Jessyka Bailey

Author: Jessyka Bailey

  • Account Scoring System: Three Weeks In

    Hi team. Can I call you team?

    I know I’ve been a little quiet, but if you’ve been following along, you probably get it. We’re getting close to the end of Q3, so I’ve been auditing my sales process, working deals, and trying to get things wrapped up before Q4.

    What I’ve Been Building

    If you’ve read some of my other posts, you also know I’ve been thinking a lot about account selection. Not just who fits an ICP, but who actually deserves my attention right now. For the last three weeks, I’ve been turning that thinking into an actual system that will ultimately take my large territory and tell me where I need to focus.

    If I can be completely honest, I genuinely thought this would be easier.

    Getting a System to Apply the Same Rules Every Time

    There are so many variables and situations that have to be considered. The hardest part so far hasn’t been finding a great account. It’s been getting the system to apply the same rules consistently and surface the same accounts for the same reasons every time.

    And I think what’s surprised me the most about building this is that you can make something, test it, and something weird can happen. Then you figure out why, make some changes, and run it again. And after all of that, something else breaks. So you start from the beginning and run it again.

    When the System Works but the Rules Are Wrong

    You can even have a system that works exactly how you told it to, and the problem isn’t anything the system is doing. It’s the rules you gave it.

    That’s basically what I’ve been doing for the last three weeks.

    How Long Does It Actually Take to Build Something?

    It’s given me a new appreciation for how long it actually takes to build something. Three weeks ago, I probably would have heard that something took six months to a year to build and wondered what could possibly take that long.

    I get it now.

    Making something work once is one thing. Making something that keeps working when you throw different situations at it is a completely different problem.

    Heading Into Q4

    Anyway, Q3 has given me a lot to think about: what worked, what didn’t, where I wasted my time, and where I should be spending more of it. So I’m heading into Q4 with a slightly different sales process, a system I built to support it, and a few things I want to test. Hopefully I’ll have some interesting results to share.

    Until then ✌️

  • What I’ve Been Building This Week

    It’s kind of weird that I haven’t written here in almost seven days, but I’ve actually been doing a lot.

    For those who don’t know, I run a non-alcoholic newsletter called The Dri Edit. We have about 600 subscribers and up until now, we’ve pretty much only existed through email.

    We’re now moving every article over to a more digital system where the stories we’re finding and writing can live on our website. This will hopefully mean we can automate some of the processes and eventually have an opportunity to generate revenue through things like affiliate links.

    Shea is getting ready to launch merchandise for No Booze Babes, so I’ve been trying to help her as much as I can. P.S. It’s launching tomorrow 9/1 🙂 @ noboozebabes.com

    And if I didn’t already have enough going on, I started reading The Coming Wave by Mustafa Suleyman, which, naturally, sent me down another rabbit hole.

    The book got me thinking more about AI safety and, specifically, what actually keeps an AI system from doing something it isn’t supposed to do.

    I figured the best way to understand it was to build a very small application.

    I built a mini CRM running locally on my computer. I connected it to the Claude API and built a simple agent powered by Claude. The agent has a very limited set of tools it can use and specific permissions around what it can access. The interesting part wasn’t really building the CRM. It was learning how I could control what my agent can do.

    For example, the agent can ask my application for an account, but Claude itself doesn’t get direct access to my database. My application checks whether the agent has permission to access that account first. If it doesn’t, the request gets denied.

    That led me into learning about tools, permissions, authorization layers, least privilege, and why you shouldn’t depend on an AI model to follow a rule just because you told it to.

    The simplest way I’ve found to think about it is: you don’t just tell the AI what it can’t do. You build the system so it actually can’t do it.

    Lastly, I’m still working on my five-account outbound experiment.

    I have been working the five accounts, but I’m no longer convinced that I picked the five most opportunistic accounts. I found some errors in the testing and ranking system I used to choose them, which is kind of the point of doing the experiment in the first place.

    So there’s more work to do there.

  • Selling in an Age of Abundance

    What makes you trust someone when you know they’re trying to sell you something? And what’s that feeling when you’re being sold something and you feel like something is off? Would you call that intuition? A gut feeling? Vibes???

