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Customer Intelligence

Customer Sentiment Analysis Reports

What buyers say about you and your competitors in reviews, forums and social posts, and what they wish someone sold them.

Get a Fixed Quote What a Report Includes

What you get

  • Multi-Platform Sentiment Tracking

    Unified sentiment analysis across Google Reviews, Yelp, Twitter/X, Facebook, community forums, G2, Trustpilot, BBB, and major social platforms.

  • Unmet Needs Identification

    What do customers wish you offered? We find the feature requests, complaints, and workarounds buried in public conversations.

  • Brand Perception vs. Competitors

    Side-by-side comparison of how customers perceive you versus each competitor. Where you win. Where you lose. Why.

  • Churn Risk Signals

    Spot warning signs of customer loss: rising complaints, more mentions of competitors, falling sentiment.

  • Segment-Level Analysis

    Break down sentiment by product line, use case, geography or customer segment, where the source material supports the split. Inferred groups are labeled as estimates.

  • Trend Trajectories

    Is satisfaction improving or declining? We show the trajectory over 1, 3, and 5 years with leading indicators.

How it works

  1. Step 1
    Brand Mapping

    We identify the platforms where your customers talk (reviews, forums, social, communities) and confirm what can be collected.

  2. Step 2
    Complete Mining

    AI agents analyze the available mentions, categorize sentiment, extract themes, score urgency and flag items for review.

  3. Step 3
    Pattern Analysis

    Cross-reference findings to identify systemic issues vs. outliers. Map sentiment trajectories over time.

  4. Step 4
    Action Plan

    Prioritized list of customer issues, unmet needs, and competitive gaps, with specific recommendations.

Scope, methods and delivery

The problem we address

Surveys answer the questions you think to ask, and response rates are often low. Public discussions can surface concerns you never asked about: what customers say to each other on forums, review sites and social media. The people who post are a self-selected group too, so we treat what they say as evidence to weigh, not a census.

Our approach

We analyze the public conversations about your brand across an agreed set of review sites, forums, social media, support communities and comparison sites. We find the recurring concerns, check them against other evidence, and state the coverage and sample limits in the report.

What customers actually say vs. what surveys tell you

Survey data has a structural problem: people answer the questions they were asked, in the way they think they should answer them, in the moment they were prompted.

The unprompted, candid version of the same opinion lives elsewhere — in the review someone posted at midnight, in the forum thread where they vented about a competitor, in the Reddit comment where they explained why they cancelled. That's the data we work from.

Where we pull the signal from

Customer intelligence draws from multiple unprompted-discussion surfaces:

  • Long-running archive of consumer discussions across forum and social platforms
  • Review platforms: G2, Trustpilot, Capterra, Google reviews, App Store, Play Store, Amazon
  • CFPB consumer-complaint records
  • FDA MAUDE medical-device adverse-event reports, including consumer-use devices, interpreted alongside the FDA's data limitations
  • NHTSA complaint data for automotive
  • Category-specific support communities

The cross-source approach surfaces patterns single-platform analysis misses. When complaints rise in forum discussions before the same issue reaches review sites, that early signal is lost if you only watch the review sites.

What the report contains

A standard customer intelligence report covers your brand and 3-5 named competitors across the same dimensions:

  • Top loyalty drivers — what your best customers actually praise, in their words
  • Top friction patterns — the recurring complaints that drive churn
  • Segmentation — demographic and use-case clusters derived from language patterns, not self-reported demographics
  • Sentiment trend analysis over rolling 12-24 month windows
  • Comparative head-to-head against competitors on each dimension

The deliverable closes with a prioritized list of operational changes, each tied to specific customer evidence.

When this fits

Customer intelligence fits companies entering a new market, repositioning a product, evaluating a category they suspect is misunderstood, or recovering from a sentiment hit. It also fits acquirers who need an honest read on the acquired company's customer base before integration.

It does not fit pure B2B niches with fewer than 50 customers — the signal-to-noise ratio is too thin for unprompted-discussion analysis to work.

Customer Intelligence questions

What is customer sentiment analysis?
Customer sentiment analysis measures how people feel about your brand, products, and services by analyzing reviews, forum discussions, social media posts, and support interactions. We go beyond star ratings. Our analysis covers archived consumer discussions across social platforms, CFPB consumer complaints, and review data across major platforms to show what customers think and how that perception has changed over time.
How is this different from social listening tools?
Social listening tools like Brandwatch or Sprout Social are software your team runs; both track social platforms, and both cover forums and other web sources too. We do the analysis for you: we combine those conversations with review platforms, consumer complaint databases and public records, and hand you findings and recommendations rather than a dashboard to work through.
How far back can you analyze sentiment?
Our consumer discussion analysis covers multi-year archives. How far back review platforms go depends on the source. This historical depth shows you the trajectory, not a snapshot. You can see exactly when customer perception shifted and correlate it with product changes, PR events, or competitor intelligence.
Can you track sentiment for specific products or features?
Yes, where the source material supports it. We can compare sentiment by product line, feature, price tier, geography or customer segment. Most posters don't say who they work for, so groups such as enterprise versus small-business customers are inferred from what they write and labeled as estimates; groups too sparse to tell apart aren't reported as established cohorts.
What are the 4 C's of customer intelligence?
There's no single standard list; the 4 C's are how we describe our own process: Collection (gathering customer data from the touchpoints in scope), Consolidation (merging data across sources into a single view), Contextualization (adding market and competitor context), and Communication (delivering findings as recommendations, not raw data). We handle all four.
How do you handle fake reviews?
Our multi-agent verification flags suspicious patterns: sudden review spikes, duplicate language across accounts, and unusual reviewer profiles. We weight verified purchaser reviews higher and note when fake review campaigns are detected. If a competitor is running fake reviews, we flag that too. See our competitor customer capture service for turning that into leads.

Related

Services

Guides

Public sources we use: CFPB Complaint Database, FTC Consumer Protection, Stanford NLP Group.

Hear what your customers won't tell you directly

We analyze the available discussions about your brand across agreed review, forum and social sources and turn the recurring themes into findings and recommendations.

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