Using Data Analytics in Sales

Demand Capture 101. This is actual data from a $60MM ARR SaaS company. Let’s break it down 👇   How a lead/account enters your pipeline is the biggest predictor of sales velocity metrics - win rates, sales cycle lengths, even ACVs.    Because how they enter your pipeline is a surrogate for buying intent & indicator of how far they are complete in the buying process.    Here’s how to measure it & use it to drive your revenue strategy:   1. Measure the Opportunity Source in Salesforce on the opportunity record.    Campaign Source = What campaign type did they convert on to move this opportunity into pipeline? (e.g. demo request, e-book download, cold call, trade show, etc.)   Source / Channel = What source or channel did they come from in order to convert? (e.g. LinkedIn ad, organic search, account intent data, ZoomInfo, etc.)    Using both of these data points combined will literally guide your strategy.    This shows you the optimal paths to *capture demand* and is easily measurable using software-based attribution.   2. Separate conversion sources between *Declared Intent* and *Low Intent*.    Declared Intent = The buyer declares intent to buy from you (e.g. Demo Request, Contact Sales) Low Intent = You assume the buyer has intent based on their digital behavior (e.g. ebook download, webinar attendee, trade show badge scan, intent data, etc.)    3. Calculate core sales analytics between the two sources.    Calculate conversion rates, lead-to-win rate, net new ARR, sales velocity, and more.    4. Visualize how much conversion intent matters to sales velocity and sales productivity.    149X higher lead-to-win rates for declared intent conversions   Declared intent = 26 “leads” to win 1 deal for $54k ARR Low Intent = 3,868 “leads” to win 1 deal for $130k ARR   18X greater sales velocity for declared intent conversions   Declared intent = $14.2MM annual sales velocity Low intent = $781k annual sales velocity 5. Recognize not all MQLs are created equal Measuring on MQLs incentivizes teams to get the most volume of MQLs for the lowest cost (low intent conversions), which is entirely misaligned with sales productivity and sales goals. Separate these into two Pipeline Sources (Declared Intent, Low Intent). Plan and build your goals for these two sources separately.   __   Now you know exactly HOW you want buyers to enter pipeline (capture demand) for maximum sales velocity & sales team efficiency. You also know exactly WHY buyers choose to take those paths to enter pipeline & WHAT triggers / channels / tactics move them to conversion. And with all of these insights, you can re-architect your strategy that optimizes for REVENUE. #revenue #sales #marketing #b2b #gtm p.s. Every SaaS company’s data looks like this, because it’s universal to how buyers buy. Most just don’t take the 3 hours of time to analyze their own data and see it for themselves.

I met a sales team that tracks 27 different metrics. But none of them matter. They measure: - Calls made - Emails sent - Meetings booked - Demos delivered - Talk-to-listen ratio - Response time - Pipeline coverage But they all miss the most important number: How often prospects share your content with others. This hit me yesterday. We analyzed our last 200 deals: Won deals: Champion shared content with 5+ stakeholders Lost deals: Champion shared with fewer than 2 people It wasn't about our: - Product demos - Discovery questions - Pricing strategy - Negotiation skills It was about whether our champion could effectively sell for us. Think about your current pipeline: Do you know how many people have seen your proposal? Do you know which slides your champion shared internally? Do you know who viewed your pricing? Most sales leaders have no idea. They're optimizing metrics that don't drive decisions. Look at your CRM right now. I bet it tracks: ✅ When YOU last emailed a prospect ❌ When THEY last shared your content ✅ How many calls YOU made ❌ How many stakeholders viewed your materials ✅ When YOU sent a proposal ❌ How much time they spent reviewing it We've built dashboards to measure everything except what actually matters. The real sales metric that predicts closed deals: Internal Sharing Velocity (ISV) How quickly and widely your champion distributes your content to other stakeholders. High ISV = Deals close Low ISV = Deals stall We completely rebuilt our sales process around this insight: - Redesigned all content to be shareable, not just readable - Created spaces where champions could easily distribute information - Built analytics to measure exactly who engaged with what - Trained reps to optimize for sharing, not for responses Result? Win rates up 35%. Sales cycles shortened by 42%. Forecasting accuracy improved by 60%. Stop obsessing over your activity metrics. Start measuring how effectively your champions sell for you. If your CRM can't tell you how often your content is shared internally, you're operating in the dark. And that's why your forecasts are always wrong. Your move.

