A collection of Collective Intellect videos that review best practices, tips and our social and text analytics technology. Scan for:

• Ever Used Semantic Technology to Conduct a Search? Now’s Your Chance. Using Semantic Technology to Analyze Social Media Conversations
• A Better Way to Use Sentiment. How to use sentiment analysis when monitoring social media conversations
• Real-Time and Trending Analysis Helps Create a 360-view of your Customer
• What’s the Sentiment Driving Your Consumer’s Intentions
• Knowing When Your Social Customer Is in the Mood to Buy
• What the Social Customer has to say about Insurance Pricing, Customer Service and Ads
• Does the Conversation Change from One Social Media Platform to Another?
• What the Social Customers are Saying About Credit Card Companies
• The Viewing Habits of the Social Customer
• Top 3 Social Media Indicators for Social Intelligence
• Think Your Customers May Be Leaving for a Better Offer? Use Social Media Analytics to Identify Customers Intent to Switch Services
• Using Social Media Analytics to Identify Customers Concerned with Pricing

Ever Used Semantic Technology to Conduct a Search? Now’s Your Chance. Using Semantic Technology to Analyze Social Media Conversations

Try out a scaled-down version of our semantic technology to quickly view 1000s of social media conversation clustered into themes.

How to use sentiment analysis when monitoring social media conversations

This video describes the importance of setting context before applying a sentiment filter. You’ll get a lot more out of your analysis if you define why you are interested in whether a consumer likes you than simply raking up the “likes”.

Real-Time and Trending Analysis Helps Create a 360-view of your Customer

Building a 360 view of your customer requires not only real-time analysis of consumer preferences and opinions but how that information trends over time. Understanding the needs of your consumer will help extend and enhance the life cycle value of your customers.

What’s the Sentiment Driving Your Consumer’s Intentions

Using text mining and analytics to surface consumer expression of intent and consideration then using sentiment to filter for actionable insights.

Knowing When Your Social Customer Is in the Mood to Buy

Surfacing purchase intent from social media conversations. Using semantic technology to organize and filter text for specific content themes related to purchasing.

What the Social Customer has to say about Insurance Pricing, Customer Service and Ads

A look at social media conversations around insurance companies: Allstate, Geico, Progressive, and State Farm. Do people really like the Gecko more?

Does the Conversation Change from One Social Media Platform to Another?

Surfacing social media insights by social media platform for the show Beyond Scared Straight.

What the Social Customers are Saying About Credit Card Companies

You know they are saying a lot but what they are saying may surprise you. Using social media analytics to surface consumer insights on credit card companies, including demographics, sentiment and their true opinion on customer service and fees.

The Viewing Habits of the Social Customer

Understanding and comparing TV audience habits and perceptions using social media analytics.

Top 3 Social Media Indicators for Social Intelligence

I spoke with some of our social media market researchers at Collective Intellect and they recommended three areas to monitor for social intelligence.

Think Your Customers May Be Leaving for a Better Offer? Use Social Media Analytics to Identify Customers Intent to Switch Services

Using social media analysis we are able to identify customers intending to switch services in this mock case study. CI’s semantic technology can be used to surface customer complaints and target those with an intent to switch services, including your competitor’s customers who are considering switching services.

Using Social Media Analytics to Identify Customers Concerned with Pricing

We created a mock case study using an apparel company concerned about market perception around the pricing of their clothing. Using keywords and latent semantic technology we clustered customer conversation around pricing. This type of analysis can be used to validate offline rumors and discussions.