HireDNA’s Post

Spending time hiring Vs. Spending time on your team Of course it can be both. But join me on this journey for a second. 👇 In the golden age of SaaS growth equaled hiring extra headcount. We all know hiring takes a lot of time. (Think: HR, conducting interviews, onboarding) WHAT IF you spend that time working with your team on Tiny Gains throughout the buyer journey/sales process? You could potentially enjoy the fruits of the compound effect. Join me walking through the following scenario: 𝗧𝗵𝗲 𝗣𝗼𝘄𝗲𝗿 𝗼𝗳 𝗧𝗶𝗻𝘆 𝗚𝗮𝗶𝗻𝘀 🚀 - Initial Scenario: Our journey starts with 100 leads. - ACV: Steady at €15,000. 𝗕𝗮𝘀𝗲𝗹𝗶𝗻𝗲 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 𝗥𝗮𝘁𝗲𝘀: - Lead to SQL: 20% - SQL to Opportunity: 30% - Opportunity to Win: 25% - Resulting Revenue from 100 Leads: €22,500 𝗔𝗱𝗷𝘂𝘀𝘁𝗲𝗱 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 𝗥𝗮𝘁𝗲𝘀 (𝗮𝗳𝘁𝗲𝗿 𝗧𝗶𝗻𝘆 𝗚𝗮𝗶𝗻𝘀): - Lead to SQL: Improved to 22% (+2%) - SQL to Opportunity: Boosted to 33% (+3%) - Opportunity to Win: Elevated to 28% (+3%) - Resulting Revenue from 100 Leads: €30,600 𝗜𝗺𝗽𝗮𝗰𝘁 𝗮𝗻𝗮𝗹𝘆𝘀𝗶𝘀: Revenue growth: Transitioning from €22,500 to €30,600. Growth percentage: A 36% increase in revenue! 🚀 𝗛𝗼𝘄 𝗱𝗶𝗱 𝘁𝗵𝗶𝘀 𝗛𝗮𝗽𝗽𝗲𝗻? The magic lies in the compound effect of improvements at each funnel stage. So of course, hiring can still be a good plan. Just don't neglect continues improvement. What are you doing to enjoy the power of tiny gains? Need help or want to chat? Send me a DM. #sales #salescoaching #salesenablement #salesdevelopment #revenueenablement

I was asked in a recent #b2boring live event, what is the difference between #intentdata and signal data? The answer in the cases where intent data companies just changed their language to signals is nothing, but there is an emerging ecosystem of companies offering "signals" so I thought I would expand here. From my vantage point, there are three types of predictive/indicative data sets in the #b2bmarketing space Trigger data - Commonly referred to as signals, these triggers are usually moments in time scooped from publicly available sources that may increase your chances to hook a meeting. Examples - Hiring a lot of sales reps on LI, a new CEO, a positive earnings call, onboarding a new technology, recent layoffs, etc. This event data isn't necessarily a signal, but a trigger that something might be brewing. Valuable, but generally assumptive - and a lot of false positives. Intent Data - tale as old as time. This data is derived from generic website consumption data. Whether through a data cooperative, or bidstream manipulation, this data tracks which companies are on which random website based on website keyword analysis. I think we can all agree, ready a website about "10 trends in HR" doesn't indicate any interest in purchasing HR Software. This is the data set that has given a lot of B2B revenue teams a poor impression of predictive data. Signal Data - This data signals a company's interest in purchasing a software/services of technology. Mostly content consumption derived, the key differentiation here is what content is being consumed - as not all content is created equal. Vendor comparison reports, Product buying checklists, engagement with product review sites, this engagement is far more predictive than simple intent data. The difference is propensity to purchase, vs propensity to learn. Lots of confusion right now in this space, and lots of skepticism (rightfully so). Make sure you dive in deep into the question that matter when evaluating predictive data. Do they buy their data from another source? Does that source sell its data to other vendors? Is the data intent to purchase, or simple intent to learn? Can the vendor create custom audiences, built specifically for your company?

