What are the responsibilities and job description for the Head of Customer Success position at Truthset?
Customer Success & Solutions Engineer
Full-Time | Customer Success / Sales Engineering | Remote or Hybrid
About Truthset
Truthset is the industry leader in consumer data accuracy scoring, providing the ecosystem with transparent, objective, and independent validation of demographic and identity datasets. Our mission is to help advertisers, agencies, platforms, publishers, and data providers make better decisions by understanding the accuracy of the data they rely on every day.
With partnerships across major identity providers, data suppliers, activation platforms, and measurement solutions, Truthset is the standard for improving customer acquisition, retention, and performance through high-quality consumer data.
About the Role
We’re hiring a hybrid Customer Success Sales Engineering professional to play a central role in helping clients understand, adopt, and realize measurable value from Truthset’s Data Accuracy Scores, Data Clean Room integrations, and audience activation solutions.
This is a strategic, customer-facing role that blends relationship management, technical consultation, data analysis, and domain expertise in the digital marketing and identity ecosystem.
Key Responsibilities
Customer Success – Drive Adoption & Measurable Value
- Serve as the primary post-sales point of contact for advertisers, agencies, platforms, and data partners using Truthset’s data accuracy products.
- Lead onboarding across:
- Data provider scoring
- Advertiser & agency audience quality evaluation
- Identity partner integrations
- Platform workflow implementations (e.g., Databricks, Snowflake, clean rooms, DSPs)
- Translate customer objectives (e.g., improve demographic accuracy, reduce waste, validate audience segments, optimize acquisition) into strategic success plans.
- Build customer-facing analyses and reports that highlight Truthset value including:
- Audience quality insights
- Supplier benchmarking
- Quarterly Business Reviews (QBRs)
- Pre-/post-activation diagnostics
- Proactively identify product expansion opportunities across additional datasets, media channels and integrations.
Sales Engineering – Technical Discovery, Solution Design & Demo Support
- Support the sales cycle with technical discovery, solution architecture, and compelling product demos.
- Act as the subject-matter expert on digital identity, demographic data, audience activation, attribution, and measurement.
- Design customer-specific integrations, workflows, and data schemas that support use cases across the marketing ecosystem.
- Evaluate the customer’s martech/adtech environment (DSPs, CDPs, MMPs, CRM systems, identity partners) to recommend optimal deployment strategies.
- Explain Truthset methodologies (panel-based scoring, ground truth alignment, demographic attribute scoring, etc.) to both technical and non-technical stakeholders.
- Demonstrate Truthset capabilities in terms of:
- Audience scoring
- Data provider evaluation
- Activation and planning workflows
- Cross-platform integrations (CDPs, clean rooms, DSPs, data marketplaces)
- Build proof-of-concepts using customer data to illustrate accuracy lift, ROI impact, and data improvement strategies.
- Advise on integration best practices, including file formats, ID handling, match keys, and secure data collaboration.
Cross-Functional Collaboration
- Work with Product & Engineering to influence roadmap priorities based on customer feedback and emergent market needs.
- Troubleshoot data ingestion, scoring workflows, and platform integrations.
- Develop reusable onboarding templates, integration documentation, and data interpretation guides.
Required Skills & Experience
- 4–8 years in Customer Success, Sales Engineering, Solutions Consulting, or Technical Account Management, ideally within adtech or martech.
- Deep understanding of:
- Demographic and consumer data
- Identity & resolution ecosystems (MAIDs, hashed emails, PII, offline/online linkage)
- Audience activation workflows (DSPs, DMPs, CDPs, marketplaces)
- Data quality evaluation, measurement, and benchmarking
- Ability to interpret and communicate Truthset scoring methodologies, match rates, overlap analysis, and attribute-level accuracy.
- Strong analytical skills with comfort handling large datasets and communicating insights.
- Track record of building strong, trusted customer relationships that lead to renewal and expansion.
- Excellent communication and presentation skills across executive, analyst, and technical audiences.
Nice-to-Have
- Familiarity with Truthset-supported environments (Databricks, Snowflake, DSPs, clean rooms).
- SQL experience for deeper analysis or data validation.
- Understanding of privacy frameworks and consented data collection practices.
- Background working with data providers, data marketplaces, or identity solutions.
Success in This Role Looks Like
- Customers routinely use Truthset scores to optimize audience strategies, improve data selection, and differentiate their datasets.
- Data partners achieve measurable accuracy improvements and adopt Truthset as part of their go-to-market strategy.
- Sales cycles accelerate due to strong technical discovery, compelling demos, and impactful POCs.
- Expansion and renewals improve because of high adoption, clear ROI, and trusted relationships.
- The broader ecosystem recognizes Truthset as an indispensable component of the customer’s data and identity workflows.