Valley

Overview

Category: Autonomous AI SDR Agent (LinkedIn-Specialized) Pricing: From $1,000-1,500/month per agent (estimated) Best For: Sales teams prioritizing LinkedIn outreach with AI-powered autonomous SDR capabilities

Valley is an AI SDR platform that provides autonomous sales agents specializing exclusively in LinkedIn outreach. While similar to competitors like Artisan and 11x in offering end-to-end AI-powered prospecting, Valley differentiates itself with a LinkedIn-only approach—making it particularly effective for B2B sales teams that rely heavily on social selling and LinkedIn Sales Navigator for prospecting.

The platform's key differentiator is pure LinkedIn specialization: Valley's AI agents are optimized exclusively for LinkedIn workflows, including connection requests, profile engagement, InMail campaigns, and multi-touch LinkedIn messaging sequences. This makes Valley the ideal choice for companies whose target audiences are highly active on LinkedIn and responsive to social selling approaches.

Valley's AI SDR agents autonomously execute LinkedIn-only outreach campaigns: identifying target prospects on LinkedIn, engaging with their content, sending personalized connection requests, orchestrating multi-touch LinkedIn sequences, and managing conversations to book qualified meetings—all with minimal human oversight.

How It Works:

1. ICP Definition: Specify target buyer personas (titles, industries, company sizes, LinkedIn activity levels)
2. LinkedIn Prospecting: AI searches LinkedIn Sales Navigator for matches, prioritizing highly engaged profiles
3. Social Engagement: AI interacts with prospect content (likes posts, comments thoughtfully) to build familiarity
4. Connection Requests: Sends personalized LinkedIn connection requests with context
5. Multi-Touch Sequences: Orchestrates LinkedIn messages and InMail in coordinated sequences
6. Conversation Management: Handles initial responses, qualifies interest, routes hot leads to sales reps
7. Meeting Booking: Coordinates calendar availability and books discovery calls

Key Differentiator: Valley's LinkedIn-first architecture means the AI is specifically trained on social selling best practices, LinkedIn engagement patterns, and LinkedIn's evolving automation policies—reducing account restriction risk vs generic AI SDRs that bolt on LinkedIn as an afterthought.

1. LinkedIn-Optimized AI Agents

AI agents specifically trained for LinkedIn prospecting workflows. Understands LinkedIn etiquette (when to connect vs InMail, optimal message timing, engagement before outreach), platform limits (connection requests per week, message frequency), and social selling best practices. Reduces risk of LinkedIn account restrictions common with generic automation tools.

2. Social Engagement Before Outreach

AI strategically engages with prospect content (likes recent posts, leaves thoughtful comments) 1-2 weeks before sending connection requests. Creates familiarity and increases connection acceptance rates from 25-35% (cold) to 45-55% (warmed up via engagement).

3. Multi-Touch LinkedIn Sequences

Orchestrates unified LinkedIn campaigns: Connection request → LinkedIn message (if accepted) → Follow-up message → InMail (if needed). Tracks engagement and adapts timing and messaging based on prospect responsiveness and LinkedIn activity patterns.

4. Personalized Connection Requests

AI crafts unique connection requests referencing LinkedIn activity (recent posts, job changes, shared connections, mutual groups). Goes beyond generic "I'd like to add you to my network" to create context for why you're connecting.

5. Autonomous Lead Qualification

AI handles initial LinkedIn conversations to qualify prospects (BANT, MEDDIC criteria), asking discovery questions and gauging interest level before routing qualified leads to human sales reps with full conversation context.

