Internal sales enablement platform

Project detail

• Symptoms: Reps spent time searching across sources, relied heavily on individual expertise, and needed a more dependable way to get current guidance during live conversations.
• Drivers: Information lived across email threads, docs, and ad hoc files, creating an opportunity for clearer ownership and governance.
• Constraints: Diverse usage patterns, constant content change, and a need for fast adoption with minimal training.
• Result: Faster cycles, more consistent messaging, and lower internal support demand.

Knowledge lived across scattered sources

Critical product and sales knowledge was scattered across inboxes, slide decks, chat threads, and personal documents. A shared source was needed to make guidance easier to find, trust, and maintain. Experienced reps developed effective shortcuts over time, and the opportunity was to make that expertise easier to share. Newer team members often learned through shadowing or by asking SMEs, so a shared system could make strong guidance available to more people.

As the organization grew, the lack of a reliable source of truth made messaging harder to maintain and scale.

Designing reference tools for live conversations

The opportunity was to make static reference content useful during live conversations. Reps needed to pivot quickly based on questions, objections, and use cases, while the existing tools relied on linear navigation and broad searches. In the moment, memory or improvisation was often faster.

The opportunity was to make guidance fast enough to use during a live conversation, so reps could rely on shared content instead of personal notes or memory.

The product had to follow the conversation

At first glance, this looked like a content organization issue. Discovery showed the bigger opportunity was how knowledge was used. Sales conversations were dynamic, situational, and nonlinear, so guidance had to adapt continuously based on client context and the direction of the discussion.

The opportunity was to design around how sales teams actually reasoned through a conversation and bring the right information into that workflow.

What the solution had to reconcile

A viable approach needed to balance:

The challenge was to make tacit expertise explicit while still feeling natural to use. That reframed the effort from documentation cleanup to system design.

• Structured guidance that still felt natural in conversation
• Consistency with room for rep judgment
• Fast access to accurate information during live work
• Shared ownership so expertise could scale across the team

Grounding the challenge in real sales and customer work

Discovery focused on how sales teams learned, retained, and reused knowledge, and how customers experienced that information in live conversations. The existing approach relied heavily on individual expertise, documents, and long email threads that took time to search and keep current.

As the organization grew, a shared source of truth became increasingly important for keeping guidance current and consistent across teams.

Research approach

Discovery combined multiple inputs so patterns were confirmed across sources and grounded in repeated evidence. I partnered with a specialized research firm to conduct moderated customer interviews while remaining hands-on in planning, live sessions, and synthesis. In parallel, I led large-scale surveys across 300+ responses to understand demographics, motivations, and behavioral differences across small business owners and more entrepreneurial operators.

Interviews started broad to surface themes, then narrowed into deeper sessions with selected participants and internal SMEs to validate assumptions and separate edge cases from core needs. Personas were derived from customer research and extensive sales team input, then reviewed with sales to ensure they reflected real objections, decision dynamics, and conversation flow.

Different buyer mindsets in the same sales funnel

One key insight was the behavioral difference between compliance-oriented small business owners and more entrepreneurial operators, even at similar company sizes.

The two groups responded better to different levels of detail, reassurance, and speed. I mapped the key behavioral dimensions across both archetypes so guidance could adapt by audience while keeping the core message consistent.

• SBOs prioritized certainty, documentation, and validation before moving forward.
• Entrepreneurs optimized for speed, upside, and strategic advantage, often tolerating more ambiguity.

Turning sales knowledge into structure

Sales teams held deep experience-based knowledge about objections, explanations, and successful framing, but much of it lived in conversations, personal notes, and memory.

I synthesized interview data, call insights, FAQs, and survey findings into structured themes that reflected how reps reasoned through complex deals.

Synthesis focused on:

Personas and themes were validated with sales and used as working tools that directly informed content structure, language, and prioritization.

• Common objections and how they evolved during conversations
• Language patterns that built trust versus increased friction
• Where reps improvised when guidance was hard to find or keep current
• Information customers repeatedly asked for and wanted easier access to

From insight to direction

Discovery showed that the real opportunity was structure, context, and confidence. The information existed; the next step was making it easier to find, maintain, and apply in real conversations.

Any solution would need to:

These insights directly shaped how the system was framed, organized, and designed in later phases.

• Make expert knowledge easy to access and reuse without oversimplifying it
• Support different customer mindsets without forcing reps to improvise
• Keep relevant context visible during live conversations
• Evolve as products, policies, and messaging changed

From individual know-how to a shared system

• Goal: Make sales knowledge fast to find, easy to trust, and simple to maintain.
• Inputs: Product knowledge, messaging, assets, and enablement updates.
• Core interactions: Search, browse by use case or audience, save, and share.
• Governance: Ownership, review cadence, versioning, and visibility rules.
• Outcome: Faster preparation and more consistent conversations across the sales organization.

Strategic goals

The strategy centered on four goals:

• Create a single source of truth Information needed to be authoritative, current, and consistent across sales workflows and customer touchpoints.
• Meet users where decisions were made Knowledge had to fit existing sales and operational workflows and stay easy to reach during live work.
• Scale access to expertise across a growing sales team The system needed to help average performers operate more like top performers while accelerating onboarding for new hires.
• Support both internal and external use cases Internal teams needed nuance and guidance. External audiences needed clarity, confidence, and trust.

Guardrails that shaped the solution

The strategy was shaped by a few core guardrails:

This led to a clear direction: build a knowledge system that turned sales expertise into explicit, reusable guidance integrated into how the organization already worked.

