Using Data Analytics in Sales

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

Power BI for Sales Performance Analysis Boosting Sales with Power BI: A Real-Life Success Story   Scenario: Challenge: Our sales team struggled with tracking performance metrics across different regions and product lines. The data was scattered across various sources, making it difficult to get a unified view.   Solution: We implemented Power BI to consolidate sales data from CRM, ERP, and other systems into a single, interactive dashboard.   Steps: 1. Data Integration:    Used Power BI's built-in connectors to pull data from multiple sources.   Example Query:     let         SalesData = Sql.Database("ServerName", "DatabaseName", [Query="SELECT * FROM Sales"])     in         SalesData     2. Data Modeling:   Created relationships between tables to allow for comprehensive analysis.   Example: Linked sales data with regional data to analyze performance by region.   3. Interactive Dashboards:   Designed dashboards to track key metrics like total sales, sales growth, and regional performance.   Features: Drill-down capabilities, slicers for filtering by date, product, and region.   Impact: Improved Visibility: Sales managers now have a clear, real-time view of performance metrics. Faster Decisions: Quick access to data enabled faster decision-making and strategy adjustments. Increased Sales: Identified high-performing regions and focused efforts on underperforming areas, resulting in a 15% sales increase.     Include screenshots of the Power BI dashboard, before-and-after performance metrics, and user testimonials. Have you used Power BI to transform your sales performance? Share your story in the comments!   #PowerBI #Sales #DataVisualization #BusinessIntelligence #TechInnovation #DataDriven

A Marketer's dream: Contact-Level Intent for Ads! LinkedIn Ads & Meta Ads live in Warmly. Most B2B companies burn half their ad budget on people who'll never convert. Customers, open opps, competitors, interns. Non-ICP contacts that get served ads, and stay in ad audiences. Ad platforms' native filters are too broad. So teams pull CRM lists, clean them, upload them manually, and watch them go stale in 48 hours. There are 3 motions for ad campaigns: 1/ PASSIVE: Triggers based on signals (visitors, intent surges, job changes) 2/ ACTIVE: push specific companies/contacts for a campaign (ABM, competitor sunsets) 3/ EVERGREEN: always-on ICP coverage (TAM, personas, lookalikes) Almost nobody runs all three well. The data plumbing is brutal. And then there's attribution. A prospect clicks your ad, hits your site, bounces, and comes back tomorrow to book the meeting. The ad gets zero credit. You attribute the meeting to "direct" or "organic" and assume your ads aren't working. They were. You just couldn't see it. The result: 60% of B2B ad spend hits people who can't or won't buy. And the ones who DO convert, you can't tie back to the campaign. Warmly's integration fixes both. It collapses the three motions into one intelligence and execution layer. And because we identify the visitor on your site as the same person who clicked the ad, you can tie LinkedIn and Meta campaigns directly to pipeline and closed-won, even a week later. PASSIVE (signal-triggered, always on): - ICP buyer hits /pricing twice → retargeting audience - Form abandon at /book-a-demo → gifting campaign with a LinkedIn DM - Bombora research surge on a non-customer → awareness audience ACTIVE (campaign-driven, initiative-led): - Competitor just sunset → bulk push every competitor user to a LinkedIn + Meta matched audience - ICP TAM minus customers and open opps → ABM blast across LinkedIn + Meta - Closed-lost from 6 months ago → win-back campaign EVERGREEN (always-on ICP coverage): - Full ICP TAM minus customers → always-on brand awareness - Every Head of Marketing at SaaS companies $10M-$100M ARR → persona-specific thought leadership - Lookalike audience built from your closed-won → automatic reach expansion The Buying Committee Agent finds the right personas at every ICP company. Validates email, LinkedIn, and title to maximize match rates. Customers, competitors, and open deals get excluded automatically. Audience reads your CRM live so it never goes stale. The attribution loop: when an ad-clicker hits your site, Warmly identifies them as coming from the ad and tracks every subsequent visit. You see which contacts received ads, visited the site from an ad, and ultimately closed, even days or weeks after the click. Setup: connect your ad account → pick or build the audience → push. Two minutes. Stay tuned. Playbooks for all 3 motions dropping over the next few days!

