AI Analytics

The backbone of everything Sift does is built on the intelligence we add on top of the unstructured conversations across your social ecosystem and community. That's how we decide what needs action, what's useful information, and what can be filtered out.

Within the Analytics section, you're able to dig deeper to understand the topics people are discussing, emerging trends, sentiment shifts, and the effectiveness of your support team.

On the first tab (AI Analytics), you'll see different ways to understand the content of interactions on the Sift platform.

This is organized by:

  • Taxonomy

  • Taxonomy Trends

  • Tag Insights

  • Relevancy

  • Moderation

Taxonomy

Taxonomy allows you to understand the topics and themes being discussed across your social channels through an AI-generated hierarchy of categories that you can drill into for more detail.

Sift provides sentiment analysis, mention counts, and response rates for each topic, with a trend chart showing how the top themes shift over time.

Click on a topic to see the conversations and records that belong to it.

Taxonomy Trends lets you track how topics and themes shift over time across your social channels, helping you spot emerging conversations, seasonal patterns, and sudden spikes in customer interest.

The trend chart shows the volume of the top themes over your selected period, with each topic plotted as a separate line so you can compare momentum at a glance.

The topics table includes a 7-day delta column showing whether each topic is trending up, down, or holding steady compared to the previous week.

Along the top you are able to select filtering by time period and sources.

Tag Insights

Tag Insights lets you analyze the tags applied across your conversations and understand the sentiment patterns within each tag.

Three metric cards summarize your data at a glance: Total Tags, Total Tag Groups, and Total Mentions across all tags.

The chart view shows Sentiment Over Time and Sentiment by Topic, so you can see how customer sentiment shifts day by day and how it varies across different tags.

Click any tag in the chart to drill into the records associated with it. Switch to Table View in the top right corner to see individual records in detail.

Relevancy

Sift uses AI to analyze each message and evaluate it for relevance to your brand and whether it requires action. These evaluations help triage interactions for your support team, typically filtering out non-relevant and non-actionable items before they enter a support queue.

Four metric cards summarize the impact: Total Items processed, Irrelevant Items, Non-Actionable Items, and Hours Saved by automatically filtering out noise.

The chart view shows Relevance and Actionability trends over time with percentage change indicators, alongside breakdown charts showing the overall split between relevant vs. irrelevant and actionable vs. non-actionable items.To help understand trends around individual topics, Sift provides a "Conversation Topics" page which shows high-level groupings of individual topics. Next to each topic is shown how many interactions related to the topic have occured in the selected timeframe (selectable from the top of the page) and change in volume.

Moderation

Sift automatically detects and handles spam across your social channels using a combination of AI detection, pattern matching, and custom rules. The Moderation tab lets you track how effectively these rules are protecting your community.

Four metric cards summarize activity: Total Spam Caught, Caught Today, Average Confidence score, and an Action Breakdown showing how many items were suppressed, auto-closed, or tagged for review.

The chart view shows Spam Volume Over Time, a Rule Type Breakdown (AI Spam, Stock Spam, Pattern Match, Regex), Top Spammers ranked by detection count, and Top Channels where spam is most prevalent.

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