• Fast access during live conversations so reps could stay in the flow of the discussion
• Trustworthy information reps could use confidently with customers
• Clear ownership and governance so content stayed current
• One flexible system that could support different customer types and situations

A conversational path to the same knowledge

Once the knowledge model was in place, we could give reps another way into it. If they already knew the question, they could ask it conversationally and get to an answer faster during live work.

Early tests highlighted an important limitation of the technology at the time: hallucination. When context was incomplete, the model could produce a confident answer that sounded plausible. Our team had already researched, written, and structured much of the ERC guidance, so we grounded the AI in that vetted content and gave it a much tighter body of knowledge to work from.

That gave reps two useful ways into the same knowledge: browse when they needed context, or ask when they already knew the question.

Designed around live customer conversations

The experience was organized around how sales and support teams think, speak, and respond in live customer conversations.

The system surfaced clear guidance at the moment of need, helping teams respond with more confidence and consistency while keeping the underlying ERC detail available when they needed it.

Customer archetypes as the primary entry point

The experience was anchored around nine customer archetypes reflecting common mindsets in ERC conversations.

Each archetype captured:

This let teams quickly recognize who they were talking to and tailor their response from the guidance in front of them.

Impact: Faster onboarding, better continuity during live calls, and more consistent messaging across the organization.

• What customers typically said
• What they were worried about
• What information moved them forward

Conversations as reusable interaction models

Common customer discussions were treated as repeatable conversation patterns that teams could reuse across calls, coaching, and follow-up.

Each conversation included:

This made proven guidance easier to share while preserving human judgment in delivery.

• Common objections or questions
• Emotional context
• Clear guidance on how to respond
• Links to related conversations and supporting content

Progressive disclosure for speed and depth

The experience supported different levels of urgency and expertise through progressive detail:

The same structure worked for live calls, follow-up, and internal prep.

• High-level overviews for quick orientation
• Conversation-level guidance for live calls
• Deeper detail when credibility, compliance, or edge cases mattered

Browse or ask, depending on the moment

The structured experience let reps browse by customer, conversation, topic, FAQ, or tool. The AI path was useful when they already had a specific question and wanted a faster route to an answer.

Both used the same source material, so the answer a rep got matched the guidance they could browse.

Designed for governance and growth

Beyond the interface, the system was designed to support:

The structure could grow while keeping guidance clear, trustworthy, and maintainable.

• Clear navigation across Customers, Conversations, Topics, FAQs, and Tools
• Content governance and updates
• Analytics, feedback loops, and AI-assisted retrieval grounded in governed source content

Mobile support for live conversations

Mobile views of the delivered Knowledge Center, showing how customer archetypes and conversation guidance carried into smaller-screen use during live sales work.

Project detail

The work combined research, design, product leadership, and delivery, turning scattered knowledge across emails and static documents into a shipped system used by the sales organization.

I led delivery end to end, assembling a cross-functional team, aligning priorities, creating the phased rollout plan, and coordinating execution with engineering while keeping sales and operations involved throughout.

Delivery was structured as milestones so usable value could ship early while the system scaled in parallel. Early phases focused on the Contentful CMS, information model, and first internal release. Later phases expanded content types, refined interaction patterns, and introduced integration and automation opportunities.

This phased approach let the team ship usable value early, keep scope manageable, and improve the platform while active sales work continued.

Validation through real-world scenarios

Validation focused on realism: could the system support live conversations under time pressure?

We ran working sessions with sales, account representatives, and internal SMEs to test whether the structure reduced ambiguity, supported scenario-based navigation, and enabled confident responses from shared guidance. Feedback led to refinements in labeling, structure, and retrieval patterns while confirming that the core interaction model matched how teams actually sold.

Internal validation and readiness

Concepts and flows were reviewed iteratively with sales leadership, operations partners, and engineering stakeholders to ensure the system was viable within organizational and technical constraints.

Reviews focused on:

Validation confirmed that the information model matched how sales teams reasoned about objections, questions, and trust-building moments. Refinements were made to labeling and hierarchy, but the underlying system design remained intact.

• Accuracy and consistency of guidance across customer scenarios
• Clarity of content ownership and update workflows
• Feasibility of maintaining content while keeping expertise easy to access
• Alignment with CMS capabilities and engineering milestones

Testing AI answers against real ERC questions

Trust was the central validation question for the AI experience: would a rep use the answer during a live customer conversation?

Grounding the model in vetted ERC content gave it a reliable body of knowledge to work from. Because the same team maintained that content for the Knowledge Center, improving the source material improved the AI answers too.

Customer & business impact

• Improved sales efficiency by reducing time spent searching for materials, answers, and approvals
• Increased confidence in live conversations through clearer, more current, and more trusted content
• Reduced cognitive load for new and tenured reps by organizing tools, content, and workflows around real sales tasks

Platform & organizational impact

• Created a single source of truth across sales, marketing, product, and leadership, reducing duplication and conflicting guidance
• Enabled faster updates to messaging, assets, and enablement materials without disrupting sales workflows
• Information architecture that could grow with the platform in products, regions, and sales motions without increasing complexity

What I took from the work

Internal platforms create value when they fit the work people are already doing.

The work left me with four things an enablement system has to get right:

Leading this effort meant aligning stakeholders with different priorities and giving the team a shared direction for clearer decisions and faster execution.

The result was an internal product that supported revenue outcomes by helping people do their jobs with less friction and more confidence.

• Design around how teams actually work in real sales situations
• Balance flexibility with governance so information stays useful as it grows
• Make accuracy, recency, and ownership visible so teams know what they can rely on
• Give AI a reliable, well-maintained body of knowledge to work from