    Now think about the opposite and remember a time when you had a great experience being sold something.

    I like to relate this to serving because, just like a majority of the products we’re trying to sell, eating out is a nice to have, not a need to have. And the server is quite literally trying to sell you something. Whether that’s an experience, that osetra caviar, or even an idea of how that food is going to taste.

    The best servers will paint the picture for you. But what really makes you believe them?

    Is it the reputation of the restaurant?

    Is it everything that happened between walking through the door and sitting down at the table?

    Or is it something about the person standing in front of you? The way they talk about the food, the way they listen to you, or the confidence they have when answering your questions?

    Because anyone can tell you that the hanger steak is amazing but a great seller makes you believe that you’ll think the hanger steak is amazing.

    As I’ve been thinking about what selling will become in the age of AI, this difference really matters. A great seller isn’t just repeating everything they know. They’re paying attention to you, asking the right questions, picking up on what your preferences are and using that evidence to make recommendations specific to what you need.

    A lot of skills we’ve historically valued in sales are getting cheaper. I don’t think they’re becoming less important. Research, product knowledge and being prepared still matter. But the effort that it takes to do those things well is changing.

    If everyone can walk into the room prepared, what becomes the most valuable asset?

    Maybe it’s your ability to make the person sitting across from you believe you.

  • How to Prioritize Accounts: How I’m Choosing Who to Prospect

    In my last post I mentioned that I was going to spend 30 days working only five accounts. I quickly realized the first and obvious problem was that I had to figure out which five were worth my attention.

    This seemed simple enough. I would start with my pool of accounts and then I would rank them. Decide what makes a company a good fit, give more weight to the factors that matter most, and let the best accounts rise to the top.

    Simple.

    Except that I immediately ran into a problem. The first run of the ranking surfaced the wrong companies.

    Going into this, I assumed that the more evidence I could find of a problem my product could solve, the more valuable that account was to work. But when I looked at the accounts that rose to the top, I realized the system was rewarding something I hadn’t intended. One of the factors I was treating as evidence of opportunity was also really common among companies where there was less opportunity.

    The problem wasn’t that these accounts were smaller. It was that I was giving them more weight than accounts where the same amount of work could lead to a much bigger opportunity. At the end of the day I am still in sales.

    Once I understood that, I stopped trying to build one perfect score and started thinking about the order these decisions should happen in. If I were building this again, this is where I’d start.

    Rules

    1. Create your gates

    These are the things that have to be true before an account is worth spending time on. Depending on what you’re selling, your gates will be different. To find mine, I made a list by asking myself, “What would make a company a hard no?”

    Here are some examples:

    • Company is outside your target market or geography.
    • Company is too small or too large for your product.
    • They don’t have the technical setup your product requires.
    • There’s no actual use case for what you sell.
    • They already use your company/product.

    Structured funnel

    2. Rank your remaining accounts

    Once an account gets through those basic checks, ranking starts to become a lot more useful. Now you’ll be comparing companies that actually make sense.

    Here are a few questions that could help you start structuring your funnel:

    • How closely does it fit your ideal customer?
    • What technology are they using?
    • How are they currently solving the problem?
    • How difficult would it be to replace what they already have?
    • How valuable is the problem if you can solve it?

    3. Understand what you don’t know

    When you’re building your structural funnel, having a clear understanding of what you don’t know is just as important as having clarity on what you do know.

    I’m working with limited tools, and unless you’re doing this at a company with unlimited resources, you’ll likely be limited to the tools you have available. Naturally, there was information I wanted to know about every company that I couldn’t get reliably across a few hundred accounts.

    For some of it, I could find clues. Website traffic could tell me something about the potential size of an opportunity. The technology a company uses could tell me something about how difficult they might be to win. Recent hiring could tell me where they might be investing, and job postings could give me an idea of what problems or priorities they might have internally.

    But those are still proxies. They can tell me where to look, but they aren’t necessarily reliable enough to make the decision for me.

