Data-Backed Approaches to Closing Deals

Your POC process is probably why you're not closing enterprise deals.   After analyzing POC outcomes across our portfolio, the data is clear: Companies with structured and priced POCs close 3x more deals than those running free pilots.   Why charge? Price signals seriousness. Even nominal fees filter serious buyers from tire-kickers. Frame your pilots as fixed-fee engagements: Say "we structure this as a 4-week, fixed-fee engagement to quantify value and build your business case."   Be sure to clarify pricing expectations in the process: If your pilot costs $5K but commercial deals are $100K-$300K based on the value unlocked, state this explicitly to avoid anchoring.   Here are 5 best POC best practices we see:   1. Define success criteria, not scope Align on specific KPIs, business outcomes, and who signs off before writing a line of code.   2. Time-box ruthlessly with weekly checkpoints POCs should run 30-90 days max. Set weekly or bi-weekly checkpoints to maintain urgency.   3. Pre-commit the path to commercial discussions Before starting any pilot, confirm that hitting the success metrics will trigger stakeholder presentations and commercial negotiations.   4. Demand access to the full buying center Technical users alone can't close deals. Ensure you meet decision-makers and budget holders during the POC, not after.   5. Document like a contract Formalize scope, terms, and deliverables in the agreement. Include specific responsibilities for both sides, data access requirements, success metrics, timelines, and post-POC commitments.   --   POCs are where your enterprise motion gets built. Treat them that way.   I wrote a guide to AI pricing with Madhavan Ramanujam and Joshua Bloom that discusses these ideas in more detail. If you're curious to dive deeper, I'll leave that link below. Also, Madhavan just released a new book called Scaling Innovation that also explores these topics. Highly recommend!

Every Firm Wants Off-Market Deals. What do many fail to realize? Deal sourcing runs on data. Want proof? 90% of the PE firms we talk to at SourceCo rely on the same self-serve databases to find deals. In 2025, anyone can access the same databases and send mass emails. So How Do You Stand Out? You leverage the right data sources to find the right companies—then enrich that data with the data that matters to your investment criteria. There are countless private equity data tools available, making it easy to feel overwhelmed. The problem? No single database is complete. We help PE firms identify the critical data they need. That could mean scraping RFP data or using AI agents to determine union affiliation. We are about to close a ~$15M deal in a niche market with only 50 or fewer targets—our second deal in the last six months, with more to come. Targeting a Niche Within a Larger Industry -We searched for a highly specialized service provider within a broader industry. -Scraped the internet for every service provider in the space and leveraged AI to refine our search. -Manually cross-referenced lesser-known datasets—trade associations, industry publications, and regional business records—to ensure nothing was overlooked. -Identified companies that were growing but still under the radar—the best opportunities aren’t always actively advertising. Strategic Seller Engagement -Prioritized relationship-building over quick wins. -Developed a content-driven nurturing system to educate sellers on how our buyer’s experience and resources could benefit them. -Used light, trust-building touchpoints before pushing for a conversation. (It took 30+ touchpoints to move the seller from “interested” to a real conversation.) Positioning Our Client as the Ideal Buyer -Highlighted our client’s unique value and experience in the sector, crafting a compelling narrative, messaging, and materials. -Anticipated seller concerns and tailored our approach accordingly. -Positioned the acquisition as a strategic win for the owner—not just a transaction. Six months ago, they closed their first deal. Six days from now, they’re on track to close their second. Now it's time for 3, 4, and 5. Want to Level Up Your Deal Sourcing? At SourceCo, we’ve compiled an extensive list of private equity data sources—all in one place. This resource highlights niche tools and datasets to help firms go beyond the standard platforms. Whether you need demographics, data processing, or financial profiles, this list breaks down the best options available. I’m happy to share the list with anyone looking to take their deal sourcing to the next level in 2025.