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 👇

Trying to land meetings in Q4 chaos?
 Here’s a play I’ve run every year—and it’s a banger for SDRs, AEs and Sales Leaders • 𝘿𝙞𝙜 𝙞𝙣𝙩𝙤 𝙮𝙤𝙪𝙧 𝘾𝙍𝙈: Pull a list of every deal you’ve closed this year    • 𝙁𝙞𝙣𝙙 𝙩𝙝𝙚 𝙥𝙖𝙩𝙩𝙚𝙧𝙣𝙨: What industries, titles and problems show up the most?    • 𝙏𝙖𝙧𝙜𝙚𝙩 𝙡𝙤𝙤𝙠𝙖𝙡𝙞𝙠𝙚𝙨: Use LinkedIn Sales Navigator or your CRM to build a list of similar accounts    • 𝙋𝙚𝙧𝙨𝙤𝙣𝙖𝙡𝙞𝙯𝙚 𝙡𝙞𝙠𝙚 𝙖 𝙥𝙧𝙤: Tie your outreach to your wins—"We helped [similar title] at [company] solve [problem]. Let’s see if we can do the same for you" 👉 𝗥𝗲𝗽𝘀: This will fill your pipeline 👉 𝗟𝗲𝗮𝗱𝗲𝗿𝘀: Your team needs this data. Help them end the year strong Whats one win from this year you can turn into a new meeting?
 Drop it in the comments—I’d love to hear how this works for you

I used to rely on guesswork for leads... Now, every lead I target is backed by data. Most businesses struggle with: 1) Generating consistent, high-quality leads. 2) Outreach can sometimes feel like a gamble Without clear targeting or systems. You're relying on guesswork. Here’s Jérémy's 6-step system: 1) Use AI for smarter research. Tools like Clay target decision-makers precisely. Stop wasting time on irrelevant prospects. 2) Automate outreach but keep it human. Lemlist + Instantly = Personalized follow-ups at scale. Test subject lines with A/B testing to boost responses. 3) Tap into LinkedIn’s potential. Combine Sales Navigator and PhantomBuster. Use Clay for refined targeting to supercharge efforts. 4) Enrich your data for insights. AI tools can analyze pricing pages or trigger trends. Deep research makes your outreach relevant. 5) Integrate inbound and outbound. Share engaging content to capture intent signals. Align personal branding with outreach messaging. 6) Act fast on intent signals. Monitor signals or engagements with tools like Trigify. Speed is your competitive edge in follow-ups. Quality leads are from precision, speed and relevance. AI doesn’t replace strategy—it enhances it. Follow us for more spicy LinkedIn tips.

What if I told you American Honda Motor Company, Inc. generated $66M in revenue... but the real story wasn't the revenue? While analyzing a Honda CB350 Sales Dashboard in Power BI, I discovered some interesting business insights hidden behind the numbers. 📊 Key Metrics: 💰 Revenue: $66M 📈 Profit: $16M 💸 Total Cost: $52M 🛒 Orders: 559 💳 Finance Sales: $37M 🎯 Margin: 23.6% 🛡️ Accessories Revenue: $3M 🛡️ Insurance Revenue: $3M Here's what the data revealed👇 ✅ Honda is generating strong revenue, but nearly 80% of that revenue goes into operating costs. Insight: Cost optimization could unlock millions in additional profit. 💳 Financing contributed $37M in sales. Insight: Customers want affordability and flexible payment options. Decision: Expand financing partnerships and simplify loan approvals. 🏍️ Premium Bikes generated $18M in sales with the highest Average Order Value. Insight: Premium customers deliver the highest value. Decision: Invest more in premium marketing and customer experience. 📅 Monthly sales peaked above $6M in top-performing months but dropped significantly during weaker periods. Insight: Demand is seasonal. Decision: Run targeted campaigns during slower months to stabilize revenue. 💵 Cash remains the top payment method at $20M, while digital payments (UPI & Credit Cards) contributed $34M combined. Insight: Customers are rapidly embracing digital transactions. Decision: Introduce cashback rewards and digital payment incentives. 🛡️ Accessories and Insurance generated $6M combined. Insight: Revenue opportunities don't end after selling the motorcycle. Decision: Bundle accessories, insurance, and maintenance plans to increase customer lifetime value. My biggest takeaway? Honda doesn't need more data. Honda needs more action from the data. The dashboard clearly shows opportunities to reduce costs, grow premium segments, expand financing options, and maximize post-sale revenue. That's the power of Data Analytics. Turning numbers into decisions. Turning decisions into impact. 🔗 Explore the Interactive Dashboard: https://lnkd.in/dTqhAUk7 #PowerBI #DataAnalytics #BusinessIntelligence #DashboardDesign #DataStorytelling #Honda #SalesAnalytics #DataVisualization Fatolu Peter (Emperor Data Analytics) 🚀📊 Data Analyst | Power BI Developer | Business Intelligence Analyst