Five years ago, Warburg Pincus LLC invested in BetterCloud and urged us to work on a project to narrow our ideal customer profile (ICP). It's the most impactful thing I've ever done to improve conversion rates, shorten sales cycles, increase deal size and ultimately transform the company. A big mistake many CEOs make is believing their product is for everyone. It’s tempting. More potential customers should mean more sales, right? But in reality, chasing too broad a market drains resources, distracts your team, muddles messaging, confuses your product roadmap, and kills go-to-market efficiency. Being laser-focused on your ICP drives alignment across product, messaging, and the go-to-market motion. When the right prospect engages, they’ll feel like you built it just for them. Anyone who has built a product or service knows that the things a small business needs are very different than what a huge enterprise needs. A company is different from a school. An IT buyer is different from a security buyer, a sales buyer is different from a marketing buyer, a director level decision maker is different than a C level decision maker… but we still believe we can sell to different segments and personas as the same time. The process to define and use your ICP is relatively straightforward but does take time. The larger your business, the more data you have, the more resources you have to crunch that data the more time you should spend to do it as scientifically as possible. The high level steps are: 1. Build a Customer Dataset: Gather all your customer data. Current and churned customers, won and lost opportunities. Enrich it with firmographic, business-specific, and buyer demographic data. 2. Engage Your Team: Your best sales and customer success people hold invaluable insights about your most successful (and worst) customers. 3. Analyze & Identify Pockets of Gold: Identify common attributes of high-performing accounts and avoid the traps of poor-fit customers. 4. Communicate the ICP to the entire company with the “why” behind the attributes that make up an ideal customer.  5. Rework your messaging to appeal to your newly defined ICP and narrow your growth initiatives to be focused only on the accounts that matter.  6. Assign the right ICP accounts to your reps and ensure they’re focused on the right buyer personas. 7. Product Development: Reassess your roadmap to align with the needs of your ICP. You should see impact fast. GTM funnel metrics will improve. Conversion rates should rise, with better leads turning into stronger opportunities. You may not get more leads, but their quality will increase. I’ve been discussing this with many Not Another CEO Podcast guests, so don’t just take my word for it. I wrote a deep dive on how to “Narrow Your ICP and Transform your Company”, with real examples from other companies. You can read the full article here https://lnkd.in/e5EN3XSR

Every frontline seller should set up two reports that they look at every month 1. Average age in each stage - forget your “sales cycle” you need to break it down to see where you can speed it up at each stage 2. Conversion rate from stage to stage - forget your close rate, it’s about can I get 8% getting people from step 2 to step 3 Anecdotally…you might have an idea but it’s tough to feel a 5% gap or 3-4 days here or there Everyone loves to focus on the activity or pipeline metrics but if you want to actually close more deals….you need to know these numbers inside and out If you aren’t looking at this, now is the time and see how you stack up to your peers as well. This data is eye opening when we show leaders it for the first time as they think they are tracking what they should when they say “we have a 60 day sales cycle” When you zoom into that nice, straight line showing the average sales cycle across the team month over month….you will see it looks less like a straight line and more like a lie detector test at the rep level😆 Track this Review it regularly Get 5% better in the first month

Generative AI surveys: where your feedback is interactive, valued, and promptly discarded. But hey, at least it’s efficient! Sorry, I know it’s a bit early to be snarky. Seriously though, closing the loop with your customers on their feedback - solicited or unsolicited - is a game changer. Start by integrating customer signals/data into a real-time analytics platform that not only surfaces key themes, but also flags specific issues requiring follow-up. This is no longer advanced tech. From there, create a workflow that assigns ownership for addressing the feedback, tracks resolution progress, and measures outcomes over time. With most tech having APIs for your CRM, also not a huge lift to set up. By linking feedback directly to improvement efforts, which still requires a human in the loop, and closing the loop by notifying customers when changes are made, you transform a simple data collection tool into a continuous improvement engine. Most companies are not taking these critical few steps though. Does it take time, effort, and money? Yes it does. Can it help you drive down costs and drive up revenue? Also, a hard yes. The beauty of actually closing the loop is that the outcomes can be quantified. How have you seen closing the loop - outer, inner, or both - impact your business? #cx #surveys #ceo