    As you’re building your funnel, each step is making a decision about which accounts deserve to move forward. If I’m going to use a piece of information to eliminate an account or move another one ahead of it, I need to know how much I can actually trust it.

    One other thing I learned: the research should get more expensive as the list gets smaller. I don’t need to deeply research hundreds of companies. I need enough information to narrow the list, and then I can spend more time figuring out what’s actually happening at the accounts that survive.

    From that, I’m left with a much smaller group of accounts that are actually worth paying attention to.

    These aren’t the accounts that are most likely to buy. I don’t know that yet. I will say, these are the five accounts where the fit is strong enough, the opportunity is big enough, and there’s enough evidence to justify spending more time.

    Rules → structured funnel → collected outcomes → learned ranking.

    Next up: collected outcomes.

  • How Many Accounts Should You Actually Work?

    When I think about outbound sales, I think about touchpoints. Emails, LinkedIn Connections/Messages, calls, and all of the ways that you’re trying to get in front of somebody to create awareness.

    But I think that we’re putting way too much emphasis on whether one of those individual touchpoints books a meeting. I can say from experience, a lot of the time, that isn’t how it happens.

    What outbound actually looks like

    What really happens is this:

    Someone gets an email from you and they don’t reply. A little bit later, you send them another email and marketing is also touching that same account. Then they go to your company’s website, where they start doing their own research, and a few days later, they fill out a demo request form.

    To me, this is outbound working.

    The outbound didn’t necessarily create the lead on its own, and neither did the marketing. What they did was work together. They told someone the same story in different ways enough times that eventually that person became curious enough to think, “this might actually help my business.”

    AI changed the volume, not the job

    Now, AI has made it possible for sales reps to create more touchpoints than ever. We can research faster. We can write and personalize emails at a scale that would have never been possible for one person to do manually. Today’s SDR can get in front of more people than they ever could before.

    But so can everybody else.

    So, I don’t think the answer is to use AI to create more touchpoints. I think the opportunity is to make the touchpoints we do create better.

    Find the right company. Find the right person. Find an actual reason why that person might care right now. And then be persistent enough to actually get in front of them.

    To get there takes judgment. And this is where I think the role of the SDR starts to get more interesting as AI does more of the work.

    Find your key accounts

    Right now, I don’t think any manager should be having their reps try to meaningfully work hundreds of accounts. If you’re responsible for touching hundreds of accounts, somebody is getting missed. I’m sorry, there just isn’t enough time to actually think about all of them.

    So hear me when I say this: you need to find your key accounts.

    If a rep has a smaller group of accounts to really focus on, they can actually spend time figuring out how to get into them.

    They can research the company. They can find the right people instead of just going after the most obvious title. They can look through LinkedIn and see if they know somebody who knows somebody. They can figure out what’s happening at the company right now and whether there is actually a reason to reach out.

    And most importantly they can start looking beyond the obvious ways of getting in front of someone. They can get creative.

    That’s the piece I think gets missed when we talk about outbound.

    Good outbound takes thinking.

    Especially now, as we’re asking AI to do more and more of the execution while we give it the direction. We’re telling it what companies to look for, what matters, who a good prospect is, how we want to sound, and what kind of message we want to send.

    So it actually matters whether the person directing the AI knows how to think through those things.

    The basics don’t change

    When we really think about it, the basics of outbound don’t really change.

    You still need to find the right company. You still need to find the right person. You still need a reason to reach out. And you still need to figure out how to actually get in front of them.

    What changes is how much of the work around outbound can now be done for us.

    What I’m doing for the next 30 days

    So what I want to do is this: I want to see what happens if I go the other way.

    For the next 30 days, I’m going to work five key accounts at a time. Although I won’t be able to tell you what accounts I chose, I will be able to give you the logic behind my decisions.

    These will be five accounts that I think are genuinely worth my time, and I’ll work them through the entire sequence. I’m going to spend more time figuring out who I should actually be talking to, why I should be talking to them now, whether I have a way into the account, and what else I can do besides just sending another email.

    If someone gives me a no, I’ll move another account in and take note.