⚠️ Car dealers 🚗 & OEMs risk losing their competitive edge without investing in digital solutions. Read more here: https://lnkd.in/dYUTPEhk ➡️ As always, just my personal opinion. Please add yours & re-share the post. The automotive retail and aftermarket is undergoing a massive transformation—standing still is no longer an option! 👉 OEMs 🚗 are scaling back their agency model ambitions across different regions. Leading brands like Volkswagen are returning to a dealer-based model, while Stellantis, Ford Motor Company, and BMW Group have halted their rollouts. Polestar is also adjusting its retail approach. 👉 OEMs have expressed a strong focus on expanding aftersales and digital services throughout the entire vehicle and customer lifecycle. This shift could increase market pressure on non-captive service providers and dealer groups. 👉 Dealers 🏪 must diversify their business both horizontally and vertically to tap into new revenue streams. 👉 To remain competitive, digital solutions must connect the dots across multiple data sources. The key lies in digitization 💿, data integration, standardization, and automation. One challenge is the fragmented digital value chain, particularly at automotive retailers. Stakeholders 🚗 operate in siloed and poorly connected systems, leading to a suboptimal customer experience. 👉 Customer Data Platforms (CDPs) can serve as the technical backbone for the stakeholders in the automotive value chain, enabling targeted and improved customer communication throughout the entire lifecycle. 👉 An integrated CDP empowers OEMs, non-captives, and dealers by consolidating customer data from multiple sources 🤝 into a single, comprehensive view. This facilitates personalized communication across all touch points. 👉 Automation & AI 🤖 enable efficient personalization without compromising personal relationships. This strengthens long-term customer loyalty 🌟 and relationship management. 👉 Digital platforms have proven to increase revenue potential per customer. A study by Veact GmbH, one of Europe’s leading CDP providers, found that depending on the vehicle class, revenue per car could increase by 21% for mid-size models and up to 38% for compact-class models. Additionally, workshop productivity could improve by 12%. 👉 VEACT’s approach leverages multiple data sources—including invoices, vehicle details, and service histories—to build comprehensive customer profiles and identify the best target audiences for marketing campaigns. 👉 By creating 360-degree customer profiles, businesses can unlock new sales & service opportunities. 🚀 Is your automotive business ready to accelerate into the future? Let's discuss how a Customer Data Platform can fuel growth, enhance customer loyalty, and drive success in the evolving automotive landscape! 👇 #automotive #automotiveretail #aftermarket #digitaltransformation #OEM #dealership #innovation #VEACT #datamanagement #AI #automation #customerexperience #customerloyalty

Outbound in 2026 isn't about better emails. It's about better routing. Instead of scaling volume - focus your effort on the right account, triggered by the right signal. Here's the full system: 1/ ICP modelling & closed-won analysis → HubSpot, Attio or your CRM of choice Pull the closed-won data. The patterns are already there. You're looking for what your best customers had in common before they bought. Use Claude Code to analyze the data. 2/ TAM mapping & qualification → AI Ark, DiscoLike (TAM mapping) → Claygent, OpenAI, Firecrawl (qualification) Build the universe that matches your refined ICP. Then qualify before anyone touches the list. AI agents now scrape websites, read job postings, and parse 10-Ks for you. Work that took an SDR a full week runs in 20 minutes. The output: a list where every account has been validated against your fit criteria, not just pulled from an Apollo filter. 3/ Scoring & tiering → Clay One platform to score, tier, and route. T1, T2, T3, DQ. Effort should match account value. A tier 1 account deserves 30 minutes of research. A tier 3 account deserves a templated email and nothing more. 4/ Contacts enrichment → Prospeo, FullEnrich, CompanyEnrich Waterfall enrichment is non-negotiable in 2026. Single-source enrichment hits 40-60% coverage on a good day. A waterfall across multiple providers gets you to 85%+. 4.5/ High-intent signal tracking (running in parallel) This runs alongside your outbound, not after it. → Website visits: RB2B, Instantly, Vector 👻 Anonymous traffic deanonymized. The accounts already researching you, before they fill out a form. → Meeting form: Tally, Default Capture intent at the highest moment of interest. Route hot leads instantly, no SDR triage delay. → Webinar attendance: LinkedIn, Luma Event signals are the most underused intent data in B2B. Someone gave you 45 minutes of attention. Use it. → Content engagement: Trigify.io, Teaminfluence, Clay Track who's commenting, liking, and engaging with your content. That's a warm list disguised as social activity. 5/ Outreach (effort scales with tier) → Tier 1 (call + LI + email): Nooks, Lemlist, Instantly The full-court press. Multi-channel, multi-touch, hand-crafted messaging tied to the closed-won patterns from step 1. → Tier 2 (LI + email): lemlist, Instantly LinkedIn warm-up before email. You've already shown up in their feed when the email lands. → Tier 3 (email only): Instantly.ai Volume play, but still personalized at the company level. Templated isn't the same as generic. Tier mismatch is the most common outbound mistake. Calling tier 3 wastes calls. Templating tier 1 wastes the account. 6/ CRM sync → CRM of choice Closed-won data flows back into the ICP model. The loop closes here. This is what makes 2026 outbound a system, not a campaign. Every output trains the next input. Save this if you're rebuilding your stack.