UX research to transform ServiceNow’s Sales Success Center (SSC) from a search pain point into a trusted, AI-assisted workspace by validating the value of “Aura” for faster discovery, smarter customization, and higher confidence.
Role: Senior UX Researcher
When: July–Aug 2025
Audience: SDR [Sales Development Reps], AE [Account Executives], SC [Solution Consultants]
Methods: Concept walkthroughs, screen share sessions
Participants: 12 across AMS, EMEA, APAC
Overview
The Sales Success Center (SSC) is ServiceNow’s internal hub for discovering and sharing approved, customer-facing content. While SSC is trusted, users reported friction finding up-to-date materials quickly enough for dynamic sales conversations. This study examined how sales roles discover, evaluate, and customize content, and tested whether integrating “Aura” (AI) could meaningfully improve speed and trust.
Roles covered: 4 SDR, 5 AE, 3 SC
Artifacts: Capability Map, Pricing & Packaging, First-Call decks
Regions: AMS, EMEA, APAC
Challenge
- Search sessions stretched to 10–15 minutes due to scattered results and inconsistent metadata.
- Users downloaded decks for speed, fragmenting version control and creating duplication.
- Customization work happened offline; localized needs (e.g., APAC) weren’t well supported.
- Workflows were split across SSC, Outreach, and MyAssist, reducing continuity and confidence.
“If I can’t find it fast, I just pull slides from an old deck.” — AE, EMEA
Pre-Interview Data Analysis
Before conducting user interviews, I analyzed SSC system logs to uncover patterns in search usage. The data showed that 62% of searches were ’empty’—users initiated a search by simply hitting enter without typing any keywords. In contrast, only 38% of searches used specific terms. This surprising ratio highlighted a strong reliance on browsing over targeted searching, shaping both my interview questions and the design of the AI prototype tested later.
Approach
- Ran 12 remote, 45-minute concept walkthroughs with live screenshare.
- Participants compared current SSC to an AI-enabled prototype, narrating their search logic, filters, and content assembly steps.
- Probed trust signals, region-specific needs, and expectations for AI.
Key Actions:
- Observed live discovery and file triage
- Compared keyword vs. AI-assisted flows
- Mapped customization patterns and blockers
Insights
1. Search & Discovery
- Users start with keywords (70–80% relevance). Filters are fallback, not first choice.
- SDRs often begin from product icons; AEs/SCs use product and industry terms.
- Frequent redownloading signals missing wayfinding and weak result ranking.
“I’ll try keywords first; if that fails, I narrow with filters.” — SC, AMS
2. Content Engagement
- Everyone customizes before sharing—decks are source material, not deliverables.
- Capability Map and Pricing & Packaging are the most trusted references.
- APAC participants cited U.S.-centric “fluff,” requiring regional tailoring.
“I would never use a standard deck without adjustments.” — AE, APAC
3. AI Integration (Aura)
- 50% faster search completion with trusted, SSC-sourced answers.
- Summaries and citations improved confidence on unfamiliar topics.
- Keeping AI inside SSC reduced tool-switching and context loss.
“This does what I’d reach after hours of research.” — SDR, EMEA
Impact
- Evidence package supported leadership momentum to license and fund Aura.
- Kickstarted roadmap work on AI search, regional templates, and predictive slide recommendations.
- Bridged ServiceNow/Seismic teams around shared success metrics and governance.
Stakeholder note:
Licensing Aura is a no-brainer. MyAssist only ingests a subset of SSC today.
Recommendations
- Enhance search intelligence: synonyms, industry taxonomy, version & customer-facing flags.
- Simplify customization: drag-and-drop slide assembly, region-specific/concise templates.
- Deeper AI: natural-language queries, predictive suggestions, long-doc summarization.
Reflection
This project showed how pairing qualitative nuance with measurable time savings converts skepticism into sponsorship. By keeping AI inside the trusted SSC perimeter and designing for real customization workflows, we shifted SSC from a repository to an assistant, and unlocked faster, more confident customer conversations.
Credits & Roles:
Research lead: study design, moderation, analysis, stakeholder facilitation, insight synthesis, executive storytelling.
Julie Elliott 