This workflow will enable you to:
- Find and scrape blogs, articles, interviews, podcasts, or any element of thought leadership from your prospects
- Generate personalized emails and LinkedIn messages that references this data
- Include AI snippets of former college traditions for even greater personalization
In this workflow, you'll need to input your prospects' LinkedIn URL and company domain. This recipe performs the following actions:
- Find and normalize the phone numbers of all your prospects.
- Generate a company description
- Create personalized copy referencing their target customers and your business solution
In this workflow, you'll be able to:
- Pull in news articles relevant to your search query by extracting the RSS Feed
- Extract the business referenced in the article with Claygent and enrich it using integrations
- Find contacts at those companies and enrich them with emails
This campaign pulls in an existing list from the client's Hubspot or Salesforce Account. This list can be imported either from a CSV or from the native import feature in Clay.
Low Hanging Fruit is a term commonly used in sales that refers to leads that are most likely to convert. In theory, it'd be much easier to book a meeting with somebody who is already familiar with a client's company and their offering. This is why the re-engage can work well.
It's also a strong campaign because there's most likely existing data points about each prospect/lead that we can utilize in the copy. We'd run this campaign for a client pretty early on in our engagement with them especially if they have an existing inbound work-flow. The copy will reference whatever activity led to the prospect to be on the HS / SFDC list, whether that be a form-fill, a demo/meeting request, a meeting held, etc. A brief 1-liner overview of the client's offering should also be worked into the campaign. Additionally, referencing recent news or a problem the prospect may be facing that the client solves should be worked into the copy using AI prompting.
This generated us roughly 30 positive replies over the course or 2.5 months and 15 of those replies were meeting requests.
Learn how this template works
This template uses a person's professional profile data, Claygent's research, and Google's Gemini LLM's reasoning capabilities to score people for outreach. It then uses additional logic to tailor the value-prop in the message for each prospect.
