For insights and research teams
Waldo for insights and research teams: findings that survive the follow-up question
GWI panels and live conversation in one queryable layer, with permanent archives and a source link on everything.
The short answer
Insights teams use Waldo as a queryable research layer: GWI audience panels alongside live social conversation, clustered verbatims, and permanent archives of everything captured. Per call you choose raw source material or scored analysis, and every output links to its sources, so findings hold up when someone asks where a number came from.
Insights teams live under a specific kind of scrutiny: every finding meets a “where did that come from?” and the answer has to hold. The working reality is a stack of disconnected vendors, panel data in one contract, social data in another, an archive that quietly loses anything the platforms delete, and a request queue from every team in the company that wants just one quick read.
Waldo puts the inputs in one queryable layer: GWI audience panels alongside live conversation from Instagram, TikTok, Reddit, X, YouTube, Meta, and LinkedIn, plus ad libraries and landing page snapshots. Everything captured is stored permanently, and every output carries links to its sources. Per call, you choose the raw layer for your own analysis or the scored layer when the synthesis is the deliverable.
The plays
Panels and conversation in one query
Cross-read GWI panel structure against what the same audience says unprompted in live conversation. /audiences/{id}/conversations returns the verbatims; the panel data sits in the same layer, so triangulation is one workflow, not two vendors.
Verbatims at scale, already clustered
Instead of hand-coding a thousand posts, pull clustered verbatims on the question at hand, each one linked to the original post. Recode against the raw layer whenever the clustering choices need checking.
An archive that does not rot
Waldo stores everything captured permanently: text, images, video, and metrics, even if the original is deleted. Longitudinal reads stay possible because the underlying material is still there next year.
Self-serve for the rest of the org
Scoped keys and the MCP connector let brand and comms teams answer their own quick questions in chat, against the same layer, while research keeps the credit pool and the methodology in view.
Questions teams ask
What is the methodology behind the data?
Two kinds of source, kept distinct. Tracked entities are captured from the platforms and ad libraries on a 24-hour cycle; audience panel data comes through Waldo’s partnership with GWI. Every output links to its sources, so you can always inspect what a finding rests on.
Can we work from raw data rather than Waldo’s scores?
Yes, and it is a per-call choice, not an account tier. The raw layer returns posts, ads, page snapshots, and verbatims at roughly 1 credit per 20 results; the analysis layer returns scored synthesis at about 5 credits, so anything methodological can run on your own analysis of raw pulls.
How do we cite Waldo data in reports?
Every output links to its underlying sources, and captured material is stored permanently, so a citation still resolves after the original post is gone. Workspaces are isolated, Waldo is SOC 2 compliant, and customer data is never used for model training.
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