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Internet trends: marketing research & predictions

Eight Insightful Twitter Search Queries

June 29th, 2010 by

Social media conversations can reflect peoples’ attitudes, needs, desires and intentions. The challenge is to listen wisely and use market research skills to “ask” the right questions.

When you wish to follow perceptions and intents keep in mind that you will need to follow day to day jargon, and that the conversations traced are typical to the specific social network you are searching at.

Currently, I find that there is no tool as Twitter to extract such knowledge and map real time reflection of peoples minds.

While conducting many social media research projects, I have collected some insightful search queries, useful for marketers and to those who wish to keep track on perceptions and shared interests.

I have divided eight social media queries to the following three categories:

1. Needs and desires

2. Attitudes toward brands

3. Buying intentions

Most of the examples presented here are global, but as you can now search Twitter conversations within specific locations (you can simply choose distance from a desired location and trace locations by coordinates), some of the conversations were generated in the New York area and by that reflect a specific demographic community.

Twitter_search_trends_New_York

I. Needs and desires:

Social media allows consumers to openly share and discuss their needs and desires. Put in real time context, we get natural expressions and spontaneous reactions. Brands should follow not only the conversations evolving around them, but come to understand general needs:

1. Follow these spontaneous expressions: “Must” and “Need”  –

1.1 “I must get a new..” (global):

twitter_search_intentions

1.2.  “I need to get..” (New York)

twitter_search_needs

1.3. “I must buy” (global)

must_buy_twitter_search_trends

2. Wish expressions indicate desires, which sometimes can no be fulfilled. Nevertheless, they carry strong emotional character:

2.1 “I wish I had” (New York)

twitter_search_trends_desire

2.2. “I wish I could buy” (global)

twitter_search_trends_desires

3.  As brands are trying to provide solutions to needs – why not use Twitter to follow “real time”  direct help request?

3.1  “I need help” (global)

needs_twitter_search_trends_help

3.2 “I need help” (New York)

twitter_search_needs_help

II. Attitudes toward brands:

In search for what makes brands likable, lets follow  direct “love” and “hate” emotions.

4. “I love brands..” (global)

I love brands twitter search

5. “I hate brands..” (global)

twitter_search_brands_attitudes_hate

6. “I hate ..service” (global)

twitter_search_services_attitudes_hate

III. Buying intentions:

Open Social Media conversations can provide you not only with desires but also with real buying intentions, those can serve as behavioral indications:

7.” I plan to buy” (global)

twitter_search_buying_intention

8. “I will definitely buy” (global)

twitter_search_buy_intentions

Read more: Twitter’s “must buy” shopping list.

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56 Responses

  1. whatsnext (BL Ochman) Says:

    Twitter Comment


    An extraordinary post from Trendspotting about Twitter search & brands. Brilliant! [link to post]

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  2. KevinMinott (KevinMinott) Says:

    Twitter Comment


    RT @jaycbee: Eight Insightful Twitter Search Queries [link to post]

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  3. jaycbee (Jazz Baker) Says:

    Twitter Comment


    Eight Insightful Twitter Search Queries [link to post]

    Posted using Chat Catcher

  4. FireHydrantCS (FireHydrant Creative) Says:

    Twitter Comment


    Useful Twitter searches? [link to post]

    Posted using Chat Catcher

  5. JackieTEwing (Jackie Thorpe Ewing) Says:

    Twitter Comment


    Eight Insightful Twitter Search Queries. [link to post] – this is a great read for Twitter newbies or anyone looking to try new ideas.

    Posted using Chat Catcher

  6. BluerockDesigns (BLUEROCK Designs) Says:

    Twitter Comment


    8 Insightful Twitter Search Queries [link to post] (RT @TrendsSpotting) #socialmedia #twitter #in

    Posted using Chat Catcher

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