Above 5% and you should stop sending immediately and clean your list. Use tools like NeverBounce, ZeroBounce, or Debounce to validate before you send.

• Domain reputation. Google Postmaster Tools (free) will show your domain's reputation with Gmail. You want "High." If it's "Medium" or below, that's your problem, not your messaging. For Outlook, check Microsoft SNDS. Or check your Spamhaus reputation score. Above a 5 is good.

• DNS records. SPF, DKIM, and DMARC must be correctly configured on every sending domain. If these aren't set up, major email providers will flag your messages before anyone reads a word. Your IT team or domain provider can help verify this.

• Sending domain setup. If you're sending cold outreach from your main company domain, stop. Set up separate sending domains or subdomains so you're not risking your entire company's email reputation on prospecting.

• Domain warm-up. New domains need a couple of weeks of simulated activity to build reputation. If you launched on a cold domain or an already low domain reputation, that's likely why you're in spam.

• Content spam signals. Links, images, and HTML signatures in your first email all increase spam risk. Tracking open rates or clicks also increases spam risks. Your first touch should be plain text. Always. Only after that should you consider adding links and images.

• Email variation. If you're sending near-identical words to hundreds of people, email providers will fingerprint your messages and start filtering them. You need meaningful variation in your copy.

The quick diagnostic if you don't have fancy tools: Reply rate is your best free indicator. If you're sending hundreds of emails and getting zero replies (not even negative ones or out-of-office) your emails probably aren't arriving. OOO are actually a good indication that the messages are landing in the inbox. Complete silence usually means deliverability, not messaging. Send test emails to yourself across Gmail, Outlook, and a corporate inbox before launching. Check if they hit primary, promotions, or spam.

Decision point: If infrastructure is broken, fix it before you touch anything else. Rewriting emails that never reach the inbox is a complete waste of time, and you could be throwing away perfectly good messaging.

Layer 2: Targeting - are you reaching the right people?

Emails are arriving. People just aren't replying positively. Before you blame the copy, audit who you're sending to.

How to systematically audit your list:

• Company fit. Your ICP says "biotech companies working in oncology" but the keywords you've used to build your list have filtered in CROs, diagnostics companies, and academic labs that will never buy. Pull a random sample of 20 companies from your list and check: would you genuinely pitch each of them in person? If more than 2-3 don't fit, your list has a targeting problem.

• Company stage and size. A 20-person startup and a 5,000-person pharma company have completely different buying processes, budgets, and decision timelines. Messaging that works for one will fall flat with the other. Check whether your list mixes these segments and whether you've tailored your approach accordingly.

• Job title alignment. Are you reaching the people who actually feel the problem your message describes? A VP of R&D and a Senior Scientist have very different priorities. If your messaging is about saving bench time, the VP doesn't care about bench time. They care about hitting milestones faster. Map your value prop to the title.

• Buying signals. Are you emailing people with a reason to believe they need what you're selling right now? Funding announcements get used a lot, but funding doesn't mean they're buying your category of tool. Hiring signals are often more reliable because job descriptions tell you exactly what capability the company is trying to build. Conference attendance, new programs, and published papers are all stronger indicators that someone might be in-market.

The honest test: Pull up your list and ask, “if I saw this person at a conference, would I know exactly what to say to them about a specific problem they're facing?” If the answer is different for different people on your list, you need to segment them into separate outreach. If you don't have a good answer for someone, they probably don't belong on any of your lists.

Decision point: If more than 30% of your list doesn't pass the conference test, your targeting needs work before you touch messaging.

Layer 3: Messaging - is what you're saying landing?

Your emails are arriving and you're reaching the right people. Now we can talk about what you're saying.

How to read your data before rewriting anything:

Before you change a word, look at the numbers you have:

• Reply rate gap. If reply rates are >3% (including OOO), people are seeing your emails and choosing not to respond. That's a messaging problem. If reply rates are below 1%, revisit Layer 1.

• Positive vs. negative reply ratio. If you're getting replies but they're mostly negative ("not interested," "wrong person," "we already have this"), that tells you something different than getting no replies at all. Negative replies often point to targeting issues (Layer 2) more than messaging issues.

• Where in the sequence replies drop. If email 1 gets decent engagement but follow-ups get nothing, the problem isn't your opening, it's that your follow-ups aren't adding new value.

Common messaging problems to check for:

• Length. From our analysis across 1M+ emails, first-touch emails in the 61-100 word range hit a sweet spot.

