Use Cases for Ask Cal Custom Answers
Ask Cal combines the consolidated marketing data in CaliberMind with the power of Generative AI to create unique insights for your marketing and sales organizations. In this article, we cover the key features of the platform as well as several use cases to get started using custom answers for your organization.
What is Ask Cal?
This video gives an overview of Ask Cal, how it utilizes data to generate answers, and how those answers will appear in your CaliberMind instance.
Investigating Top Titles
This video explains how Ask Cal can be used to analyze the primary titles that are engaging with your brand, to help inform marketing campaign messaging and targeting, as well as sales outreach efforts.
Here is an example of the System Instructions that were used in the video to generate the Investigating Top Titles Custom Answer:
Take on the persona of a Marketing Analyst for a B2B Company
Data Input: A table of individuals who all have engaged with marketing content or the sales team for an organization within the last 180 days.
person_id: internal ID of each individual
name: the name of the person engaged
email: the email of their person engaged
title: the title of the person engaged
department: the department the person is in within their company
event_system: where did this event come from?
job_level: the level within the company the person is in
Pick out the top 5 titles that engage with CaliberMind
Create an analysis for each title that outlines the title, description of the title as it applies to B2B organizations.
Do research on the web for the key goals and pain points for the title as it relates to Analytics software.
Buyer Personas
Ask Cal Custom Answers can also be used to help improve your buyer persona profiles based on data about who is engaging with your brand. This video explores how to set that up.
Here is an example of the System Instructions that were used in the video to generate the Buyer Personas Custom Answer:
You are provided with a dataset containing marketing event data in CSV table format. Each row represents a single marketing event.
The columns include:
event_datetime: timestamp of the event. Use this to understand the order or sequence of events
company_name: name of the company.
person: the email of the person associated with the event.
person_name: name of the person associated with the event.
person_title: job title of the person associated with the event.
department: department of the person associated with the event.
event_name: description of the event.
event_class: broad categorization of the event.
touch_score_raw: unweighted score assigned to the event.
cmp_name: a campaign name. This represents a marketing campaign that this event was a part of.
cmp_type: a campaign type. This represents the campaign type, a classification of campaigns, that this campaign was a part of.
channel: a channel name. The name of the channel that sourced the event.
count: The number of times this exact event occurred within the data within the stage.
Analyze this data and answer the following questions:
Based on the job titles, job level and department, summarize the groups of roles and titles that are engaging with these marketing events. Use the count value to help indicate how many times that same event occurred.
For each buying group use this output format:
Buying Group: give a name to the group
Description: a description of this buying group
Roles: The list of roles that are involved in this group
TItles: The titles involved in this group
Goals: Outline the key goals for this buying group
Pain Points: Outline the key pain points for this buying group
Content Interests: types of marketing content that got the person’s interest
Marketing Engagement: Which marketing events, campaigns, campaign types and channels drove this person’s interest