We have 3 new revenue roles! People Data Labs is coming off of an all time record breaking Q2 and H1. That’s particularly exciting for three reasons: 1. The majority of our revenue team has been hired in the last two years, with a strong anchor of employees who are 3-4+ years in at PDL. 80% of our sales team was hired in 2023 and 2024, with half of the team hired between Feb-April of this year. 2. Historically we’ve referred to ourselves as an “H2 business.” In our early days we had very lopsided years. As we’ve pushed for consistency in performance we’ve seen that significantly even out and H2 will no longer need to balance out the year. 3. We did all of this while also achieving profitability earlier this year. Meaning we broke several records while arguably spending upwards of 30% less annually to do it. None of this would be possible without the myriad of teams at PDL, but our sales team in particular had a standout performance. The Q2 numbers: - Our sales team hit 138% of quota, to drive momentum we lowered quotas for a portion of the team, even with the original quotas we would’ve hit 125% of quota - Of our 5 tenured reps, 5 were above $400K, 3 were above $500k, and one was above $600K - Our 2024 new hires closed $500K collectively, 99% of their team quota This hasn’t been easy, pivoting to a focus on profitability in late 2022 required tough cuts to get our burn under control, and record breaking performance only matters if you can back it up in the following quarters. Deep appreciation for everyone on the team who worked hard to make this happen, and a special thanks to Craft Ventures for being such a consistent source of support as we pursued a new growth path. We’ve learned our lesson and we will continue to be protective of our burn, which includes high standards around green-lighting new roles. You’ll notice that we are not making any additional sales hires, we want to see that team with overflowing pipeline before we add more AEs. We have 3 roles: - RevOps Manager - Inbound SDR - Marketing Generalist - Build Your Role/Title with Us Navigating profitability and growth is a high bar and it takes a certain type of mindset. For anyone interested, think about how you are breaking through the noise. Even as a smaller company we are seeing 100+ applicants within 24 hours of a job post. For the Marketing Generalist role, we had so much fun putting this together. We mean it when we say it, we want this person to design their dream role with us. Data as a Service (DaaS) just doesn’t have the typical playbooks and we are looking for someone excited by that challenge. We love creativity, surprise us! Zach Hallett is the recruiter for all three roles, Lindsay Warren is the HM for the Marketing and SDR roles, and Brooke Threewitt is the HM for the RevOps role. Comments for reach, tags to alert great candidates, and reshares are sincerely appreciated. We also have a number of engineering roles open. Link in the comments!

Lets say you're a rep at a small startup with a huge TAM. How do you prioritize who to reach out to? For me it's Clay. When I get a new list, I pop all the accounts into a table and analyze which ones look good based on some demographics and triggers. Things like: • Job openings • YoY Growth stats • Mergers and Acquisitions I also have portions of the table that return LinkedIn profiles for my ICP - specifically Network Engineers and IT directors. This allows me to make logical decisions about who I will prioritize my outreach to instead of just hoping I'm prospecting into an account that's ready to buy. I talked to a rep the other day who had 12,000 accounts in the SMB space. If I were them, I'd make a Salesforce report of top 50 companies by ARR, export the CSV, and upload it into this table to get data on the company and surface possible triggers. Most of the data I have surfaced on this table is stuff any ENT rep should know about their BoB. Some of it is only applicable to me, but is a great starting point for someone who wants to be more strategic in their outreach. Other things I'm planning on adding to this table in the long run: • AI email copy • Surfacing when a senior IT leader is hired • AI analysis of 10ks - fed to another table, hence why I have the Gsheet function in there. • Headcount growth by role or department Anything else you guys think would be helpful in tracking triggers on a table like this? Link to my table template - https://lnkd.in/eBkX2UVq Curious about Clay? Sign up here - https://lnkd.in/e8qZkR-k #sales #outbound #sdr  

Most Founders and SDRs think intent = job listings. Here’s why that’s dead wrong: In a perfect world, we’d have access to the scalability of cold email, along with knowledge of each prospect’s situation in-depth like we’d spent days researching their situation. So most sales teams decide to go after job listings of companies in their ICP to determine prospect intent. Problem is, job data is: 1. Unreliable 2. Not scalable when researched manually 3. Being looked at by every SDR and their mother. If you want to be a true Data Sniper™, you need to be able to connect multiple data points to get a crystal clear sense of each prospect’s situation, and where they want to be. Truth be told, job listings can be part of a balanced diet of measuring prospect intent. But when you and every other SDR on the planet use it to construct cold emails, you end up drowning in the sea of spam in your prospects’ inbox. Instead, do this: Take your lead list and go one-by-one pulling data from a few sources – this could be their technology used, reviews, blog posts, etc. When you have a few data points, combined with the job data you gathered earlier, you have a much clearer picture of their current situation. I’ll admit, this is hard :( It requires you to: 1. Know what data you’re looking for, for each lead in your list 2. Know where to get that data 3. Do it on a list of 10k+ leads without hiring a massive sales team That’s why we built internal tools to accomplish this exact goal, and how we’re able to… Click a button → Do in-depth research on 10k leads → Predictably get 28% positive reply rates on our outbound campaigns. Check out Sparkscalingsolutions.com for a free explainer on how you can do the exact same for your B2B company :) #salesdevelopment #coldemail #digitalmarketing