• Self-centred copy. Count the "I" and "we" statements versus the "you" and "your" statements. If you're leading with your platform, your capabilities, your data, you've lost them. Scientists get pitched constantly. The emails that work describe a problem the reader recognises in their own words.

• CTA calibration. "Can we book 30 minutes this week?" to someone who's never heard of you is a big ask. "Let me know if this is relevant" gives them nothing to respond to. Try a low-commitment next step: "Would it be useful if I shared a short case study on how [similar company] approached this?" Something concrete to say yes or no to.

• Subject lines. 1-3 word subject lines consistently outperform longer ones. Your subject line should look like something a colleague would send, not a marketing email.

• Technical credibility. If you're emailing a scientist and your email reads like it was written by someone who's never set foot in a lab, you instantly lose credibility. You don't need to write a methods section, but mentioning a technique, a bottleneck, or a pain point that's real to their day-to-day earns credibility in a sentence.

• Too many ideas. If your email covers three value props, two use cases, and a case study, the reader doesn't know what to engage with. One email, one idea, one CTA.

• No personalisation. Fully personalised 1:1 emails (where the body is custom-written per lead) outperform template-based approaches. The reader should feel like you understand who they are and why you're reaching out to them specifically.

If you want an honest and brutal assessment of your messaging, check out this tool Nick made called “Roast my Email”: https://roastmyemail.succession.bio/

Layer 4: Sequence structure - is the overall sequence working?

Individual emails don’t work. It can take 7-11 touchpoints to get that first meeting, but the sequence as a whole could be working against you.

• Not enough touchpoints. If you're sending 1-2 emails and calling it a day, you're leaving replies on the table. First-touch emails have the best per-email reply rate, but follow-ups account for the majority of total replies. People are busy and they miss things. Persistence done respectfully works. 3 days between message 1 and 2 seems to be the sweet spot.

• Repetitive follow-ups. If every follow-up is a slightly rephrased version of email one, you're not giving them a new reason to engage. Each follow-up should bring a different angle, a new piece of value, or a different framing of the problem.

• No multi-channel reinforcement. Email alone has limits. Adding LinkedIn connection requests, comments on their posts, or a short video DM creates familiarity. By the time your third email lands, they've seen your name somewhere else. Familiarity builds trust, and trust drives replies.

Layer 5: Approach and positioning - is your framing right?

Sometimes everything is executed well, but the underlying approach is off. This is the hardest layer to diagnose because it requires stepping back from the tactics.

Message-market fit vs. product-market fit. Before you question whether your product is right for the market, question whether your message is right for the market. These are two different problems, and the second one is far more common. Your product might genuinely solve a real problem, but if your emails describe it in a way that doesn't resonate with how your audience thinks about that problem, you'll get silence and mistake it for lack of demand.

How to test this: Talk to 5-10 people in your target audience. No sales pitch, just a genuine conversation. Ask them how they describe the problem your product solves. Listen to the exact words they use. If those words are completely different from the language in your emails, you've found your issue.

If those conversations reveal that nobody actually recognises the problem, it might mean:

• Your audience needs educating before they need selling. If you're selling something genuinely novel, your first outreach shouldn't be trying to book meetings. It should be raising awareness of the problem itself. Teach first, sell second. Run outreach that shares insight, challenges a common assumption, or introduces a concept. Then follow up with a more direct approach to the people who engaged. This is where outreach type #2 (educate and nurture) becomes your primary motion, not a backup plan.

• You're targeting the wrong segment. Maybe your product solves a real problem, but you're pitching it to large pharma when it's actually a better fit for 50-person biotechs who feel that pain more acutely.

• Your positioning needs reframing. The same product can be positioned around efficiency, cost reduction, risk mitigation, or speed. If "speed up your workflow" isn't landing, try "reduce variability in your results" or "stop losing data between experiments." Different framing, same product, potentially very different response.

How to actually test what's working

Diagnosing the problem is only half the job. The other half is systematically testing your way to something that works. This is where most teams go wrong. They change everything at once, declare the new version "better" or "worse," and have no idea which change actually mattered.

The core rule: isolate one variable at a time

If you change your subject line, your opening line, your CTA, and your target persona all at once, and results improve, you have no idea what worked. If results get worse, you have no idea what broke. Either way, you haven't learned anything.

Pick one variable. Test it. Read the results. Update your approach.

