Know how your customers feel in real time

Track sentiment trends across reviews, calls and social feeds with Avahi’s AWS-powered analytics that turn noisy data into precise, actionable insight.

Why you’ll love Avahi sentiment analysis and social listening

Detect emotion, key themes and intent in more than one hundred languages with Amazon Comprehend and Bedrock models.
Combine social, support and survey data to reveal a single, accurate customer pulse.
Real-time alerts surface emerging issues before they escalate, improving CSAT and brand health.
Dashboards in QuickSight link sentiment scores to revenue, churn and campaign metrics.
All data stays inside your AWS account, encrypted at rest and in transit to meet privacy and compliance needs.
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How it works

01

Discovery workshop

Define data sources, KPIs and alert thresholds in a one-hour session.

02

Pilot pipeline

Ingest a sample feed, configure custom entities and validate sentiment accuracy against known cases.

03

Production rollout

Orchestrate streaming ingestion with Kinesis and Lambda, push insights to QuickSight and alert channels.

04

Optimise and expand

Add new platforms, refine models and surface predictive churn or purchase propensity scores.

Industry use cases

Industry
Example use case
Retail and e-commerce
Monitor product reviews and social buzz to optimise launches and reduce returns.
Finance
Detect early warning signs of customer frustration in support calls to lower complaint rates.
Hospitality
Analyse guest feedback across booking sites to prioritise service improvements.
SaaS and B2B
Gauge sentiment in tickets and community forums to guide roadmap decisions.
Media and entertainment
Track viewer reactions during live events to adjust content and advertising in the moment.

What our customers
are saying

Avahi surfaced a spike in negative sentiment minutes after a promotion glitch. We fixed the issue before it hit the evening news
quote 1

Lena Morales

VP Customer Experience, QuickCart

Key Result

95 percent average sentiment classification accuracy

3× faster issue resolution compared with manual monitoring

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How FreshBank reduced churn by 18 percent with sentiment-driven outreach

Challenge

Support call transcripts hinted at rising frustration, but the bank lacked a systematic way to quantify or act on it.

Solution

Avahi built a Comprehend pipeline that scores every call and social mention, then triggers personalised retention offers when sentiment drops below threshold.

Results

Early churn signals identified 30 days sooner

Customer churn decreased 18 percent in six months

Net Promoter Score improved by ten points

Frequently
Asked Questions

Which channels can we monitor?

We integrate social networks, review sites, call recordings, chat logs, surveys and any custom data source via API.

Can the model detect custom entities or jargon?

Yes. We train Comprehend custom classifiers and entity recognisers on your domain language.

How is pricing structured?

You pay for characters analysed and compute consumed. Most SMBs spend less than traditional social-listening tools while gaining deeper insight.

Ready to hear what your market is saying?

No credit card required. An AWS Solutions Architect will respond within one business day.
No credit card required. An AWS Solutions Architect will respond within one business day.

Download Solution Brief