> ## Documentation Index
> Fetch the complete documentation index at: https://clearskies.cc/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Objection Trends

> The objections and buying criteria coming up across your calls, as a recurring report. What your market is pushing back on, before it shows up in your win rate.

Every rep hears objections and handles them alone. Enablement finds out at the next QBR, or when a win rate drops and somebody goes looking. The information already exists in your call recordings; nobody reads two hundred calls to find the pattern. Objection trends reads them: what buyers are pushing back on, which criteria they keep raising, what is new this month, and how the objections differ between the deals you win and the ones you lose.

## Data Sources

| Category         | Required | Recommended |
| :--------------- | :------- | :---------- |
| Calls            | ✓        |             |
| CRM              | ✓        |             |
| Email + Calendar |          | ✓           |
| Messaging        |          | ✓           |

**Starter** (required only): objections and buying criteria across your calls, grouped and counted, tied to the deals they came from and their outcomes.

**Full** (required + recommended): the same, plus what came up over email. Pricing pushback and procurement requirements often arrive in writing rather than on a call, and those are the objections that decide deals.

CRM is required rather than recommended here, because an objection count without outcomes attached is trivia. The useful version is which objections appear in deals you lose.

See the [Context Graph](/docs/unifying-gtm-data/customer-context-graph) for how each source feeds the report.

### Choose your path

| Path                       | Best for                                                           | Output is delivered                   |
| :------------------------- | :----------------------------------------------------------------- | :------------------------------------ |
| Build in Clearskies        | Teams who want a standing monthly or weekly read                   | To Slack DMs or channels              |
| Build in Claude or ChatGPT | Enablement and leaders digging into a specific objection or window | In the Claude or ChatGPT conversation |

## Build in Clearskies

Build the workflow once and the read arrives on a cadence, so the pattern is visible while it is still early.

### The Workflow

In the Clearskies app, open the workflow builder and describe what you want in plain language:

```text theme={null}
On the 1st of each month, review the customer calls from the last
30 days. Identify the objections and buying criteria that came up, group
them, and count how often each appeared. For each one, note which deals it
appeared in and how those deals are trending. Call out anything that is
new versus the previous month. Post the report to the #enablement channel.
```

The app configures the schedule, the calls in scope, and the destination.

Scheduled workflows have no meeting context, so the calls come from a record lookup over a date range rather than from a single meeting. Record lookups cap at 100 records per step, so a high-volume team should scope by segment or by a shorter window rather than trying to sweep everything at once.

Start with a month. A week is not enough conversation to see a trend and a quarter is late.

### Deploy to Slack

Once published, the channel gets the read:

```text theme={null}
Objection Trends — July
62 customer calls reviewed · 34 deals

Most frequent
1. Onboarding capacity, 19 calls (up from 11 in June)
   Buyers are not objecting to the product, they are objecting to their own
   ability to absorb it this quarter. Appeared in 4 of the 5 deals that
   slipped a close date in July.
2. Data residency and retention, 14 calls (up from 6)
   Almost always raised by legal or security, not by the champion, and
   usually after the champion is already sold. Two deals stalled at this
   step for over three weeks.
3. Price versus the incumbent, 12 calls (flat)
   Consistent, and not correlated with losses. Deals where this came up
   closed at roughly the same rate as deals where it did not.

New this month
"Can we run this without giving it access to email" appeared on 5 calls,
zero in June. All 5 were in regulated industries.

Objections that appear in losses but not wins
• "We need to see this working with our own data first" — appeared in 6 of
  8 lost deals, 1 of 11 won deals.
• "Let's revisit next quarter" — 5 losses, 0 wins. Worth treating as a
  no-decision signal rather than an objection.

Buying criteria being raised
Single weekly report a VP can read without an analyst (9 calls). SSO and
provisioning (7). Existing workflow tooling compatibility (6).

Worth acting on
Onboarding capacity nearly doubled month over month and shows up in most
of the slips. That is a proof-and-onboarding problem, not a pricing one.
```

### Customize the rollout

* Set the cadence: monthly reads the trend, weekly catches a new objection early
* Scope by segment, region, product line, or team, since objections differ across them
* Group objections against your own categories rather than letting them be grouped from scratch each run
* Compare against the previous period, or against the same period last year
* Route it to enablement, product marketing, or a leadership channel
* Chain it with [competitive intel](/docs/use-cases/competitive-intelligence-from-your-own-data) so objections and competitor mentions read together

## Build in Claude or ChatGPT

The better path when you have a specific question. Enablement rewriting a piece of collateral wants one objection in depth, not the whole report.

### The Prompt

Open Claude or ChatGPT with the Clearskies MCP connected and paste this (or modify to your needs).

```text theme={null}
Using the Clearskies Context Graph, analyze the objections in our customer
calls over the last 90 days.

Give me:
- The objections that came up most, with counts
- For each one, who raises it: the champion, or someone brought in later
- Which objections appear in deals we lost but not in deals we won
- The buying criteria buyers keep naming
- Anything that is new in the last 30 days versus the 60 before it

Quote the actual language buyers use. Do not paraphrase an objection into
our own vocabulary.
```

That last instruction is the one that makes this useful. An objection restated in your positioning language stops being evidence about the market.

### Make it yours

* Add `Show me every quote where a buyer raised onboarding capacity` to go from the pattern to the raw material.
* Add `How did each rep respond when this came up, and which response preceded a won deal` to turn the analysis into coaching.
* Add `Draft the objection-handling guidance for the top three` when the output is going into enablement collateral.
* Add `Only deals in [segment]` when you suspect the pattern differs by market.

<Tip>
  Want this packaged for your team? [**Reach out**](mailto:support@clearskies.cc) and we'll help you customize this into a skill for your workflow.
</Tip>

## The Plugin

**Ready to make this part of your team's workflow?** We'll set up the Clearskies plugin with you. Clearskies workflows, Claude skills, all tailored to how your team works.

[**Book 15 minutes →**](https://calendly.com/pouyan/new-meeting)

## Next steps

1. [Sign in to Clearskies](https://app.clearskies.cc/)
2. Connect your data sources
3. Get your [Clearskies MCP server](/docs/building-with-clearskies/mcp-server) and try with [Claude](/docs/building-with-clearskies/mcp-clients/claude) or [ChatGPT](/docs/building-with-clearskies/mcp-clients/chatgpt)