Navigating the Job Market: A Frustrating Reality The job market is tougher than ever, and one thing I’ve noticed is how often job listings aren’t transparent about key requirements. You take the time to click on a promising role, only to find out later you’re not in the preferred region or don’t qualify based on factors that could’ve been stated upfront. Hiring teams, please be clear from the start! It saves everyone time and energy. If you’re looking for skilled professionals, I’m available and ready to make an impact. With expertise in digital marketing, data analytics, and client relations, I’m confident I can bring value to your team. Let’s connect—hire me! #JobHunt #RemoteWork #HireMe #MarketingExpert #Salesforce #CRM

Using intent data/trigger events to your prospecting (outbound motion) will 3x the success of it. By nature, outbound has a lower success rate than inbound or referrals. But it's also easier and faster to get started. But instead of doing 'cold' outbound, you should use intent data to make it only 'semi cold'. Intent data (trigger) are a proxy/indicator that they will face the issue/problem you are going to solve for them. When you combine intent data with my TAPSA framework you will see good results. You connect trigger events with a correlated (assumed) pain. Here are a few of the intent data: 🔸new hires 🔸change in leadership positions 🔸promotion/new role of persona 🔸Headcount changes (growth or decline) 🔸Open job postings/ads 🔸Revenue growth (or decline) 🔸Funding events 🔸 M&A activity (Mergers & Acquisitions) 🔸 Press, media & news about the company 🔸 Bad/good reviews: 🔸 New Product/Feature launched (e.g. on Producthunt, Company Blog, Helpcenter...) 🔸 software/tools they are using 🔸 offered integrations (e.g. Zapier, Salesforce, Notion, etc.) and much more You will find the TAPSA framework and all intent data in the link below.

Here is how you can build a fully automated outbound system in just 6 steps. Outbound can be very time-consuming but there are a lot of things that can be automated in 2024 by leveraging the right tools. At ColdIQ we have built many automated outbound systems for clients. Once we start working with clients we are always looking at what are the relevant triggers for their business. To explain what is a relevant trigger, I often ask “What is a data point we can monitor that usually indicates that a prospect is in the market for your product/solution?” The trigger that is relevant for most companies and that generates the most volume is often the “Open jobs” trigger. Here is a 6-step blueprint to build a complete system based on hiring trigger: 1. Identify Open Jobs - Use Apify to get open jobs data from LinkedIn, Greenhouse, and Indeed (or LeadsOtter to aggregate all the job platforms). 2. Find the companies behind the job offer and the contacts to reach out to using the LinkedIn enrichment on Clay. 3. Enrich Data - Leverage multiple data sources with Clay. 4. Check Data Quality - Validate the quality of your data using tools like Prospeo, DeBounce, and Enrow. 5. Personalize Outreach - Use the API keys from Anthropic or OpenAI to add some personalization to your sequence. 6. Send the Emails - Use Smartlead (the best email sequencer) to rotate between your different mailboxes and run your campaigns. Following this blueprint allows you to have an automated prospection machine generating opportunities without adding new leads manually. Curious to hear if you have already automated some part of your outbound process?

I am a Data Entry and Lead Generation Specialist skilled in managing and processing data accurately while identifying and cultivating potential clients for businesses. My expertise includes data analysis, market research, and strategic outreach, ensuring high-quality leads and efficient data management to drive sales growth and business development. #dataentry #entrydata #dataentryjobs #b2b #leadgeneration #lead #generation #generations #b2bmarketing #b2bleadgeneration #leadsgeneration #generation1

For this “Chq this Out", I want to dive into Revenue Intelligence. This week, Clari, a top platform in Revenue Intelligence, announced they'd hit $4 trillion in revenue under management. Crazy, right? So, how does this relate to Talent Acquisition? It's a common belief that HR/TA falls behind Sales/Revenue teams in tech innovation and budget. That's why this caught my eye. When I think about Salesforce's journey from early CRM days to dominating cloud SaaS, it's no wonder a company like Clari, solely focused on Revenue Intelligence, can reach such heights on SF’s back. It got me thinking… This year in the US alone, companies will hire over 60 million people and will write job offers totaling over $3.5 trillion. And from the perspective of a revenue platform like Clari, our talent teams will manage pipelines of over $50 trillion. Wrap your head around that for a moment. And to ground this even further, think about it this way. If I oversee a team hiring 500 people annually at $100k salary each, I'm handling a talent pipeline worth $800 million and closing a $50 million hiring plan. Scale that up to hiring 5,000 or 50,000 folks, and the numbers hit the billions quickly. So here is my thought. Maybe our industry needs to start adopting metrics like our peers in the revenue space, like $$$ under management. This would help shine a brighter light on how critical the work of recruiting is and help move closer to getting TA teams the strategic seat at the table (and budgets) they deserve. Am I crazy or is it time to rally around the Trillion $$$ Under Management idea for TA and recruiting? #hiringintelligence #qualityofhire #recruitinganalytics