DataLane

Number 1 reason sales reps selling to local businesses aren’t efficient? The data they are using in Salesforce is a complete mess. In the past month, we’ve onboarded 5 companies with 200+ sales reps and all of them had the same problem. When we map our real-time database to the static accounts in their Salesforce, over 50%(!) of their accounts aren’t addressable: - Out of business: turnover for local businesses is huge - Wrong industry: over the years bad data accumulates - Duplicate accounts: business hierarchies are extremely difficult to map And on top of that, companies are often missing thousands of good-fit accounts. These blindspots lead to incorrect claims about “exhausted TAM” and broken territory assignments. We’re working on a way to offer a 30 min Salesforce Health Check that securely and automatically builds this waterfall, without any data leaving your CRM. For one multi-billion restaurant SaaS company we discovered 60% of their accounts needed to be disqualified, but fortunately we simultaneously identified 2x new, qualified accounts. If you’re interested in getting an accurate picture for your company, send me or Miles Kane a message.

I often get asked why local economy? The answer is simple - it’s a massively underserved market. 99% of sales tools are designed to sell to office workers. This is no knock on LinkedIn Sales Nav or ZoomInfo, those tools are great if you’re selling to tech companies or F500. The challenge is if you sell into restaurants, the trades, brick-and-mortar retail, healthcare providers, or any other mainstreet business - these companies and individuals simply do not exist on LinkedIn or in traditional databases. They are ghosts on the internet. As a result, sales reps in these industries spend 20-40% of their week on manual research - making it nearly impossible to hit ambitious revenue goals. The good news is it’s finally possible to solve this problem. Unstructured data algorithms are now intelligent enough to map an incredibly noisy web of online, offline, and proprietary data sources. The best companies are already automating this research away, freeing up reps to focus on selling. Over the next few weeks, I’m excited to start sharing more examples of how they’re doing it and what it means for the future of GTM.

GTM for the local economy requires a completely different playbook. Unlike traditional B2B GTM, selling into hospitality, home services, healthcare, and other local verticals has always lacked the data infrastructure to make TAM mapping, scoring, intent, and contact coverage actionable. With AI, that gap is closing. The best sales teams in local verticals are scaling faster than ever. Excited to be doing a deep dive into this topic on the GTM panel at Vertex: The Vertical Software Conference. Highly recommend you check out the event if you're in the Bay Area on Tuesday!

Lots of AI tools make big claims, but few deliver real, measurable impact for sales teams today. Owner just raised a huge Series C at a $1B valuation and is one of the fastest growing tech companies selling to SMBs. Kyle Norton their CRO took an early bet on DataLane and has seen huge benefits: ✅ DM connect rates increased by 2.5x ✅ Deal cycles shortened significantly ✅ Reps made 50% more calls when not tasked with contact research Decision maker contact data has been notoriously hard to find but AI has completely changed the game. There’s a lot of noise about AI SDRs and intent products, but if you’re selling to SMBs, getting in touch with decision makers directly will have by far the biggest impact. Want your outbound team to bring in $72K ARR CW per month? Check out datalane.com

Most healthcare sales teams waste 20-40% of their week searching for prospect data. Learn how industry leaders are finally solving this in 2025.

Most wellness & beauty sales teams waste 20-40% of their week searching for prospect data. Learn how industry leaders are finally solving this in 2025.