"What are the most common reasons customers lost business this season?" "Analyze last month's call recordings and tell me the most common concerns customers raised." "What are the common patterns among customers who have churned in the past year?" These are tasks that data analysts typically spend hours writing and analyzing with SQL queries.Breeze Data Agent can help AI analysts do this in minutes with just one natural language question.is. We investigate across CRM, call recordings, emails, documents, and the web, and return answers with evidence.
Data Agent is an "AI analyst" that simultaneously examines multiple data sources within HubSpot and provides answers in natural language. Analysis that previously required multiple steps to create a CRM report → check call recordings → search email body → manually integrate can be performed with a single prompt.
The most effective way to use the Data Agent is to"Create this week's regular sales agenda based on last week's transaction status" → CRM data is automatically reflectedThat's true. It is particularly effective in answering hypothesis-testing questions such as, "I think the price was the cause of last month's lost orders, but what would happen if we analyzed the actual call recordings?" A data analyst simply tells them in natural language what they want to confirm, and an answer is returned with evidence. Since the consumption amount is small at 10 credits/prompt, it is recommended to use it actively.
⏱ 50% reduction in meeting preparation time. Enables discussions based on dataQuestions that lead directly to business decisionsMaximize value by doing so. Typical utilization patterns by department are shown below.
| Department | Example question | Insights you get |
|---|---|---|
| Sales | Analyze the differences in calls made by salespeople with high closing rates and those with low closing rates. Please tell me the difference between talk and question patterns. | Extracting success patterns of top performers and utilizing them in team training |
| Sales | List the deals that have stopped trading in this quarter, and whose last activity has been more than 30 days. Please also tell me the final communication for each project. | Early detection of neglected cases and setting of follow-up priorities |
| marketing | Among the 10 email campaigns sent last month, we analyzed the subject line patterns that had high open rates and CTR. | Extract common elements of effective subject lines and apply them to your next campaign |
| marketing | What is the average time from downloading content to turning into a business negotiation? Analyze whether there are differences by industry | Content → Optimize nurturing design by understanding the conversion time of business negotiations by industry |
| customer support | Which ticket from last month "took more than 3 days to resolve"? Analyze common causes of delays | Identify categories with long resolution times to improve processes and strengthen KB |
| RevOps | MQL conversion rate 30% = 30 MQL increase | Identify early warning indicators of churn risk to set customer success intervention criteria |
| executives | Are there enough deals with a current probability of 70% or higher in this period's pipeline to meet the number of deals needed to achieve the budget? | Instantly understand pipeline coverage and determine the need for additional measures |
Number of monitored companies x 10 credits. First, filter ICP-compliant companies from CRM and check the number.Automatically write to custom properties in CRMThis is the collaboration with Smart Properties. By automatically populating the ``What competitive tools does this company use'' field into the ``Competitive tools used'' field, all sales reps can reference that information before making a deal.
Smart Properties10 credits/caseHowever, if the number of target records is large, credits will be consumed rapidly. Setting up 4 Smart Properties for 1,000 contacts costs 40,000 credits.Target only new contacts / Apply only to records with high ICP scoresThis design controls consumption. First, test on 50 items to confirm accuracy before rolling out the entire system.
Data Agent answer quality isMuch depends on the "quality of the question". Ambiguous questions will only give vague answers. Adhering to the following principles will greatly improve accuracy.
| principle | Bad question (low precision) | Good question (high precision) |
|---|---|---|
| Specify the period | "Analyze recent order losses" | "Analyzing lost orders from October to December 2025" |
| Narrow down your focus | “Tell me about customer trends” | “Please tell me the churn rate and common patterns for manufacturing companies, 100-500 employees, and customers in Japan.” |
| Specify output format | “Tell me the status of the pipeline.” | "Summary the pipeline status in table format with the probability of closing by phase and person in charge" |
| Set the comparison axis | "Analyze the effectiveness of emails" | "Compare this month's and last month's email open rates by industry, and tell me which segments are improving and which segments are deteriorating." |
| ask for evidence | “Tell me the reason for the loss.” | "Tell me the reasons for the loss. Include quotes from the call recordings that support each reason." |
Teams that manually perform the same analysis during weekly sales and CS reviews can reduce preparation time by 90% by creating canned question sets in Data Agent.Set a routine to "send the following 5 questions to the Data Agent every Monday at 9 o'clock"All you need to do is automatically gather the insights you need for your weekly review. Five points function as a weekly standard set: pipeline coverage, last week's deal conversion rate, ticket resolution time, top 5 companies with churn risk, and content → deal conversion rate.
Managers who cannot write SQL will be able to ``verify hypotheses using natural language.'' Data analysts are freed from routine tasks and can focus on more advanced analysis. Speed and democratization of analysis will be realized at the same time.
CRM numbers alone can only tell you what is happening. When combined with the text of the call recording, it becomes clear why this is happening. He is especially effective at analyzing lost orders and churn factors.
Start researching contacts. Start monitoring buyer signals and automatically reach out when signals are detected
Compared to Customer Agent (100cr/conversation) and Prospecting Agent (100cr/contact/month), Data Agent has an exceptional cost performance of 10cr/prompt. If you ask 100 questions a month, you'll get 1,000 credits. Proactive use will improve the quality and speed of decision-making.