Erica C. +1 to what Jonathan W. mentioned! Even better, if you already have pre-made sequences based on industry in your SEP (E.g. Salesloft/Outreach, etc), a little tip could be to get AI to sort the company into one of your pre-defined industry, and reach out accordingly. If not, a simple thing could be feeding this to your sales reps, so it gives them a 'warm account' to go after. But of course, ensure to score the account first and ensure it's qualified 🙂
Ciaran E. Probably 2 ways on the top of my mind
https://www.featuredcustomers.com/ -> I've seen this website quite abit when it comes to finding verified customer reviews (I'm not too sure on their methodology in doing so, and I'm unsure if they have any type of API to connect to Clay). But if it's just a few website and you don't mind manually doing it, this website might be worth looking at
If you want to do it in Clay, I can think of 2 ways:
Firstly, have a company's website, followed by an enrichment column (Claygent) to find the company's customer stories page. Once you have that page, you can either get Claygent to scrape the page and return you a list of client names, or use Zenrows to return all page details, followed by using Claygent to extract the client names.
The first method might not work if a company's website is formatted in a different way (E.g. You have to click on industries first prior to seeing any case studies). In this case, you might want to try using Clay Navigator instead, where you instruct the AI agent to specifically find some examples of customers on {website}. This might work but again, not 100% and takes many credits.
If you don't mind going outside of Clay, I might suggest using something like Manus AI which has slightly better AI agent capabilities.
Hope it helps! Feel free to DM if you have more questions
Hey Caroline B., thought I’d jump in with a couple of pointers. There are generally two inputs people rely on, which it seems like you are using as well:
Their LinkedIn summary
Their current or past experience
For the summary (See first screenshot): If the person doesn’t have a LinkedIn summary, the model won’t have anything meaningful to work with. In your case for example, I found your linkedin profile, and seems like your summary field is blank, so Clay can’t use that as a personalization source. For experience data (See second screenshot): Clay returns the experience section as a JSON array, meaning each role is its own object. Because of that, you can’t just tell the AI to “look at the profile”, it will treat it as unstructured text and give weird results. The right way is to first use formulas to extract and format the relevant data from each experience item, then feed that structured version back into your prompt. That’s what makes the personalization reliable. I also have some thoughts on how to get the most out of AI for personalization overall, but figured these two points would be most useful to you right now. Feel free to DM me if you want to dive deeper or if you want the template to extract all the 'summary' from each experience, happy to help!
Claire C. Starting from one data point is a good start 🙂 I might even layer in segmenting by the sub-industries. E.g. "Here's what {titles} from {sub-industries} are saying" Might take time, but if there's a sub-industry that you have really strong set of content & case studies for already, might be great to experiment with it!
Claire C. Just sharing my two cents from my own previous experience in SaaS + my work with different clients now The funnel stages aside (E.g. Awareness, Consideration, Conversion, etc), I think the segmentation logic should be slightly simpler. It could be:
Segmenting by industries, company size, your typical firmographics data
Going one step further, segmenting by type of sub-industries. This is where Clay comes in and do it really well. Get Claygent to go into each website, find out what they do and from there put them into a list of predefined sub-industries
Other data points - for example, segmenting by their title, segmenting by the type of text that they use, segmenting by the type of business they are
Because the fact is, it doesn't matter where this prospect is at the current funnel stage, because it will always be fuzzy. But if a message is relevant to the person's title, the type of industry, and the type of company, it doesn't matter where they are in the funnel. That message will always resonate, and that's a touchpoint that is memorable. And when it comes to signals, there are ones that you can definitely use. For example, when a prospect with an ideal title just started at one of your target company, that's a potential signal to use. However, the best signals are probably not the ones that are already built for the general public because everyone is using them. The best signal is probably one that takes time to understand your ideal client profile and from there build something custom based on unique data sets or bring things together to make it your own. (Jordan Crawford talks about this really well)
Petar R. Try either one of this!
Call HTTP to https://postman-echo.com/delay/10, this adds a delay of 10 seconds! If you need 30 seconds for example, just add 3 columns.
I recently saw https://delayclay.com/ as another option, great to give it a shot!
Loren P. Might want to check out either using icypeas.com's sales navigator export or using Clay's "Find people from external list", especially if it's a large export. Using PhantomBuster with your own cookies might result in temporary linkedin ban if not careful. But for one time use, it should be fine!
Loren P. You could use the option that Honourable A. suggested, but you might have to do an extra step. That option is actually weird and doesn't work the same way as Sales Navigator's filter. This is how it will work:
For example, Bob used to work as a software engineer at abc.com, but as now gone to be a engineering manager at amazon.com.
But Clay will return Bob as 'software engineer' at abc.com, and it will not return his latest position.
You will have to do a second step, which is to take the linkedin profile returned, and enrich the linkedin profile, and check for their current company, which using an excessive amount of credits. Loren P. Are you looking to run either one of these plays?
Find people who used to work at your clients' company, and reach out to them
OR do you already have a list of people within your CRM who used to be clients, and you want to check who has moved on, and you target them accordingly?
Might have some ideas that I can share here depending on your answer.
Hey Karol K. , sharing my 2 cents here. Generally speaking, Clay's 'Find People' might have updated information sometimes. So the first step I would do, is to use 'Enrich Person' and at least check if any of their 'current companies' is the same as what Clay gave you. I typically like to use a formula *See attached), and extract out all their current domains from 'current_experience'. You can then imagine once you have the current domains, it's fairly easy to do a lookup from your original list to the new list. Hope it helps a little!