    What I want to know is pretty simple: can I get more meaningful engagement by going much deeper on fewer accounts? Or are people just truly burnt out from all the outreach they get?

    I’ll let you know what I find.

  • A Good ICP Isn’t Enough

    When I was a kid, we took a field trip to a water filtration plant. After lunch, a guide gave us a cut-open plastic bottle and had us build our own water filters out of gravel, sand, and charcoal.

    When I was writing my last post, I was thinking about that field trip and building that filtration system. It maps surprisingly well to prospecting. I promise I’m not grasping at straws here. Hear me out. Finding the right companies and people at those companies is basically like building a filtration system.

    The gravel

    The gravel comes first because it catches all of the bigger stuff. In prospecting, those are the hard nos, the rules that immediately disqualify a potential prospect. Wrong size, wrong market, already a customer, whatever I’ve decided is a non-negotiable.

    A hard no is a no. There’s no weighing it against anything else, and nothing further down the filter can undo it.

    The sand

    Once a company passes the obvious tests, I need to know whether it’s actually a good fit.

    This is where the details matter. The economics. Who’s their customer? Are they currently using a product like the one I’m selling? And does what I actually sell make sense for their business?

    I try not to think of fit as pass or fail. That’s what the gravel does. Mine works more like weighted tiers. Some fit factors are going to carry more weight than others, but enough smaller fit factors could potentially outweigh one larger one.

    The charcoal

    And then we get to the charcoal, which is to me the most interesting part of the system.

    Gravel and sand filter by size. They physically trap whatever’s too big to pass through. Charcoal works differently. It filters by adsorption, smaller stuff actually sticks to its surface. This is my signal layer.

    What’s happening at this company that gives me a reason to talk to them right now?

    Maybe they’re hiring, maybe they’ve launched something new, maybe they’re expanding, maybe there’s a problem that’s visible from the outside. It could be job postings, customer complaints, changes happening within the business, or something else that gives me actual evidence of a problem or a reason why now.

    The three questions

    Boiled down, each layer is answering a different question:

    Gravel — Can I sell to them? Hard eligibility.

    Sand — Should I sell to them? Structural fit.

    Charcoal — Why should I talk to them now? Observable signal.

    By the time a company makes it all the way through the three layers, I don’t just have a company that fits my ICP. I have a company that passes my hard rules, that I actually know is a fit, and I actually have a reason to reach out to.

    If you don’t know what I’m talking about, read: The List Is the Problem, Not the Message

  • The Content AI Learned From

    Maybe I’m biased because I work in affiliate marketing, but the way I see it, affiliate built the incentive for publishers and creators to make a huge amount of commercial content.

    Think reviews, comparison sites, buying guides, product recommendations, tutorials — all of the things people create based on actually using, researching, or caring about something.

    Take the money out and I don’t think that content disappears. People love writing about the things they buy, their hobbies, and their experiences. But I do think, without the incentive, it would have happened a lot slower.

    Affiliate didn’t create that content as much as it set the pace for it to be created.

    It fueled and gave life to something that might have just smoldered along slowly on its own.

    And then AI shows up.

    Suddenly, there’s this massive library of years and years of reviews, recommendations, comparisons, forums, articles, videos, and niche expertise for these models to learn from and draw on.

    For the most part, it’s all content AI didn’t create. And in most cases it’s content it isn’t paying for.

    So what happens when the people creating that information decide that exchange doesn’t work for them anymore?

    Lately I’ve been seeing more publishers talk about blocking AI crawlers or putting content behind paywalls. And really, it’s not just talk anymore.

    Cloudflare already lets website owners block AI crawlers or actually set a price for them to access their content.

    Others are going the licensing route instead — essentially saying: you can use our content, but you need an agreement with us and you need to pay for it.

    So, I don’t think this means affiliate goes away — I actually think it’s more important than ever now. I also don’t necessarily think there’s going to be one new model that suddenly replaces it.

    I think we’re watching the value exchange around content change in real time.

    What I keep coming back to is the incentive.

    I’m on both sides of this. I work in affiliate marketing, and I’m also building with AI constantly.

    But somebody still has to create the information that makes it useful.