If you are writing sales messaging that could apply to anybody in your TAM, you're writing sales copy that nobody gives AF about. OUCH! I know that might be hard to hear, but here's the hack to better segment your TAM in 2025. ➡️ The harsh truth is that Founders who take a "boil the ocean" approach to selling in will fail. Here's how you can get better results in 3 steps: Step 1 - Move your focus from everybody who *could* possibly buy from you to the group of folks who are most likely to buy now, buy at a high price point, and later renew or be a referral source. Step 2 - From that much smaller group of accounts, create segments. These are not the traditional segments that help your organize your territories. These are segments that help you speak the language of a deep sub-set of prospects. I suggest at least 5 layers of segmentation blending firmographic data, signals, and contact-level data. EXAMPLE: You sell production line automation software. You believe your ICP is: US-based supply chain executives in manufacturing organizations with at least 1k employees. Great start, but it's time to add 5+ layers of segmentation before you can create a message that matters. Segment 1: Midwest "Manufacturing Belt" only Segment 2: Chief Supply Chain Officers only Segment 3: Machinery manufacturing only Segment 4: 50,000 to 100,000 employees Segment 5: New CFO hired in the past year Now you are only speaking to the CSCO or a sub-industry working in the region where you have the strongest social proof. By tightening the employee range you know they have a big enough problem to solve (+ can pick the best name drops) and a new CFO signals an openness to (re)explore cost-saving software. Step 3 - Use this process to launch dozens of micro-campaigns that speak to specific sub-sets of your territory because you've created enough segmentation to be 99% sure your copy will be RELEVANT to them. This is THE only way I've found to personalize at scale. I love teaching orgs how to better segment their accounts and create segment-specific value props. I call it #ValueBasedSegmentation ➡️ The result is: - Highly relevant copy - Emails that can be fully automated - High CTRs/replies without tedious personalization 📌 How do you personalize at scale?

Results = activity x effectiveness. How do you measure activity or effectiveness in a large sales organization? Starting this month, Outreach sellers, managers, and admins will have full analytics of their entire sales funnel - from initial outbound to revenue booked. This means understanding how sales activity converts to conversations with prospects, how conversations convert to meetings booked, how meetings convert to pipeline created, and how pipeline converts to revenue. TL;DR: this report gives you a 360° view of sales Activity and Effectiveness. You can use this report to: 1. Use data to identify specific points of bottleneck in the sales process for more targeted improvements - whether it's building lead nurturing automation, improving follow-up processes, or refining sales messaging. 2. Set more realistic goals by leveraging your own historical data, conversion rates, and rates of improvement. 3. Understand where to allocate more resources (ex: orgs that struggle to convert meetings to pipeline may benefit from additional enablement on how to hold effective demos and discovery calls). 4. Coach more effectively by comparing metrics between various teams and individual reps to scale the winning strategies of your top reps. This report is a major gap in the Sales Engagement ecosystem and I can't wait for our customers to see it live in their platforms! If you want to learn more, I'll link our May Product webinar in the comments below 👇

"Let's just divide accounts evenly among reps." Famous last words from every sales leader who's never done territory math. Six months later: Rep A closes $800K, Rep B closes $200K. Same quota. Same comp plan. Different territories. Folks - territory planning isn't about fairness. It's about math. Here's the formula to always keep in mind: Territory Value = (Account Potential x Win Probability x Coverage Capacity) - Competitive Density. So, how do you apply the formula? Let's bust out our TI-82s and break this down... Step 1: Calculate the true account potential. Don't use company size alone. Use buying indicators: - Recent funding rounds (+50% potential). - Executive hiring sprees (+30% potential). - Tech modernization projects (+40% potential). Example: 500-employee company = $50K base potential + $10M Series B = $75K total. Step 2: Determine the win probability by account type. - Green field (no solution): 25-30% win rate, 4-6 month cycle. - Competitive displacement: 15-20% win rate, 6-9 month cycle. - Expansion accounts: 60-75% win rate, 2-4 month cycle. Step 3: Eval the coverage capacity reality. Each rep can effectively work: - 25-30 ENT accounts (15-20 hours/month each). - 50-75 MM accounts (8-12 hours/month each). - 100-150 SMB accounts (3-5 hours/month each). Step 4: Inspect geographic efficiency. - Dense metro: 8-10 meetings/week (1.0x capacity). - Regional spread: 4-6 meetings/week (0.75x capacity). - National territory: 3-4 meetings/week (0.6x capacity). Step 5: Measure the competitive density tax. - Low competition: +20-30% win rates. - Saturated markets: -25-35% win rates. Here's an example of how to score territories: 1. Territory A: 40 enterprise accounts x $90K potential x 25% win rate x 0.8 geography x 0.9 competition = $648K. 2. Territory B: 60 mid-market accounts x $35K potential x 35% win rate x 1.0 geography x 1.1 competition = $809K. As you'll see, territory B wins despite LOWER account values. Once you've run the math, don't treat all accounts equally. Allocate effort thusly: - Tier 1 (20% accounts, 60% revenue): Weekly touches, exec relationships. - Tier 2 (30% accounts, 30% revenue): Bi-weekly touches, manager relationships. - Tier 3 (50% accounts, 10% revenue): Monthly touches, inside sales. At the end of the day, good territory planning is applied mathematics, not office politics. Equal doesn't mean fair when account potential varies 10x. Run the math. Weight the factors. Track the results. Because the rep with the better territory will always outperform the rep with more accounts. Remember that math doesn't lie, but territory assignments definitely do. :)