What to test and in what order

Work in the order that gives you the most signal with the least effort:

1. Persona splits (test first) Split your list by job title or seniority and run the same messaging to each segment. This tells you who responds to your core message before you start optimising the message itself. If VPs reply at 3% and Scientists reply at 0.5%, you've just learned more than any A/B test on subject lines would have told you.

2. Messaging angle / value prop Keep everything else constant (same persona, same subject line format, same CTA) and test different framings of the core problem. Does "reduce assay development time" land better than "improve reproducibility across sites"? Same product, different angle. This is the most important messaging test you can run.

3. CTA type Once you've found a persona and angle that gets engagement, test what you're asking them to do. Meeting request vs. content share vs. question vs. intro offer. The CTA often has a bigger impact on reply rate than the body copy.

4. Subject lines Test short vs. slightly longer, question vs. statement, specific vs. vague. But do this after you've got the bigger variables right. Optimising subject lines on a fundamentally broken message isn’t helpful.

5. Send time and sequence spacing Lower priority. Test once you've got the above dialled in. There's less variance here than people think, but it's worth a pass.

Sample sizes and when to call a test

This is where most teams get sloppy. You need enough volume to actually trust the result.

• Minimum 100 sends per variant before drawing any conclusions. Ideally 200+. Anything less and your results are noise.

• Run variants simultaneously, not sequentially. If you test version A in week 1 and version B in week 2, you're also testing "week 1 vs. week 2" and any difference in timing, news cycle, or recipient behaviour.

• Wait for the full sequence to play out before judging. Don't kill a variant after 48 hours because email 1 didn't perform. Follow-ups shift the numbers significantly.

• Reply rate is the metric that matters, not open rate. Opens are increasingly unreliable due to email privacy features. Focus on who actually responded and whether those responses were positive, negative, or neutral.

Common testing mistakes

• Changing three things at once. You'll feel like you're moving faster. You're not. You're just creating ambiguity.

• Killing a variant too early. Two days of data on 50 sends tells you almost nothing. Be patient.

• Only testing messaging when targeting is the problem. If your persona split test shows nobody in a segment responds, no amount of copy optimisation will fix it. Move on to a different audience.

• Not documenting what you tested. Keep a simple log: what you changed, the hypothesis, the sample size, and the result. Without this, you'll end up re-running tests you've already done.

• Treating every reply as equal. A "not interested" reply and a "this is relevant, let's talk next quarter" reply should not be counted the same way. Track positive, negative, and neutral separately.

Using AI to accelerate the diagnosis

You don't need an enterprise tech stack to start diagnosing what's going wrong. Here are a few things you can do with Claude or ChatGPT right now:

• Paste your email copy and ask: "What spam trigger words are in this? Is this too long? Is the CTA clear? Does this sound like a marketing email or a human?"

• Paste your target list criteria and ask: "Are there segments within this audience that would respond to different messaging? What buying signals would indicate they're in-market?"

• Paste your reply data (positive, negative, no reply counts) and ask: "Based on these numbers, is this likely a targeting problem, a messaging problem, or a deliverability problem?"

• Paste 5 negative replies and ask: "What patterns do you see in why people are saying no? Is this a relevance problem, a timing problem, or a product fit problem?"

AI won't give you perfect answers, but it'll give you a starting point for asking the right questions.

We also have a couple of tools for scrutinising your emails specifically:

• Email grader — get instant feedback on subject lines, personalisation, CTA, and overall effectiveness.

• Roast my email — get a brutally honest, entertaining critique of your sales emails from different buyer personas (not for the easily offended).

One thing to try this week

Pull up your worst-performing outreach. Don't rewrite the emails. Instead, run through the five layers above in order. Odds are the problem isn't where you think it is.

And if you've already diagnosed the issue and want a second opinion, reply to this email. We genuinely want to hear what you're seeing.

Apple Podcast | Spotify | YouTube

Episode 84: How Biotech Founders Navigate Growth Stages and Commercialization: Sonya Weigle

1. Lead Generation: We’ll build target lists, write scientifically relevant messaging, and send messages on your behalf to book qualified sales meetings with biotech and pharma companies.

2. Training for Teams: If you want to upskill your team around prospecting, driving to close, key account management, AI, or any other topic, we can put together a training plan specific to your organization’s needs.

3. Strategy Call: Need more than training? Want help implementing and executing your sales strategy? In a 30-minute call, we will assess your company’s current situation and identify growth opportunities.