What's up, it's Zayd.

These days, you can know everything about a prospect before you've ever spoken to them. Their tech stack, hiring patterns, funding history, content engagement, coffee preferences...probably. That said, response rates are at historic lows.

This seems backwards. Better information should lead to better conversations. Instead, we're drowning in data points and starving for actual insights.

It's like having a GPS that tells you the exact longitude and latitude of every palm tree on the 101, but not where you actually need to turn.

Forwarded this email? Get Enabled in your inbox each week.

Zayd’s Picks

My favorite finds of the week

• Not doing this kills your deliverability (link)

• Top 10 resources for early-stage founders (link)

• Tech stack for $10m in pipeline (link)

• SaaS pricing is shifting (link)

• Free sales training from a $30k/year mastermind (link)

• Expert framework for scaling SaaS products to 7-figures (link)

• Secrets to structure and present SaaS pricing (link)

The Data Collection Hamster Wheel

The insidious thing about sales data is that collecting it feels productive.

You're researching.

You're being thorough.

You're leaving no stone unturned.

…kinda

Meanwhile, your competitor sent a simple, relevant message and booked the meeting while you were still analyzing the prospect's LinkedIn engagement patterns.

The average B2B prospect has 47 different data points collected about them before first contact, but when you ask reps what they learned, they give you generic insights like "they're growing fast" or "they probably need our solution."

The Three Stages of Signal Pollution

Stage 1: Data Addiction 

"We need more information to be effective!" Teams add tool after tool, each promising to provide the missing piece of the puzzle.

Stage 2: Analysis Paralysis 

Reps spend more time processing data than actually talking to prospects. The perfect message becomes the enemy of the good message.

Stage 3: Generic Personalization 

Ironically, having too much data leads to more generic outreach. "I see you hired 3 engineers" becomes the new "hope this email finds you well."

The Information Processing Reality

Humans can effectively process about 7 pieces of information simultaneously. Psychology 101 (yeah, I went to a semester of college once). Yet the average sales platform presents 15-20 data points per prospect. We're literally overwhelming our own cognitive capabilities, then wondering why our outreach feels scattered.

Signal vs. Noise: A Simple Framework

Not all prospect data is created equal. Here's how I think about it:

Tier 1: Action Triggers

• Recent job changes

• Company funding/acquisition news

• New product launches

• Regulatory changes affecting their industry

• Direct website visits to pricing pages

These suggest immediate need and perfect timing.

Tier 2: Context Builders

• Industry trends

• Competitive moves

• Leadership changes

• Technology implementations

Useful for conversation context, but shouldn't drive timing.

Tier 3: Background Noise

• Company size

• General tech stack

• Historical funding

• Basic demographics

Good for qualification, but if this is your personalization angle, you're not really personalizing.

How We Approach Research at Valley

We built Valley to focus on three layers that actually matter:

Individual Level: What has this person shared publicly that reveals their current challenges?

Company Level: What specific events or changes create urgency for solutions like ours?

Industry Level: What trends are affecting their business that we can help them navigate?

Three layers. Deep research on each. No noise.

The Anti-Overwhelm Process

Here's what actually works for prospect research:

Define the Hypothesis First: Before researching, ask "What would make this prospect need our solution right now?" Then only collect data that proves or disproves this.

Three-Point Rule: Limit yourself to three key insights per prospect. If you can't identify three compelling points, they're probably not worth pursuing right now.

Connect the Dots: Multiple data points should tell a coherent story about their situation. Random facts aren't insights.

Test the Insight: Can you state your understanding in one clear sentence? If not, you need to keep synthesizing.

What High-Performing Reps Actually Do

After working with hundreds of sales teams, the best reps share these habits:

They ignore demographic data entirely They focus on recent events and changes They look for patterns across multiple prospects in the same industry They spend 80% of research time understanding the problem, 20% on the person.

The worst reps do the opposite: 80% on the person's background, 20% on whether they actually have a problem worth solving.

How I Can Help?

Let me book sales calls for you while you’re filtering signal from noise. Seriously.

I built Valley to be your automated SDR and empower AEs. Get started today and watch your calendar fill up with qualified leads.

How can we work together 🏔️

1. See more of Valley’s messaging examples, feel free to roast them: https://withvalley.notion.site/Cool-Message-Bro-1c0b917b0ed481dab014c465c354b4b8 

2. Generate more demos for your company using LinkedIn: https://meetings.hubspot.com/zayd-from-valley/tryvalley
   

3. Become a Valley partner and get 20% recurring commission for every user you bring in: https://withvalley.notion.site/valley-affiliate-partner-program