    If publishers and creators are being asked to keep producing that information while getting less traffic, fewer clicks, and potentially less money back from it, at some point you have to ask:

    What keeps the incentive going?

  • The List Is the Problem, Not the Message

    If you spend any time in the sales communities on Reddit, you start to notice the same questions repeating. Usually from someone who is new to sales.

    They have a list of a few hundred companies, a quota, and a sequence they are supposed to fill. And in one form or another, they’re asking: “who am I actually supposed to reach out to? What am I doing wrong? Pretty sure I’m getting put on a PIP –what do I do?”

    The answers they get are often overwhelming. Send more. Personalize everything. Follow up 15 times. Most of the advice is about the message and the volume and very little talks about the actual list.

    A little bit about me:

    I’ve worked in sales since I was 16 and can tell you that right now is the hardest it’s ever to been to actually sell something.

    Why?

    Inboxes are fuller, everyone has access to AI and messages all sound the same. So what do we do?

    The reframe

    Most of us, when outbound isn’t working, assume the problem is what we’re saying. So we rewrite the subject line, refine the body and add another follow-up. But the harder truth is that a lot of the people and companies in the sequence never belonged there in the first place. No message can fix a list of the wrong people.

    Hear me out. Because there’s a number that makes this concrete. At any given moment, only about one to two percent of a market is actively looking to buy. That holds across nearly every kind of B2B selling.

    Sit with that for a second. If only one or two accounts out of a hundred are ready to buy this quarter, then the list of companies your new boss just gave you is all noise. That means your job isn’t to reach everyone who could buy. It’s to find the few companies and people who fit and have a reason to move now.

    That leads to three simple questions to ask before anyone goes into a cadence.

    Question one: does the business actually have the problem?

    Most descriptions of an ideal customer are really just a description of who a rep wants to talk to. “Marketing leaders at software companies with 50 to 500 employees” is not a real target. It is a demographic. It says nothing about whether that company actually struggles with the thing you fix.

    The better test is almost too simple: can you look at a company and say, in a sentence, why they specifically have the problem you solve? If you can’t, they do not belong on the list. Not because they are the wrong size or industry, but because you have no evidence of the pain.

    Two things save you a lot of time here. First, don’t trust the filters in your prospecting tool. A company can match every box — right industry, right size, right region — and still have no real use for what you sell. Pull up their site or their product for a minute and check if what your selling would actually fit into how they already work. Second, be honest about which accounts deserve your best hours. There’s pressure to chase only the big logos, but a middle logo deals that closes this month is often what keeps your numbers alive while large deal drags across two quarters. Keep those smaller accounts nurtured with a lighter touch rather than overlooking them.

    Question two: can this person buy, or open a door to someone who can?

    The first question gets you the right company. This one gets you the right person inside it.

    New reps often stress over whether to reach out to the decision-maker or to someone lower down. The honest answer is that it depends on your goal, but it’s rarely only the decision-maker who makes a decision. I like to split my outreach between C-Suite and someone closer to the actual work – who really feels the problem. They’ll make the case for you in rooms you’ll never be invited into.

    The one person to skip is the one with no authority and no path to it. A pleasant conversation that leads nowhere is still nowhere. So the test is straightforward: this person passes if they can buy, or if they can credibly carry you toward someone who can.

    Question three: is there a reason to reach out right now?

    This is the question that most reps skip, and it’s the one that fixes reaching too wide.

    Fit tells you a company is a good match. Timing tells you they are a good match today. The strongest outreach almost always points to something happening in the prospect’s world right now. If your message could have been written a month ago, it’s already stale.

    So what counts as a reason to move now? A few of the clearest signals, strongest first:

    • A decision-maker changes jobs or gets promoted. This is the single strongest one — people rethink what they buy soon after stepping into a new role.
    • The company recently raised funding. ( Yes, everyone knows this one)
    • They are hiring for roles that point to the work you support.
    • They use a tool yours works alongside, or they are swapping tools in that stack.
    • They engaged with content, attended an event, or asked publicly about the exact problem you solve.
    • They left a critical review of a competitor, on the weakness you happen to be better at.