Valley maps to 4 of 5 GTM stages, with primary strength in Personalization + Orchestration:

Primary Stages

Stage 1: Signal Detection

• LinkedIn activity signals: Recent post engagement, profile updates, job changes
• Company signals: Funding announcements, hiring patterns, growth indicators
• Content engagement: Monitors who views your company's LinkedIn content
• Connection network: Identifies prospects in extended network (2nd/3rd degree connections)

Stage 2: Enrichment

• LinkedIn profile data extraction: Title, company, tenure, education, interests
• Social activity analysis: Post topics, engagement patterns, thought leadership
• Network mapping: Identifies decision-makers and influencers in target accounts
• Profile enrichment: Deep LinkedIn data analysis for targeting and personalization

Stage 3: Personalization ⭐ Primary Strength

• LinkedIn-specific personalization: References posts, comments, shared connections
• Context-aware messaging: Different approaches for cold vs warm connections
• Persona-based messaging: C-suite vs IC, technical vs business buyers
• Dynamic content: Adjusts messaging based on LinkedIn engagement history

Stage 4: Orchestration ⭐ Primary Strength

• LinkedIn sequencing: Optimizes timing and message cadence for LinkedIn outreach
• Social engagement automation: Likes/comments before outreach
• Multi-stakeholder threading: Engages multiple buyers at same account via LinkedIn
• Meeting coordination: Handles back-and-forth to schedule discovery calls

Sends Data To

Valley → Salesforce
└─ "LinkedIn-sourced leads + conversation history → Lead records"

Valley → HubSpot
└─ "Connection acceptances + meeting bookings → Contact timeline"

Valley → Slack
└─ "Qualified lead notifications → #sales channel"

Receives Data From

LinkedIn Sales Navigator → Valley
└─ "Saved searches + lead lists → AI prospecting targets"

Clay → Valley
└─ "Enriched LinkedIn data → Enhanced personalization"

Salesforce/HubSpot → Valley
└─ "Existing contacts for re-engagement campaigns"

Works Alongside

• Wiza/Phantombuster: LinkedIn data scraping → Valley outreach
• Expandi: Some teams use both (Expandi for volume, Valley for high-touch AI personalization)
• Clay: Pre-campaign research → Valley AI execution
• Attention/Gong: Valley books meetings → Call intelligence tools analyze conversations

Native Integrations

• CRMs: Salesforce, HubSpot
• Communication: Slack
• LinkedIn: Sales Navigator (required)
• Calendar: Google Calendar, Outlook Calendar (meeting booking)

Primary Use Case 1: LinkedIn-Only Outbound for B2B SaaS

Problem: Target executives are overwhelmed with cold outreach but highly active on LinkedIn—traditional cold outreach fails

Solution: Valley's LinkedIn-only approach achieves 10-15% response rates through social selling

Example Workflow:

1. Target 200 VPs of Sales at Series B SaaS companies (highly active on LinkedIn)
2. Valley AI engages with their posts for 7-10 days (likes, thoughtful comments)
3. Sends personalized connection requests: "Hi {{firstName}}, noticed your post on pipeline challenges—we help Series B VPs scale from $5M → $20M. Worth connecting?"
4. 55% acceptance rate (vs 30% cold) = 110 new connections
5. Day 3 after acceptance: LinkedIn message referencing shared interest
6. Day 7 if no reply: Follow-up message with case study
7. Day 14 if no reply: InMail with relevant resource
8. Result: 20-25 positive replies (15-20% response rate) → 6-8 meetings booked

Results: 6-8 meetings from 200 prospects (3-4% meeting rate) through LinkedIn-only approach

Primary Use Case 2: Multi-Stakeholder Account Penetration

Problem: Enterprise deals require engaging 6-8 stakeholders across departments—reaching multiple buyers is challenging

Solution: Valley identifies and engages multiple LinkedIn profiles at target accounts simultaneously

Example Workflow:

1. Target 50 enterprise accounts ($100M+ revenue companies)
2. Valley maps LinkedIn profiles: CTO, VP Engineering, Director DevOps, Security Lead per account (4 contacts × 50 = 200 prospects)
3. Personalized outreach per role:
   • CTO: ROI focus, board-level metrics
   • VP Engineering: Technical architecture, scalability
   • Director DevOps: Implementation ease, team efficiency
   • Security: Compliance, SOC 2, GDPR
4. Valley coordinates timing: Connect with CTO first → Reference CTO connection when reaching Director
5. Multi-threading creates internal buzz: "4 people from [company] connected with me this week about [solution]"
6. Result: 40 of 50 accounts have 2+ engaged stakeholders → 12 enterprise meetings booked

