What is a Prospect Relationship Management (PRM)?

1 Jan
5min read

👉 A prospect relationship management platform is a database made to manage your leads.The ultimate goal of a PRM is to increase sales and revenue by converting leads into customers. Effective prospect relationship management help revenue teams to streamline their sales process, increase sales pipeline, prioritizing most promising accounts, and reduce customer acquisition costs.‍

From CRM to PRM#

Traditionally, the CRM lets you interact with prospects and customers and catalog those interactions. What is confusing is that most B2B companies use CRMs for the prospecting part and the customer one.

While they’re two sides of the same coin, they do not belong to the same logic.

On the first hand, CRM aims to enrich and nurture the existing relationship between the company and its customers (i.e., loyalty, satisfaction, and expansion).

On the other hand, the PRM refers to a set of strategies, processes, and technologies that companies use to store and manage interactions with prospects. This can involve activities such as lead nurturing, prospecting sequences, or tracking and analyzing prospect interactions to understand their maturity level.

‍We live in an unbundle era, where we have best-of-breed for each use case. It does not make sense anymore to rely on your CRM as a big box where you sync all sorts of data.

It’s time to make a shift in the way we approach prospecting.

Especially since CRM and MAP tools are records-based, you don’t want to pay extra costs because you added thousands of cold prospects.‍

Let me introduce you to the PRM, a shadow guy (for now) that has the potential to be an unfair advantage for any sales-led organization.‍

Let’s dive in!‍

Why PRM represents an amazing opportunity for the sales-led motion#

It’s not a surprise anymore..

Since the recent hype around PLG, you understood that the Sales-Led motion does not have the wind in its sails.

There are notable reasons for that:

  • Sales spend only 1/3 of their time Selling (source: 4th edition Sales State)

  • 55% increase in CAC over 5y. (source: Profitwell)

  • 79% of sales reps don’t hit quotas

  • Still, 80% of companies have a sales-driven approach.

As Elena Verna put it, each market segment has its favorite monetization motion. “Favorite” is defined by the segment's preferred way to buy and the cost-effectiveness of the sale.

We live in a time where we need to revamp how we think about the sales organization, and the rise of revenue operations as a strategic function is evidence of this new status quo.‍

Let me explain:‍

Most companies today do the same things and expect their sales to hit the quotas.‍

They rely on an army of spreadsheets filled with thousands of leads, missing information, and duplicated records and push those messy data into the CRM.

What’s the bottom line?

Sales reps waste their time talking to gatekeepers, un-qualifying accounts that are not ICP, crafting emails that finally bounce, and cold calling invalid numbers.‍

It gets even worse:

As an easy, not appropriate though, response to it, reps are given too many accounts to try to solve this inefficiency gap.

As a result, they fail to hit quota because of time spent on admin and CRM and almost end up having a mental breakdown.‍

Some companies that try to improve sales performances do vertical outreach, like “let’s focus on accounting companies.” This is good for resonance and marketing to create dedicated assets in this segment, but it still does not help prioritize accounts in the buying window.‍

You might be wondering: What should we do instead?

Enter the PRM.‍

Imagine you centralize all your Total Addressable Market in one place and can focus only on the hand-raisers, the 3-5% of leads in the buyer window, notably thanks to Intents (see why intents are useful to auto-populate new accounts in your CRM) and through lead scoring.

Let's take it one step further.

You have enriched all the records and validated them using Zerobounce, Neverbounce or Scrubby for email validation, Numverify or VA to assist you with phone numbers (using Taskminions, for instance).

You have monthly crons (i.e., commands to a server for a job to be executed at a specified time) that check if there is any change in your prospects based on their LinkedIn profile URL.

As a result, you have up-to-date accounts with their related stakeholders ( at least

2) and all verified contact data in one extensive repository you control.

ONLY THEN, you push it to your CRM and assign them to your sales reps. That is what I call the "Minimal Viable Lead or account" which refers to the required attributes that need to be present before assigning it to a sales rep.

