Sales Role (Multiple Openings)

Overview

You'll be selling Hightouch's data activation platform to enterprise marketing and data teams. The product syncs customer data from data warehouses (Snowflake, Databricks, BigQuery) into 250+ marketing and sales tools. Your buyers are typically marketing ops leaders, data engineers, and CMOs at mid-market to enterprise B2C and B2B companies.

Role Snapshot

Company Context

Stage: Series C+ (503 employees suggests well-funded)

Size: 503 employees

Growth: Hiring across all functions, ranked #8 on Forbes Best Startup Employers list

Market Position: Strong player in the Composable CDP space, competing against Segment, mParticle, Census, and traditional CDPs like Salesforce CDP

GTM Reality

Pipeline Sources:

• ~40% Inbound - Companies actively looking for CDP/data activation solutions, likely some free trial or POC conversions given product-led signals
• ~40% Outbound - Targeting companies with data warehouses who are struggling with data activation
• ~20% Partners/Referrals - Likely partnerships with Snowflake, Databricks, and consulting firms

SDR/AE Structure: Likely dedicated SDR team given company size (500+ employees)

SE Support: Almost certainly have Solutions Engineers given technical product and enterprise focus

Competitive Landscape

Main Competitors: Segment (Twilio), mParticle, Census, Rudderstack, traditional CDPs (Adobe, Salesforce), reverse ETL tools

How They Differentiate: "Composable CDP" positioning - sits on top of your existing data warehouse vs. proprietary data store. More flexible than traditional CDPs, less engineering-heavy than pure reverse ETL.

Common Objections: "Can our data team just build this?" / "We already have Segment" / "Is this really different from Census?" / Pricing concerns at enterprise scale

Win Themes: Speed to value, warehouse-native architecture, marketing team autonomy, 250+ integrations, AI/personalization capabilities

What You'll Actually Do

Time Breakdown (varies significantly by role)

If SDR/BDR: Prospecting (60%) | Qualification Calls (25%) | Internal/Admin (15%)

If AE: Active Deals (45%) | Prospecting/New Pipeline (30%) | Internal (25%)

If AM/CSM: Account Management (50%) | Renewals/Expansions (30%) | Internal/Product Feedback (20%)

Key Activities (AE perspective)

• Discovery calls with marketing ops and data teams: You're diagnosing their current data activation setup - what tools they use, what's manual, what's breaking, what use cases they want to enable. These calls are technical; you need to understand data warehouses, ETL/reverse ETL, and marketing automation platforms.
• Multi-threaded enterprise sales: You're coordinating between marketing buyers (who want the features), data/engineering teams (who need to approve the technical architecture), and procurement/security. Getting all three aligned takes time.
• Demo and POC coordination: Working with SEs to show how Hightouch syncs data from their warehouse to their specific tools. POCs often involve actual data integration, so there's technical risk and timeline slippage.
• Competitive displacement: Many prospects already have some data activation solution (Segment, homegrown scripts, basic integrations). You're convincing them to rip and replace or run parallel systems.

The Honest Reality

What's Hard

• Technical sales complexity: You're selling to both business and technical buyers. Marketing loves the use cases but engineering might push back on "another tool" or argue they can build it themselves. You need to be credible in both conversations.
• Long, multi-stakeholder cycles: Even mid-market deals involve marketing, data engineering, IT security, and procurement. Enterprise deals can drag 6-9 months with multiple false starts and stalled champions.
• Competitive and crowded space: The CDP/data activation category is hot but noisy. Prospects are confused about the differences between Segment, Census, Hightouch, and building internally. You'll spend a lot of time positioning and differentiating.
• POC dependency: Many deals require technical POCs where prospects test the product with their actual data. These can uncover unexpected technical issues or just take forever to complete.

What Success Looks Like

• Consistently building pipeline from both inbound leads and self-sourced outbound
• Running 8-12 active mid-stage opportunities at once without dropping balls
• Closing 60-70% of deals that reach POC stage
• Keeping sales cycles under 4 months for mid-market, under 6 for enterprise

Who You're Selling To

Primary Buyers:

• VP/Director of Marketing Operations (economic buyer)
• Head of Data Engineering / Analytics Engineering (technical validator)
• CMO or VP Growth (enterprise deals, strategic buyer)
• RevOps leaders (B2B companies)

What They Care About:

• Marketing: Speed of campaign execution, personalization capabilities, reducing dependency on engineering for data requests
• Data/Engineering: Scalability, data governance, not maintaining brittle custom integrations, leveraging existing warehouse investment
• Executive: Customer experience improvement, marketing efficiency, competitive advantage from better personalization

Requirements

• Experience selling B2B SaaS to marketing and/or data teams
• Understanding of marketing technology stack (CRMs, marketing automation, advertising platforms)
• Some familiarity with data concepts (warehouses, ETL, APIs) - you don't need to be technical but can't be intimidated by it
• Comfortable with consultative, multi-stakeholder enterprise sales
• Track record of hitting quota in 3-6 month sales cycle environment
• Strong at building champions and navigating organizations