Results: 12 enterprise meetings from 50 accounts (24% account penetration) through coordinated LinkedIn outreach

Primary Use Case 3: Post-Event LinkedIn Nurture

Problem: Collected 300 business cards at conference—generic follow-up outreach gets low response rates

Solution: Valley nurtures via LinkedIn social engagement before asking for meeting

Example Workflow:

1. Connect with 300 conference attendees on LinkedIn (manual or via Valley automation)
2. Valley AI monitors their LinkedIn activity for 2-3 weeks post-event
3. When prospect posts, Valley likes and comments: "Great point about [topic]—we discussed this at [conference]"
4. After 3-4 engagement touches, Valley sends message: "Been following your posts on [topic]. Based on our [conference] conversation, would love to show you how we're solving [pain point]. 15 min next week?"
5. Warmed-up approach achieves 25-30% meeting booking rate through social engagement
6. Result: 75-90 meetings from 300 attendees

Results: 75-90 meetings (25-30% rate) through LinkedIn nurture approach

Secondary Use Case 1: LinkedIn Thought Leadership + Outbound

Run Valley to engage with target prospects' posts while you publish thought leadership content. Prospects see your name in their notifications (liking/commenting), then see your content in feed—creates familiarity before connection request.

Secondary Use Case 2: Competitive Replacement Campaigns

Target customers of competitors on LinkedIn. Valley engages with their posts complaining about [competitor], then reaches out: "Saw your post about challenges with [competitor]. We help former [competitor] customers like [client logo] achieve [outcome]. Worth a conversation?"

Pricing Model

Valley uses custom pricing (estimated based on market positioning):

Pricing Notes

• Annual Contracts: Typically requires 12-month commitment
• LinkedIn Sales Navigator Required: Additional $80-135/mo per seat
• Includes: LinkedIn outreach, AI personalization, meeting booking
• Training Period: Budget 2-3 weeks initial setup and training

Cost Calculator Examples

SMB (1 Valley Agent)

• 1 agent @ $1,250/mo (estimated) = $15,000/year
• Sales Navigator @ $80/mo = $960/year
• Total: $15,960/year
• Replaces: 2 human SDRs @ $120K = $240K/year
• Savings: $224K/year (93% cost reduction)

Mid-Market (3 Valley Agents)

• 3 agents @ $1,200/mo each (volume discount) = $43,200/year
• Sales Navigator @ $135/mo (Advanced) = $1,620/year
• Total: $44,820/year
• Replaces: 6 human SDRs @ $360K total
• Savings: $315K/year (88% cost reduction)

ROI Calculation

• Cost per meeting: $15K/year ÷ 100 meetings = $150/meeting
• vs Human SDR: $60K/year ÷ 40 meetings = $1,500/meeting (10x more expensive)
• Payback: 8-12 closed deals covers annual Valley subscription

5-Step Implementation Guide

Step 1: Prerequisites & Demo (1-2 weeks)

• Subscribe to LinkedIn Sales Navigator ($80-135/mo)
• Schedule Valley demo (no self-service signup)
• Negotiate pricing and contract terms
• Provision LinkedIn accounts (2-3 dedicated accounts recommended)
• Pro Tip: Use separate LinkedIn profiles vs personal/company profiles to reduce restriction risk

Step 2: ICP & Messaging Setup (Week 1)

• Define target personas with LinkedIn-specific criteria (engagement levels, post frequency)
• Upload messaging framework: Value props, pain points, LinkedIn tone/voice
• Provide 10-20 examples of successful LinkedIn conversations
• Configure engagement rules: Which types of posts to engage with, comment guidelines
• Pro Tip: Study target prospects' LinkedIn activity first week to understand engagement patterns

Step 3: Training & Calibration (Weeks 2-3)

• Valley AI generates initial connection requests and messages for review
• Daily review: Approve/edit AI outputs, provide feedback on tone and personalization
• Test social engagement: Verify AI comments are thoughtful and relevant (not spammy)
• Monitor connection acceptance rates: Target 40-50% acceptance
• Pro Tip: Start with 25-50 connection requests/week during training (scale after validation)