55% of sales leaders witnessed increased lead conversions with intent data, a stat that marks a new era in the art of sales and marketing. 🔍 A Personal Tale: From Data Jungle to Targeted Strategy 🔍 I once partnered with a client who was overwhelmed by a deluge of intent data from Bombora. Picture navigating a dense jungle without a map. The data was vast but unstructured, not effectively mapped to accounts. I was reminded of Craig Rosenberg's words - "The key on intent is fit comes first." 💡 Turning Complexity into Clarity: The Role of Context Our quest was clear: to cut through this jungle and find a path. We initiated a meticulous cleanup, aligning intent data with specific accounts. Then, we took a pivotal step further by focusing on contextual intent data. 🧭 Unlocking the ‘Why’ Behind the Data Contextual intent data is like a compass in uncharted territory. It goes beyond identifying interested accounts; it's about grasping the reasons behind their interest. This deeper understanding enabled us to tailor our approach, addressing the specific needs and challenges of each account. 🌈 The Outcome: Precision-Driven Sales and Marketing Success The transformation was remarkable. Sales dialogues became more focused and resonant. Marketing campaigns struck a chord, addressing the unique context of each account's journey. 🛤️ A 5-Step Blueprint to Mastering Contextual Intent Data Data Harvesting: Collect intent data with an eye for the underlying context of each interaction. Intelligent Mapping: Align this data with specific accounts, illuminating your path through the data forest. Tailored Tactics: Customize your outreach based on the nuanced context of each segment. Adaptive Campaigns: Launch dynamic, context-sensitive campaigns that connect deeply with each account's narrative. Strategic Refinement: Continuously evolve your strategies, responding to the ever-shifting landscape of intent signals and contexts. 📈 Beyond Just Data Points: Contextual intent data isn't merely a collection of information; it's a storytelling tool. It's about transforming raw data into compelling narratives that not only reveal who is ready to buy but also why they are on this journey, creating more meaningful and effective sales and marketing engagements. Step into the world of contextual intent data and watch your sales and marketing narratives change from abstract data points to stories that connect and convert. #ContextualIntentData #SalesInnovation #MarketingTransformation #DataDrivenDecisions #BusinessGrowth #B2Bmarketing #ABM #accountbasedmarketing #METABRAND #IndustryAtom

my competitor and i launched identical linkedin campaigns. same budget, same audience, same product category. i crushed him 8:1 on deal conversion. he was confident going into the test. better product. stronger brand recognition. more funding. bigger team. we both targeted VPs of sales at 500+ person companies. same demographic criteria. same ad creative quality. $10K budget each. month one results: me: 47 deals closed. him: 6 deals closed. he was convinced i got lucky with better prospects. "let me see your targeting strategy," he asked. i pulled up my dashboard. "i don't target demographics at all." "what do you mean? you're running linkedin ads." "i target behaviors." i showed him my approach: instead of job titles, i track content consumption. instead of company size, i monitor website journeys. instead of industry filters, i watch engagement patterns. "i built an audience of people who've consumed competitor content in the last 30 days. downloaded sales automation guides. attended webinars about pipeline management. visited pricing pages of tools like ours." my "audience" wasn't demographic. it was behavioral. "linkedin lets you upload custom audiences," i explained. "i upload lists of people who've shown buying behavior. then i target those lists with ads." he was targeting people who might need our product. i was targeting people actively shopping for our product. "how do you identify buying behavior?" he asked. "third-party intent data. website pixel tracking. content engagement scoring. competitor analysis tools." i showed him my process: week 1: identify companies researching sales tools. week 2: find individuals at those companies consuming content. week 3: build custom audiences from behavioral data. week 4: launch ads to pre-qualified prospects. "demographics tell you who someone is," i said. "behavior tells you what they're doing." he was advertising to VPs of sales. i was advertising to VPs of sales currently shopping for solutions. same title, completely different mindset. my prospects were already in buying mode. his were just scrolling linkedin. the conversion difference made perfect sense. he rebuilt his entire approach: behavioral targeting instead of demographic filtering. intent data instead of job title assumptions. shopping behavior instead of profile characteristics. next month's results for him: 52 deals closed. 9x improvement over his original campaign. the lesson was clear: demographics describe who people are. behavior reveals what people need. target the behavior.