    You do not need all of these. You need one, and it needs to be current.

    The whole thing on a sticky note

    Before anyone goes into a cadence, they should clear all three: the business has the problem, the person can buy or open a door, and there is a reason to reach out now.

    And for everyone who does not clear all three, the answer is not “delete.” It is usually “wait.” A good-fit account with the right person but no trigger yet doesn’t get a sequence; it gets patience, and your attention the moment something changes. Most sales are made on the follow-up, when a good fit finally meets a real need.

    It feels backward, but the reps with the steadiest pipeline are usually sending less, not more. A smaller list of the right people, reached at the right moment, beats a giant list of the wrong ones every time.

    Why I wanted to write this down

    I’m writing this down for the person on Reddit with three thousand accounts and no idea where to start. When I began, no one handed me a simple way to decide who was worth the effort.

    Qualify hard. Be patient with the rest. And put your best hours into the few who have actually earned them.

  • A Professional Skateboarder in Tech Sales

    For most of my life, the clearest way to explain who I was involved a skateboard.

    I started skating when I was young, and in 2022, after roughly twenty years of working toward it, I became a professional skateboarder for There Skateboards – the first queer-owned skateboarding company.

    But skateboarding has never been the only work I have done.

    I’ve also worked in sales since I was 16. Building a sustainable career in skateboarding is difficult, so for most of my life, sales and skating have existed alongside each other. Sales gave me the financial stability and flexibility to continue pursuing skateboarding. What I enjoyed most is that I didn’t have to leave one career behind to begin another. I could build both at the same time.

    Have you noticed?

    People can become uncomfortable when someone changes or begins exploring something outside the identity they are known for. There can be an expectation that once you become recognized for one thing, you should continue presenting yourself in that same way.

    If anything, each part of my career has made the others possible.

    Skateboarding taught me how to work toward something without knowing exactly when, or whether, it would pay off. It taught me how to repeat the same motion hundreds of times, study what went wrong, make small adjustments, and keep trying. Sales taught me how to understand people, communicate value, create opportunities, and navigate industries where success is rarely guaranteed.

    More recently, those skills have led me toward artificial intelligence.

    Over the last several months, I have been spending my days working in technology sales and my nights building with AI. I’ve experimented with AI agents, outbound research systems, data aggregation workflows, and a trading bot built with Claude Code. Some of these projects work. Some work only under the right conditions. Others have shown me how wide the gap still is between an impressive AI demonstration and a dependable system someone can actually use.

    I’m not an engineer, and I am not pretending to be one. I am a salesperson learning how to build because I believe the people selling AI should understand more than its talking points. They should understand what it feels like to turn an idea into a workflow, connect different tools, work through unreliable outputs, and decide which parts of a process should be handled by software and which still require a person.

    At the same time, I have also been thinking differently about what it means to be a professional skateboarder.

    Professional skateboarding can sometimes become centered on the individual: what sponsors you have, what opportunities you receive, what footage you produce, and what the industry can give you. I understand why. It is an incredibly difficult career to build, and the opportunities are limited.

    But I am at a point where I am thinking more about what I can give back to the community that made me who I am.

    Skateboarding gave me, friendships, confidence, and a way of understanding the world. Being part of There Skateboards has also shown me the importance of creating space for people who have historically been overlooked or made to feel that skateboarding was not built for them.

    I want the next stage of my career to include more than what I can personally accomplish. I want to use the relationships, business experience, technology, and opportunities I have gained to help create access for other people.

    That is part of what I want this site to document.

    Some posts will explore AI, sales, my ideas, and the future of work. Others will show systems I am building, including what worked, what failed, and what I still haven’t figured out. I also want to write about skateboarding, representation, and how I am contributing to the community that gave me so much.

    These subjects may appear unrelated from the outside. To me, they are connected by the same questions.

    How do people create opportunities when a traditional path does not exist? How can technology give someone more leverage? What systems allow people to participate, earn, and build sustainable careers? And once you have created opportunities for yourself, how can you make it easier for someone else to do the same?

    Hello, and welcome to the journey.