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Deep Research currently enabled for a subset of our partners. If you think your team could benefit from this feature, please reach out to us on Slack to connect.

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What is Deep Research?
Deep Research allows your team to uncover custom, AI-driven insights from your own data, allowing you to answer complex business questions with precision. Instead of spending hour sifting through reports, Deep Research provides intelligence for accounts and opportunities, so your team can focus on execution. Example insights you can target using Deep Research:

Pricing dynamics: “Was pricing considered a blocker?”

Competitive landscapes: “Which competitors were present in the deal?”

Persona Engagement: “At what stage did the IT persona get involved?” These insights provide the tools to move beyond surface-level reports to truly understand the “why” behind what moves deals forward.

Deep Research Queries Examples

Multi-thread velocity	For sales accepted deals, how many days does it take to multi-thread into 3 members of the buying group?
Reject reason identification	Reclassify rejected deals into new categories based on the context available in communication records.
Flagship event influence	Assess opportunities for inferred influence from a specific high-value event, even if poorly tracked.
Referral identification	For a given set of opportunities, identify if the prospect was referred by a 3rd party, and if so, identify the referrer and the time/place where the referral occurred.
Frequently asked questions	For a given set of opportunities, identify the questions that prospects ask during their evaluation. The questions can be aggregated to develop a public-facing FAQ.
Account dossier	Prepare a 1-page transition document for a given list of accounts to aid account executives that are taking ownership of the accounts. It should include current state, active prospects, prior challenges/blockers, and incumbent renewal dates.
Customer sentiment during a specific period	For a given set of opportunities, identify customer sentiment during a specific period — for example, the implementation phase.
Competitor identification	For a given set of opportunities, identify which competitors were considered and which competitors won the deal, if applicable.

Dataset List

The Deep Research Datasets or Dataset List page provides an overview of each dataset you have created.
Next to each dataset name, the type, status, entity type, number of records, and number of AI columns is displayed.
Use the search bar to query by dataset name.
Click to enter into any dataset.

Creating Datasets

Use the Create New Dataset button on the Deep Research Datasets page to generate a new blank dataset to submit for processing.

Once the new dataset is created created, you can:
- Filter by Opportunity or Account Name entity types.
- Use the Columns dropdown to select or deselect specific columns.
- Add and create AI Fields by selecting the New AI Field button and opening the modal.

Creating AI Fields

Field Name: Enter the field name or alias under which this field can be found.
Description (optional): Enter an optional description of the field’s purpose for your human team members.
AI Instructions: Enter the instructions for the agents. The best instructions will be detailed and straightforward.
Output Type: Select output type from a dropdown of Short Answer, Long Answer, Single-Select, and Multi-Select. For Single- and Multi-Select, an additional field will appear, prompting the input of selection options.

Report View

Each Report View displays a single dataset with each Opportunity or Account’s details, along with answers to the questions asked by your pre-specified AI Fields. In the example above, the AI Field used was “Compensation/Total Rewards First Engaged.”

AI Fields

The AI Fields page displays a list of all created AI Fields in your organization for you to easily access and edit your desired one.
Next to each Field Name, the Description (for human team members), Entity type (Account or Opportunity), Output type, and the number of active reports utilizing the field are displayed.