#Negotiation Tip Number 4: Gather and Leverage the Data.   In his book “Moneyball,” Michael Lewis quotes John Henry, renowned investment manager and owner of the Boston Red Sox, in reference to a comparison between professional baseball and the financial markets, “People in both fields operate with beliefs and biases. To the extent you can eliminate both and replace them with data, you gain a clear advantage.” Since that book was published, data analytics has become a vital part of how almost every major professional sports team makes decisions. Data is equally important in commercial real estate negotiations. Most CRE professionals realize the importance of obtaining data, but few understand how to fully use it to achieve a successful outcome. In a negotiation while representing a buyer of a low-rise office building in a submarket with dozens of similar-sized office buildings, my team cherry-picked comparable sales and sent them to the seller’s representative, making a case for a purchase price around $90 per square foot. On the contrary, the seller’s representative made the case that the purchase price should be closer to $100 per square foot — submitting their own version of comparable sales as justification. At this point, our team was certainly tempted to accept the invitation from the seller’s broker to play the high-low game. Instead, we evaluated the seller’s comp set to determine how we could either work toward bridging the gap or defend our original position all while trying to achieve our client’s goals. As we dissected both data sets, we were able to see that many of the seller’s comparable sales had already been renovated, while the property being bought still needed cosmetic renovation. That was telling from a qualitative analysis, but the most convincing case came when we put both sets of sales comps on a line graph to show the trend in sale price per square foot over time. This line graph was very helpful for both the buyer and the seller to understand the current value of the property as the next data point in a trendline. Ultimately, they agreed on a purchase price that equated to $87 per square foot. Both sides had data, but it wasn’t until it was dissected and brought to life that anyone truly understood how it brought relevance to the negotiation. #CapitalMarkets, #InvestmentSales, #CRE, #CommercialRealEstate

Several times M&A negotiations stall not because of unrealistic demands from the other side but because of ❗️uncommunicated assumptions about business performance and risks and ❗️lack of a data-driven negotiation process. Two examples from the past six months: 1️⃣ We represented a buyer team, involving a complex earnout scenario in an acquisition. Negotiations around valuation and deal structure began to stall because the target felt we were pushing for a structure that would penalize the target unfairly for post-close performance. 2️⃣ We represented a seller that believed in their forward performance. However the top few potential buyers were skeptical and didn't believe our client could hit the numbers. ✅ Solutions to both scenarios: 🎯Instead of negotiating with the other side in a vacuum, we built and shared a more detailed model with them with our drivers and our assumptions based on historical data and the customer pipeline. 🎯 The discussions moved from the abstract to collaboration on a shared set of numbers and business assumptions. 🎯 We were able to step through specific scenarios and have a much more nuanced, granular discussion, with each side using the same framework and model structure. 🎯And we were able to drive to a successful resolution in both deals. (This is NOT saying that you open everything to the other side. Knowing the parts of the model that should be shared for negotiation purposes and those that shouldn't be is critical). But sometimes the best path forward in "stuck deals" is throwing light on the data. #mergersandacquisitions

Who doesn’t love a QUICK win?? After a 6-week pilot using 6sense hot account alerts, Sift hit 220% of their pipeline goal! By tapping into intent signals and multi-threading within key accounts, they’re driving more meaningful engagements and closing deals faster. It’s all about focusing your resources where they matter most. Here’s how they did it: ✅ They tapped into account insights, real time. Sift used 6sense’s intent data to monitor and act on real-time signals from accounts in decision and purchase stages. By focusing on hot accounts, they were able to prioritize outreach to prospects who were most likely to convert, driving rapid pipeline growth. ✅ They multithreaded for deeper engagement. Sift’s SDRs didn’t just focus on one contact. They used 6sense to identify and engage with multiple stakeholders across each target account. That led to stronger relationships and increased ability to move opportunities forward. ✅ They ran targeted competitive campaigns. Sift ran highly specific campaigns targeting both industries and competitors. By aligning their messaging to each target group’s pain points and competitive landscape, they were able to differentiate themselves and capture attention quickly, leading to higher engagement and pipeline generation. 3 Big Takeaways 1. Don't miss a revenue moment. When an opportunity presents itself, we call that a “revenue moment.” Not a revenue year, revenue month, or even revenue week. Use real-time data to know exactly when to reach out — then watch your conversion rates soar and deal cycles shorten. 2. Engage the whole buying team. Say it with me: Single-threading kills deals. Engaging ALL the right decision-makers within each account from the start makes deals stickier and moves them through the buying journey more efficiently and effectively. 3. Get hyper-relevant. No one needs another generic email or ad. Use data plus generative AI to tailor your messaging to specific industries, roles, competitive situations, etc. Speak to prospects’ specific needs and you’re going to have a much better chance of connecting.