Step 4: Launch LinkedIn Sequences (Week 4)

• Enable LinkedIn sequences after validating social engagement approach
• Monitor engagement: Track which prospects respond to different message types
• Set up meeting booking automation with calendar integration
• Configure lead routing: Qualified leads → Slack → Sales rep assignment
• Pro Tip: Keep sequences short (3-4 touches) initially; extend after proving engagement

Step 5: Scale & Optimize (Ongoing)

• Increase daily outreach: 50/day → 100/day → 150/day as acceptance rates hold
• A/B test messaging: Different connection request angles, message timing
• Analyze performance by persona: Which ICPs respond best to LinkedIn outreach?
• Add additional AI agents for different regions or ICPs
• Pro Tip: Weekly review of LinkedIn account health; pause if restriction warnings appear

Common Mistakes to Avoid

• ❌ Sending 100 connection requests Day 1 → LinkedIn restriction (warm up slowly!)
• ❌ Generic connection requests ("I'd like to add you") → Low acceptance (always personalize)
• ❌ Skipping social engagement phase → Cold outreach = 25-35% acceptance vs 45-55% with warmup
• ❌ Using personal LinkedIn profile → Risk to professional brand (use dedicated accounts)
• ❌ Ignoring LinkedIn health signals → Account warnings escalate quickly
• ❌ Not training AI on your brand voice → Generic "AI-written" messages damage credibility

Official Resources

• Valley.ai: Product overview, demo request
• LinkedIn Sales Best Practices: Valley blog on social selling strategies
• AI SDR Guides: How autonomous AI SDRs work, ROI calculations

Our Resources

• Valley + Clay Integration Guide: Pre-campaign LinkedIn research → Valley AI execution
• LinkedIn-Only vs Multi-Channel Comparison: When to use Valley vs Artisan
• Social Selling Playbook: How to warm up prospects before connection requests
• Multi-Stakeholder ABM Workflows: Engaging 3-5 buyers per account on LinkedIn
• LinkedIn Account Safety Guide: Reducing restriction risk with AI automation

Works Best With

1. LinkedIn Sales Navigator - Required for Valley (provides prospecting data)
2. Clay - Pre-campaign research enrichment → Valley AI execution
3. Attention/Gong - Valley books meetings → Call intelligence analyzes conversations
4. HubSpot/Salesforce - CRM for lead tracking and pipeline management

Recommended Stacks

Stack 1: LinkedIn-Only Outbound

• Valley (1 agent) ($1,250/mo) - LinkedIn AI outbound
• Sales Navigator ($135/mo) - LinkedIn prospecting data
• HubSpot Sales Pro ($90/user × 3 = $270/mo) - CRM
• Total: $1,655/month vs $180K/year for 3 human SDRs

Stack 2: Hybrid AI + Human

• Valley (1 agent) ($1,250/mo) - Top-of-funnel prospecting
• Human SDR ($60K/year = $5,000/mo) - Qualification only
• Clay ($149/mo) - Pre-campaign research
• Total: $6,399/month for hybrid approach

Stack 3: Multi-Channel AI Stack

• Valley ($1,250/mo) - LinkedIn-only
• Artisan ($1,500/mo) - Multi-channel capabilities
• Salesforce ($200/user × 5 = $1,000/mo) - CRM
• Total: $3,750/month covering multiple channels with full AI autonomy

Integration Partners

• LinkedIn: Sales Navigator (required), Recruiter
• CRM: Salesforce, HubSpot, Pipedrive
• Enrichment: Clay, ZoomInfo, Apollo
• Meeting: Google Calendar, Outlook, Calendly
• Communication: Slack

This profile was compiled from:

• Valley.ai mentions in GTM tools database
• Comparison analysis vs Artisan, 11x, Expandi
• AI SDR category research and market positioning
• User feedback patterns from AI SDR platforms
• LinkedIn automation best practices
• Social selling methodology research

Last Updated: March 2025 Profile Completeness: 15/15 sections ✅