# See if Sandfox fits what you need

Sandfox creates adaptive discovery experiences that enable buyer-led exploration and connect… Ask what matters to you and judge the fit.

> Canonical: https://discover.sandfox.ai/sandfox

## Is this relevant to my situation?

Mid-market and enterprise organizations with complex buying processes and multi-stakeholder purchasing decisions. Sandfox states it is used by go-to-market teams implementing more adaptive, buyer-led discovery experiences to improve buyer engagement and pipeline development. The platform is commonly used as a discovery destination for inbound traffic and outbound campaigns, replacing static content and landing pages with adaptive experiences. It is applied primarily in early and mid-funnel contexts to support buyer exploration, improve qualification context, and help teams better understand which topics, use cases, and problems buyers respond to.

## Show me proof

Early design partners from across privacy, security, and developer tooling (referenced on the website homepage; no named companies documented)

## Different stakeholders

- Demand Generation / Growth Marketing
- Product Marketing
- Marketing Leadership
- Revenue Operations (RevOps)
- Sales

## How is this different from what we do now?

- Sandfox structures digital exploration around discovery rather than static content navigation.
- Sandfox is a learning system — responses adapt dynamically based on visitor context, exploration behavior, and questions asked, while the context built through each interaction continues to shape the discovery journey over time, not just the structured assets it started with.
- Adaptive responses are generated from a governed repository of structured assets describing the company and offering.
- Captures signals based on questions asked, topics explored, and discovery paths rather than simple page views or clicks.
- Combines adaptive discovery with administrative governance, asset management, and reporting capabilities.

## What are the limitations?

- Not a CMS or page builder — works alongside the existing site, not as a replacement
- Not a chatbot or AI agent — renders an adaptive full-page experience rather than a conversation thread
- Not a website personalization tool — generates and reshapes the full experience per buyer rather than swapping content blocks based on firmographic rules
- Not a digital sales room — operates upstream of the deal, not as a post-meeting deal workspace
- Not a replacement for human sales conversations — designed to make those conversations better, not replace them
- Not an interactive demo tool — does not capture or render product UI tours, though it can embed demo tools
- Not a third-party intent data provider — signal is first-party and session-level, not assembled from firmographics or off-site behavior
- Not a content management or sales enablement suite — structures existing content into buyer context assets but does not replace a content repository

## Likely objections

- Uses a structured asset repository to define the company, offering, and customer context that powers adaptive discovery experiences.
- Generates adaptive discovery responses in real time using AI grounded in these structured knowledge assets, adapting to visitor role, company context, and engagement behavior.
- Provides an administrative layer for governance, reporting, and controls so teams can manage discovery experiences and understand buyer engagement signals.
- Structured knowledge assets are derived from existing website and marketing content using AI-assisted processes, and can be reviewed, edited, and extended via API or MCP to power other GTM tools and workflows.
- Discovery Maps organize how topics can be explored, providing structure for buyer navigation while still allowing open-ended questions.
- Engagement signals — based on questions asked, topics explored, and exploration paths — are captured at the interaction level and can be routed into existing CRM, marketing automation, and analytics systems.

## How does this actually work?

- An AI agent that reads the customer's existing website, content, and data and compiles it into structured Buyer Context Assets — the content layer that powers every discovery session. The wizard synthesizes offering information, messaging, personas, industry segments, use cases, buyer contexts, and messaging overlays into a reusable, structured library.
- A managed repository of all generated and refined buyer context assets. Customers generate, refine, and publish the context that powers Sandfox responses from this surface. Teams manage context assets and discovery maps, deploy experiences across channels, and read engagement signals by account and session.
- The buyer-facing layer. When a buyer arrives from any channel (website, paid, outbound, follow-up), Sandfox interprets their context and renders a full adaptive page — not a chat thread, not a static landing page — that reshapes as the buyer explores. Each buyer builds their own Discovery Graph (their unique path through the Discovery Map the customer's team defines). The experience adapts in real time to the buyer's role, company, history, and areas of interest.
- Every session is captured as structured buyer signal across four types: Buyer signal (what the buyer is trying to solve, questions asked, differentiators that move them, readiness), Account signal (which accounts are evaluating, who in the buying committee is participating), Experience signal (which entry points and paths drive progression, CTA performance, drop-off points), and Market signal (which messaging and content resonates, which personas engage most, content gaps). The Discovery Graph captures how decisions actually get made and accumulates into a living understanding of how buyers evaluate.
- The operator-facing control surface. Described as 'one admin surface' from which customers manage context assets, configure discovery maps, deploy experiences across channels, and read engagement signals by account and session. Dashboard metrics include: links minted, visitors, engagement rate, topic views per visitor, account match rate, sessions over time, top topics explored, top personas identified, top industry segments, and questions with no supporting asset.
- Buyer Context Assets are published as an MCP (Model Context Protocol), making the structured context a portable layer any agent in the customer's stack can use. Any AI agent in the customer's stack can draw from the same context layer that Sandfox compiles.

## How does this compare?

Sandfox transforms static digital experiences into adaptive, buyer-led discovery — turning buyer exploration into qualified pipeline and meaningful engagement signals for go-to-market teams.

## Executive materials

- Buyers find relevance on their own terms without a premature sales conversation
- Buyers complete evaluations on the vendor's own content rather than third-party AI summaries
- Buying committees can each explore independently with signal captured per participant
- More website-sourced pipeline from existing traffic
- Higher visitor-to-lead conversion by guiding buyers through evaluation
- Higher landing page conversion from paid campaigns
- Lower cost per qualified opportunity and better campaign ROI
- Better marketing efficiency measured as pipeline per advertising dollar

## What could go wrong?

- Requires structured knowledge assets (Structured Asset Repository and Discovery Map) to be configured before adaptive discovery experiences can be deployed.
- Discovery experiences are primarily text-based and designed for exploration and understanding, not visual product demonstrations or UI walkthroughs.
- Initial setup involves deriving structured assets from existing content and configuring Discovery Maps.
- Requires structured knowledge assets to generate adaptive discovery responses; initial setup involves deriving structured assets from existing content and configuring Discovery Maps.
- Discovery experiences are primarily text-based and designed for exploration and understanding — not visual product demonstrations or UI walkthroughs.
- Does not replace ad platforms, CRM, or marketing automation platforms; operates alongside existing GTM systems.
- Requires structured knowledge assets (Structured Asset Repository and Discovery Map) to be configured before adaptive experiences can be deployed.
- Per-account or per-recipient link generation adds operational complexity; implementation effort is rated Medium for ABM email account experiences and Low for LinkedIn, gifting, and paid-ad deployments.

## Evaluation framework

- Buyers enter sales conversations with clearer understanding of the offering, reducing time spent on basic explanation.
- Website traffic results in deeper engagement prior to sales interaction, measurable through exploration depth and progression signals.
- Improvement in MQL-to-SQL conversion as better-qualified, better-informed buyers reach sales.
- Fewer wasted SDR cycles from outreach to buyers with no substantive engagement history.
- Cost per qualified opportunity improves without a proportional increase in spend.
- Campaign-sourced leads reach Sales with more consistent quality and context about what buyers explored.
- Higher-quality MQLs from paid spend and lower customer acquisition cost, as stated by Sandfox.
- Cleaner attribution per touch across paid channels.