Here is how to build a data infrastructure that'll make your competitors weep. 

The most important thing to consider when doing this is that you should be trying to build infrastructure, like roads and power grids, and not a random constellation of tools that you use whenever they’re needed. Imagine if you had to build the power lines whenever you needed to add lights to your home. The best data infrastructure is one where new tools are easy to add on, and where you know where data is inside of the system. 

The most important step is to centralise your operations. Your data needs a single home, not spreadsheets scattered across multiple devices. There are several levels to consider, depending on the scale and usage of your tools. Most companies have some data storage infrastructure. If you have a lot of data, that might mean hosting your data on an AWS database or otherwise. However, for most businesses, a good CRM is more than enough. Get familiar with Salesforce, Hubspot, or whatever new CRM you prefer. The important thing is just to pick on and commit. 

After you have the data stored somewhere, you'll need to think about the tools you want to use. 

Your tools should talk to each other if they don't, fire them. API integrations aren't a luxury, they're a necessity. Make sure your stack plays together well because static data is data that’s already dead. Infrastructure needs to be updated in real-time. Set up webhooks, use Zapier, and write custom scripts. Do whatever it takes to keep your data fresh. Don't build for today, build for where you want to be in 18 months. 

Cloud-based solutions aren't optional. They're mandatory if you want to scale without headaches. If your list of targets is a static CSV, you're doing it wrong. Implement dynamic list management. As data changes, your lists should update automatically. This is where Clay works especially well (even for people who are not particularly technical). Not all leads are created equal. Try to implement a scoring model. Use machine learning (or some other numerical system + AI/NLP) to refine your scoring criteria based on actual conversion data continually. 

Basic demographic segmentation is for amateurs. Try to get more granular. Combine firmographic, technographic, and behavioural data for hyper-specific segments. Set up triggers that automatically move prospects between lists based on their behaviour or changes in their data. Just closed a deal with a company? Trigger an update to target similar companies. 

Use AI to predict which companies are most likely to convert next month, next quarter, or next year. Build forward-looking lists that align with your sales forecasts and growth targets. 

Basic Data 

Firmographic data: I'd pair Clay with Apollo LinkedIn person/company data. Don't settle for basic info. Dig deep into employee counts, revenue figures, and growth trajectories. 11-50 employees does not mean 11-50 employees – it could mean 10 or 500 actual headcount. On Clay, click the Enrich button and find the number of employees with LinkedIn accounts, or send the Claygent to their LinkedIn site to check. 

Technographic data: BuiltWith is ok. Personally, I prefer publicwww.com raw code search. This doesn't just apply to tech companies. Knowing a prospect's tech stack gives you insights into their pain points and decision-making processes. It'll also let you build an offer that is especially relevant to them. 

Intent data: G2/Glassdoor/Indeed/X (Twitter)/LinkedIn (and more) – track what your TAM is researching and where they are being mentioned. Set up alerts for your target accounts. When they start sniffing out solutions like yours, pounce. When you see a signal or pre-signal, pounce. Proceed with caution, though. If you're relying on out-of-the-box intent data, you are too late. Try to use data sources that nobody else is using or build your own custom scrapers. If DemandBase or 6sense has sold a signal to 1000 other companies, you can be fairly certain that you are too late. 

Remember - your automated outbound strategy is only as good as the data that powers it. If you neglect your infrastructure, you might as well be shooting in the dark. Get this right, and you'll have a precision-guided missile aimed straight at your ideal customers. 

This approach isn't just about gathering data; it's about getting the right data that others miss. It's about digging deeper, looking where others don't, and creating custom solutions that give you an edge. Don't settle for off-the-shelf solutions when you can build a data acquisition strategy that's as unique as your business. Your competitors are using the same tired data sources – be the one who zigs when everyone else zags.

Your data strategy should be a living, breathing entity that evolves with your business and the market. Keep it dynamic, keep it clean, and keep it compliant.