# Dale W. Harrison

Dale W. Harrison works on B2B marketing and sales effectiveness. In a LinkedIn post, Harrison describes the role as Head of Strategy at The Insight Collective and co-hosts a series about B2B sales, marketing, and revenue growth.

- Profile: https://b2binfluencer.marketing/creators/dale-w-harrison/
- LinkedIn: https://www.linkedin.com/in/dalewharrison
- LinkedIn followers: 29,813
- Topics: sales, b2b-marketing, revenue-operations, marketing-measurement
- Based on 22 dated posts, latest 2026-10-08

## Summary

Most useful for pressure-testing B2B metrics like ICP, lead scoring, pipeline velocity, and sales-marketing alignment.

- Best for: B2B SaaS or B2B technology brands improving lead scoring, pipeline velocity, and sales-marketing alignment.
- Not for: Consumer apps, fitness, Gen Z install campaigns, or short-form entertainment video.
- Check first: Confirm episode calendar, pricing, deliverables, and audience role data before committing.

### Takeaways

- Compare wins with losses before treating a customer trait as predictive.
- Buyer fit includes whether the seller can win and serve the account.
- Check the distribution of deal durations instead of relying on averages.

## Main ideas

- **Compare wins with losses before calling a customer trait predictive**: Harrison argues that a trait shared by customers is not automatically useful for finding more customers. It matters only if it helps distinguish wins from losses. They connect this to information theory: a data point is informative when it changes what you can infer about an outcome.
- **Buyer fit includes whether the seller can win and serve the account**: A company being in-market for a product category does not mean it will buy from a particular vendor. Harrison adds the seller’s market position, product readiness, and ability to sell into the account to the usual question of buyer intent.
- **Treat pipeline metrics as evidence to examine, not facts to trust**: Harrison warns that CRM time-in-pipeline can be distorted by how deals are entered, kept open, or measured. Reps rewarded for pipeline value may leave stalled opportunities open; incentives around win rates may lead teams to enter deals late. They recommend examining deal-duration distributions and incentives before using sales-cycle averages as a measure of effort.
- **Ask whether a metric changes the chance of reaching revenue**: Harrison questions reporting that stops at impressions, clicks, MQLs, or pipeline generated. Their proposed test is whether a measure helps explain the probability of revenue reaching the business. They also argue that revenue-efficiency analysis should include lost deals, because the sales effort spent on a loss still has a cost.
- **Explain sales-marketing friction through wasted time and blame**: Harrison frames marketing as trying to avoid blame for weak results and sales as trying to avoid regret over time spent on leads that will not buy. Their proposed bridge is account scoring based on demonstrated results that helps prioritize prospects with a better chance of becoming revenue.

## Work to read

- [Build an ICP by comparing wins with losses](https://www.linkedin.com/posts/dalewharrison_%F0%9D%AC%AC%F0%9D%AD%82%F0%9D%AD%85-%F0%9D%AD%84%F0%9D%AD%82%F0%9D%AD%87-%F0%9D%AD%83%F0%9D%AD%82%F0%9D%AD%85-%F0%9D%AD%83%F0%9D%AD%87%F0%9D%AD%82%F0%9D%AD%83%F0%9D%AD%83%F0%9D%AD%82%F0%9D%AD%87%F0%9D%AD%82%F0%9D%AD%87%F0%9D%AD%82%F0%9D%AD%87%F0%9D%AD%82%F0%9D%AD%87-activity-7500608389555769346-Z0wZ)
- [Buyer-seller fit: the ICP is not necessarily your ICP](https://www.linkedin.com/posts/dalewharrison_buyer-seller-fit-the-icp-is-not-necessarily-activity-7465824771499376640-GjVO)
- [What sales-effort metrics can hide](https://www.linkedin.com/posts/dalewharrison_%F0%9D%97%95%F0%9D%9F%AE%F0%9D%97%95-%F0%9D%98%83%F0%9D%98%83%F0%9D%97%B2%F0%9D%97%B0%F0%9D%98%81%F0%9D%97%B6%F0%9D%98%83%F0%9D%97%B2%F0%9D%97%BB%F0%9D%97%B2%F0%9D%98%80%F0%9D%97%B5%F0%9D%97%BC%F0%9D%98%84-activity-7495146005835710464-23Vq)
- [Use deal duration to spot possible zombie deals](https://www.linkedin.com/posts/dalewharrison_%F0%9D%97%9C%F0%9D%98%81-%F0%9D%97%A7%F0%9D%97%AE%F0%9D%97%B8%F0%9D%97%B2%F0%9D%98%80-%F0%9D%9F%AF-%F0%9D%97%A7%F0%9D%97%B6%F0%9D%97%BA%F0%9D%97%B2%F0%9D%98%80-%F0%9D%97%AE%F0%9D%98%80-%F0%9D%97%9F%F0%9D%97%BC%F0%9D%97%BB-activity-7495890107971862528-krgS)

## Brand relationships

- **The Insight Collective** (employment)
- **Next-Gen MQL** (disclosed_partnership)

## Partnerships

Dale W. Harrison's LinkedIn Live series carries a named sponsor, The Insight Collective, where they work as Head of Strategy. Episode announcements credit the sponsor in the post text and describe its business as lead generation for B2B technology brands built on marketing science and marketing effectiveness. The series is co-hosted with other practitioners and features outside guests, so the sponsor appears alongside named hosts and guests rather than owning an entire run. Episodes are analytical and data-led, written for B2B sales, marketing, and finance readers; any sponsor message has to fit that editorial frame. Ask the sponsor directly for a rate card, package tiers, audience specifications, and an inquiry route.

## Alternatives

- Omprakash Karuppanan: For the same B2B SaaS lead-scoring brief, Omprakash Karuppanan is the stronger choice when the buyer needs an operator to build and run AI-assisted ABM execution in HubSpot or Salesforce, especially to diagnose stalled mid-funnel deals. The published posts describe Claude skills for deal reporting, audience targeting, account research, field marketing, and stall diagnosis. The stall-diagnosis post names buying-committee gaps, champion silence, unacted triggers, and sequence fatigue as ranking factors. That fits a company that accepts the lead-scoring concepts and needs a working pilot to read call transcripts, CRM outcomes, and engagement data to surface stalled accounts. They also state that they run ABM execution programs for enterprise SaaS and IT services companies, which is closer to implementation than commentary.
- Brigitta Ruha: Brigitta Ruha is the stronger alternative when the same B2B SaaS need is owned by a founder or GTM leader who wants a staged operating plan and a repeatable AI lead-gen workflow. One post lays out rules by ARR band from $0-1M to $25M+, including when to score ICP with signals rather than firmographics, when to add SDRs and ABM, and what to watch in CAC payback and NRR. The second post describes a lead-gen system that compares closed-won and closed-lost deals in Claude, requires at least two buying signals, and turns research into personalized outreach. For a company that needs the workflow and stage-specific rules to make lead scoring repeatable, that is more directly actionable than a conceptual framework.
- Victor Adolph: Victor Adolph is not a better choice for the stated B2B SaaS lead-scoring and pipeline-velocity need. He becomes relevant only if the campaign decision shifts to e-commerce growth measurement: which KPIs to track and how to structure demand capture. The posts argue that ratios such as conversion rate and revenue per visitor beat absolute numbers like revenue and clicks. They also describe a monthly push-and-pull cycle for a seven-figure e-commerce brand, with a demand-capture sale followed by a design drop to returning customers. For a DTC or Shopify operator wanting to test spend and measure performance with ratios, that is a clearer fit.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/