We're big believers in cold calls and cold emails. Built two businesses on the back of cold outreach. But there's always been a version of the problem that bothers us: calling blind.
Every day in this industry, something happens to one of your target accounts. Capital gets raised. A pension fund makes an allocation. Firms merge. Advisors move. RIAs get acquired. Most sales teams find out weeks later, if at all. The gap between when that event happens and when your rep knows about it is where real opportunities disappear.
A few years back, our team got frustrated enough to actually do something about it. We knew if we built a news team for Dakota Marketplace, we'd benefit — and more importantly, our customers would too. So we did.
We cover three things. Fundraising News tracks capital raises, new fund launches, and mandate activity across institutional allocators. Private Company Transaction News covers M&A, firm mergers, acquisitions, and ownership changes — the kind of news that resets investment committees and puts existing manager relationships up for review. Wealth News tracks advisor movement, RIA acquisitions, and breakaways. When an advisor moves, their book often follows.
All of it flows into the Dakota Marketplace database daily and surfaces through the Claude, Chat, and Co-Pilot connectors. So when something changes at a target account, you can find it before you call. It makes the cold a little warmer.
Here's where it gets interesting. The investment industry produces a high volume of these trigger events. Tracking them manually across thousands of accounts is not a realistic ask for any sales team — which is why we built the product in the first place.
But what we didn't anticipate was the API demand. Within the first year of launching Dakota News, customers started asking if they could get the data directly into their CRM and data lakes — Snowflake and Databricks specifically. The use case was clear: push news events into Salesforce, set a signal for the account, and trigger a prompt to the rep when something changes at a target firm. It's kind of crazy how one simple concept, news, turns out to be so useful once the data is clean and current.
With AI agents in the mix now, the bar for acting on that signal has dropped considerably. If you have good, accurate data, building an automated signal workflow is not a heavy lift. Customers who got their news signals clean first are finding the agent layer falls into place quickly.
The most direct use is pre-call research. Before any outreach, filter Dakota News for the firm. A recent acquisition, an advisor departure, a new capital raise gives you a specific, current reason to call. The second use is trigger-based prospecting: set filters on event type, firm size, or geography, and build your weekly outreach list around what actually happened rather than a static account pull. And increasingly, customers are using the Dakota News API to automate this entirely — events flow into Salesforce automatically, queuing prompts for the rep assigned to that account.
We are living, breathing examples of simply trying things with data and AI and seeing what happens. The more you test, try, and tweak, the more you learn. There is still a lot of apprehension around these topics at a lot of firms. The teams willing to experiment are the ones building a durable edge.
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