The rise of signal-based partner management

You’ve heard of 10x developers—those whose productivity skyrockets tech teams.

But what about a 10x partner manager? Imagine a partner manager who activates 10x more partners and sources 10x more revenue than their peers.

With automation and AI, we’ll be seeing partner management outliers who outperform and exceed revenue expectations.  

Saving just 50 minutes a day with automations translates to about 10% of their time.

But the productivity gain is nonlinear. Automation allows partner managers to parallelize their work—engaging 10 different partner contacts simultaneously rather than just one.

I believe that those who leverage this parallelization properly and without losing the human touch will drive up to 10x more leads and revenue.

The rise of signal-based partner management

Data is the lifeblood of any GTM team. It’s what makes them more focused and effective.

Signal-based prospecting is already a game-changer in sales, using data like job changes or website activity to target prospects precisely and drive better results (due to increased relevance).

The same principles apply to partnerships.

The old way vs. the new way

Old way: Respond to the loudest voices, your favorites, or those partners you think might be helpful.

New way: Use technology to scan a broad range of signals and engage the right people at the right time.

Hidden gems: Data you might be overlooking

You probably have a wealth of unused data. Tap into:

  • Website visits
  • Marketing content engagement
  • Portal or LMS logins (e.g. into Salesforce PRM, PartnerStack, Allbound, Magentrix etc.)
  • Sandbox or tool logins
  • Marketplace activity (visits, leads, clicks e.g. via Partner Fleet)
  • Certifications
  • Individual lead submissions
  • Overlap account ownership (Crossbeam & Reveal data)
  • Last interaction or interaction frequency
  • and many more

Combine these signals with company-level data to power up your partner engagement strategy.

Prioritize and segment for success

Not all signals are created equal. Prioritize based on:

  • Partner type
  • Partner tier
  • Job title or role in the partnership

And remember: A lack of signals is also a signal. If someone stops engaging, it’s time to reconnect. For instance, Salesforce tracks the last activity date. If an active contact goes silent for six months, don’t let them slip away—reach out and re-engage!

Leveraging your existing data

Many companies love the idea of signal-based partnering but feel unprepared due to a perceived lack of data. In reality, you likely have more data than you realize. And adding missing fields to Salesforce is often simpler than expected.

Warning: This list of data points is quite extensive, and you don't need all of them to get started. In fact, standard SFDC fields are often sufficient for many powerful use cases.

Select SFDC fields for signal-based partnering

Accounts:

  • Partner type (e.g., “Agency”, “Tech partner”)
  • Partner tier
  • Partner stage (e.g., NDA signed or Account mapping initiated)
  • Last lead submission date
  • Last QBR
  • Last enablement session
  • Last 30 days marketplace views

Contacts:

  • Primary contact (checkbox)
  • Role or job title (e.g., “Partner manager”)
  • Last activity date*
  • Contact created date*
  • Last portal (or LMS) login
  • Certifications completed
  • Last lead submitted date
  • Last website visit

Opportunities:

  • Sourcing Partner Account
  • Influencing Partner Account
  • Sourcing Partner Contact
  • Influencing Partner Contact
  • Deal stage*
  • Date of last stage change*
  • Deal value*
  • Renewal date

Custom Objects:

  • Partner Opportunity object (which would include various fields, incl. the ones listed under Opportunities)
  • Crossbeam or Reveal custom objects
  • ACE
  • Tackle, Workspan, or Suger custom objects

* These are standard fields so you already track them.

By embracing signal-based partner management and optimizing your Salesforce data, you can transform your partnership strategy and drive significant revenue growth. Don’t let valuable data sit unused—harness these signals rather than following your gut.

Reality check: What the experts think

"Maximizing efficiency is increasingly critical to achieving significant impact, especially given the lean structure of many partnership teams. There is a wealth of partner engagement data at our fingertips that has been historically untapped. By leveraging this data, we can strategically create touch points throughout the partner lifecycle, enabling us to collaborate effectively with our partners at scale. This approach not only ensures our interactions are personalized, timely, and seamlessly automated, but also allows our Partner Managers to focus their valuable time on what is most impactful."
- Rachel Grosh, Head of Partner Experience & Programs at Udemy

"At Netlify, signal-based partnering is a game-changer. Through automation, our partner managers can engage the right partners at the perfect time. This means we can activate more partners and drive higher revenue with less effort. Embracing this approach makes partnership management more efficient and impactful."
- Brittany Givens, Sr. Partner Development Manager at Netlify

“There’s a lot of buzz about signal-led sales. Partner signals are just as important as, if not more of a priority than, other signals that exist today. The challenge is that 3rd party data signals are generic and wide-sweeping, usually not indicating buying intent. Further, it’s heavily limited in the technographic area. First-party data is OK, but limited to what you are collecting, which has too much variance and is harder to scale. Second-party data - from partners - is perhaps the biggest unlock to understand buying power, actual decision makers (relevant to your business), and technographic information (down to module + health scores) that are otherwise nearly impossible to know and understand and collect.”
- Will Taylor, Head of Nearbound Partnerships at Reveal

"Signal-based partnering has the potential to revolutionize the way partner managers operate by leveraging a specific set of actual intent data to drive precision and efficiency as it relates to revenue. By harnessing these signals partner managers can prioritize and segment the outreach more effectively. This approach, amplified by automation and AI, allows managers to engage multiple partners simultaneously, resulting in exponential productivity gains. The challenge has always been how to implement partner data, strategy and tactics into your field teams daily activities, embracing signal-based partnering allows you to do just that and drive significant growth in partnerships and revenue."
- Jason Yarborough, Co-Founder at Arcadia
👉 Jason is also the organizer of the hottest Anti-Conference for Ecosystem and Revenue Leaders, so check out ALX.

“In today's dynamic business environment, the power of partnerships is increasingly evident. Collaborating and co-selling with partners offers significant revenue opportunities, but true success hinges on mastering the use of captured data to drive automation in these relationships.”
- Kristine Stewart, Senior Partner Evangelist at Spur Reply

"After having access to Superglue for less than a month, my productivity is going through the roof. I realize now just how many contacts I wasn't touching base with. Trying to personalize every message and keep track of my last touch points was a nightmare, let alone trying to remember what conversations I need to have with which people. The only downside to implementing and using Superglue is that you realize how many relationships you've had to let slip due to time constraints."
- Devon Boyd, Channel & Alliances Director, EMEA at AB Tasty

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