Now, let’s see how to build such a piece of technology

How to build a PRM the right way#

The origin of prospect data is mainly external (2nd & 3rd party data) and, more rarely, internal (1st party data like content leads or free users).

You first need the classical Sales Stack, including tools to scrap leads, do enrichment, and data validation.

Whether you use Cognism or ZoomInfo to get the lead data enriched and verified or do the extraction yourself using tools like Phantombuster or CaptainData and enrich it with Clearbit, Dropcontact, or Kasper, you would need validation tools or VAs to make sure your data is accurate and reliable.

The second thing you want is that big box that will gather all your TAM. Modern companies, such as Gorgias, Stripe, Gopigment, and Spendesk, where I worked, use the Data warehouse as the main database for leads.‍

And when you have this data storage in place, you need at least the following components of the modern data stack:
- EL tool: Formerly called ETL, those tools are used for the ingestion of data, from your different data sources, into the data warehouse.

  • Data Transformation: Those tools are made to prepare the data, to go from RAW to actionable data that will drive insights or further revenue orchestration.

We often see this modern stack as the typical way to gather first-party data and do BI on top. Using it to work with 2nd and third-party data is new here.

This required close collaboration between revops and data folks. The data engineers are accountable for plugging the data sources and ensuring that those data are business-ready, thanks to the transformation layer. The revops, on their side, are responsible for the revenue orchestration that goes on top.

Having all that data in your data warehouse enables you to benefit from greater observability, security, and flexibility. And getting Cargo on top is the application layer for revenue teams that sits on top of the work made by data engineers. The best of both worlds combined offers the 360° view of the customer you’ve heard about since the CDP emergence but never been able to see in your world.

Use cases of PRM for Revenue Operations.#

Once you have all your prospect data in your Data warehouse, revops have tons of use cases for leveraging the data warehouse.‍

Think about it this way: you have direct access to your CRM, prospects, product, behavioral, and financial data in the same place. The potential of what you can do is limitless.

The main areas would be:

Lead management

  • Lead scoring: By scoring your prospect on various criteria such as technographic, firmographic, psychographic, and intent-based - You can easily prioritize the most promising leads that deserve sales attention.

  • Lead tracking and categorization: by getting a centralized platform to store and manage all leads, you can easily track and categorize leads based on various criteria such as industry, technographic, and location. As a revenue orchestration tool like Cargo let you write back to the Data warehouse, you can easily track the lead's behavior (open email, click, reply) and work them accordingly to their behavior.

  • Lead routing and assignment: One thing that typically follows the account grading or leads scoring is to route leads and engage them differently based on their score: One-to-many approaches vs. tailored one, email only vs. multi-channel, Key-decision makers focus vs multi-threaded. Also, based on your own territory and rules, you can assign each account to the best sales reps, aka the most suited to convert them (using their win rate ratio for this specific industry & company size).

  • Lead nurturing and personalization: After or before a prospecting sequence, you can also decide to nurture the lead, whether to warm them up before getting prospected or to be top of mind when they would be ready to buy. You can also further personalize your messaging and sequences with all the data from your data warehouse.

Sales efficiency:

  • Automation of manual tasks: You can automate slack notifications when a specific behavior occurs, create new sourced accounts in your CRM and auto-assign them using a round-robin process. In Cargo, you have AI integrated, so you can custom-create a cold call script or personalized hook for emails and push it back to your CRM.

  • Integration with other sales and marketing tools: The PRM integrates with other sales and marketing tools, such as customer relationship management (CRM) systems, marketing automation platforms, and email marketing tools. This streamlines the sales process and helps teams to be more productive.

  • Improved visibility into sales pipelines: You can see where leads are in the sequence, and decide to push a slack notification to the sales rep assigned, what actions have been taken, and what the next steps are.

Better data insights

  • Analytics and Reporting: Cargo lets you write back into your data warehouse, and BI tools like Tableau, Metabase or Looker sit directly on top; it means you can run dashboards in a matter of minutes to identify areas for improvement and make data-driven decisions quickly.

Curious how Cargo can let you do revenue orchestration on top of your existing data warehouse?‍

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