Every business wants to grow. That's why marketing exists. But, inside "marketing", growth hacking is a new field with a simple goal: getting new customers. While traditional marketing is about branding, "growth hacking" focuses on building a system to win new customers, fast! 🚀

Growth hacking is at the crossroad between marketing and tech. Startups set up multi competencies growth hacking teams with developers, marketers, and product managers. And growth hacking, once limited to early-stage startups, is becoming mainstream.

During the last months, growth hacking teams (or simply "growth teams") have contacted me to discuss how their company does prospecting and to see how to use Datablist to store prospects. In their organization, the growth team is responsible for prospecting. The sales team is used later on in the workflow once a prospect shows a sign of interest.

Growth teams build large prospect lists using scraping and companies' databases. Then, they score prospects to engage only with relevant ones. Interested prospects are then passed to the sales CRM and the conversation continues with a salesperson.

Their results are stunning, with multi digits growth rate! I wanted to share with you what I've learned from those interviews and explain how modern startups use data and engineering to fuel their growth.

Below is a summary of how growth teams set up prospecting.

Step 1: Prospect List building

It always starts with building prospect lists. Prospects are companies (or people) who may be interested in the product you are offering.

B2B company databases (e.g. Crunchbase or AngelList) let you export large datasets with basic business data: the company industry, funding rounds, employee headcount, etc.

Another way to build a list of prospects is "scraping". LinkedIn offers premium members to search for profiles using job titles, or industries. Third-party tools extract the LinkedIn profiles into spreadsheets or CSV.

Scraping works also with Twitter and Facebook Groups. I've talked with people scanning for new Facebook B2B group members and engaging with them on LinkedIn. See our guide on how to scrape Facebook group members.

Growth teams are really creative to find new prospects. I've seen teams tracking job offers or employees changes. For example, a Fintech startup has coded an "algorithm" to detect businesses that have just recruited a CFO (Chief Financial Officer).

Another software company selling an e-commerce plugin parses website HTML code. HTML tags indicate which e-commerce framework is used. All websites built with Magento or Shopify (e-commerce frameworks) are added to their prospects list.

Other growth teams screen new startups on ProductHunt or IndieHackers.

Storing B2B prospect lists

I asked for the tool they use to store their prospects:

  • Small teams use spreadsheet tools like Google Sheets and Airtable. Airtable comes with basic data types, some collaboration features and an API which makes it great to store prospects.
  • In bigger startups, teams have coded their workflow with a custom database. PostgreSQL, an open-source database, is often cited; along with Google Firestore, a cloud database. With the database, some have added a data-warehouse (Google BigQuery, Snowflake) to log all events generated from their prospects. When a data-warehouse is added, the system becomes a "Customer Data Platform". They log events from prospects, users with a free plan, paying customers, churned customers, etc. A Customer Data Platform offers a full view of the funnel acquisition from the prospect to the paying customer.

Both spreadsheets and custom developments bring challenges:

  • Airtable reaches its limits with 10k prospects and Google Sheets doesn't have data structures.
  • With a custom database, developers have to code an interface, manage user permissions, deal with integration to their sales CRM and code data management feature such as deduplication, and leads merging. Instead of focusing on algorithms to source prospects, they waste time reinventing the wheel.

Prospecting relies on a large volume of data and Datablist is perfect to store prospects. With an easy-to-use interface, CSV imports, deduplication, items merging, users management, and a developer-friendly API.

Step 2: Prospect Enrichment

The next step is prospects enrichment. Enrichment's purpose is to have a complete identity for every prospect you have, whether they come from a business database, from scraping, or for manually added prospects.

With identifiers such as a website URL or an email address, it's easy to fill in the missing information.

The growth teams I've interviewed perform manual and automatic enrichment. Teams with prospect lists on spreadsheets use manual enrichment. When a new prospect is added, they use LinkedIn, Crunchbase, etc. sources to fill important attributes.

Bigger teams, with larger prospect lists, have automated this process by plug-in external APIs into their workflows. New prospects trigger enrichment functions. A wide variety of SaaS products exist to search for any kind of data whether you want to enrich a contact or a company.

For contacts, enrichment services include:

  • Email Finder
  • Email verifier
  • Job Title

For companies, enrichments include:

  • Company Tech/Sales/Finance Stack
  • Website traffic estimation
  • Funding rounds
  • Employees Headcount
  • Social Network profiles
  • Country
  • Industry

Step 3 : Prospect Scoring

Then, every prospect is scored based on its properties and the prospects list is ranked. Defining a scoring formula is tricky but you need to define your "Ideal Customer Profile" and the score must reflect how close to this ideal customer your prospect is.

A prospect score may change. For example, if a company raises money, it means the company is accelerating and your product might fit with this change.

Scoring in spreadsheets or with custom databases is similar. But when a data warehouse is connected to the system, event logs from the data-warehouse are added to the score formula. Events from your website analytic software can feed the data-warehouse.

Scoring is meant to narrow your prospects list and avoid spamming everyone on your list.

Have you ever received an invitation from a stranger on LinkedIn to connect? Most of the time, they come from an automated workflow. And have you noticed you receive fewer invitations since the beginning of 2021? That's because LinkedIn restricted the number of invitations a member can send from 100 per day to 100 per week, i.e. 300 invitations per month (almost 90% less). When you have 300 prospects per month to contact, you want to cherry-pick them.

Same with cold emailing. Spam filters detect accounts sending mass mailing and analyze how people react to the emails. Do they open them, do they click, reply, etc. Sending hundreds of emails per day will get your domain blacklisted in no time.

That is why scoring and segmenting are so important. And because nobody likes spam, you aim to contact fewer prospects but increase your conversion rate with relevant ones.

Step 4: Engage with prospects

Next, select prospects with the highest scores, and engage with them. "Engaging" means you want them to at least read what you have to offer. You can engage by contacting them or with targeted advertising.

Here is a list of solutions growth teams use to engage with prospects:

  • Direct contact
    • Cold emailing: Lemlist, Reply.io, etc.
    • LinkedIn Automation to connect and send LinkedIn messages
    • SMS, Whatsapp, Facebook, etc.
  • Events
  • Targeted Advertising

Engaging with prospects generates events that can fuel your growth system. Email clicks, user visits, and other events can be logged to a data warehouse to update the score of the prospect.

Once a prospect replies to a message (email, LinkedIn), it ignites a sales approach. Steps 1 to 4 are dealing with thousands of prospects. In the fifth and last step, the prospect becomes a lead and is now the responsibility of the sales team.

Step 5: Import leads to Sales CRM

In the companies I've interviewed, a reply (or any sign of interest) converts a prospect into a lead. Leads are sent to sales CRM (for example Salesforce) and are assigned to salespersons.

Prospects and Leads belong to different teams and tools. Prospection is for the growth team and prospect lists can have hundreds of thousands of contacts.

And leads are managed by the sales team in a sales CRM. CRMs should be only for warn leads that know your product and show a minimum of interest. You must avoid polluting the CRM with thousands of useless prospects.


Growth teams are reinventing prospecting. From a manual task performed by salespersons, it becomes an "automated system" built like internal software. Datablist is a perfect tool to store your prospect, merge duplicate entries, and run enrichment services. Feel free to contact us!