Speeding up search: Google Instant

Towards the end of last week I learned about the launch of Google Instant, which aims to speed up the search process by providing suggested search terms as soon as the user starts typing in a search query. For instance, I started typing in “br” and the search bar started showing 4 results varying from “british airways” to “britains got talent”.

With this new, dynamic way of generating results, Google claim that typical researchers will save 2 to 5 seconds on every search query. With Instant, Google clearly tries to differentiate itself from competitive search engines such as Bing and Yahoo! who offer ‘search before you type’ functionality. The main things I learned with regard to Google Instant:

  1. Dynamic results – Relevant search results are generated whilst the user is typing in a query.
  2. Predictions – Google Instant predicts the rest of a search query even before the user has finished typing.
  3. Scroll through predictions – The user can scroll through the predictions (see learning point 2.) and see the results for each prediction when scrolling down.
  4. It’s aggressive! – I can imagine that Google Instant might not be for everyone, especially if you rather not have suggestions presented to you that are completely irrelevant to what you’re looking for!

What does Google Instant add to the existing search engines out there? The main value added in the speed with which search results are generated and the ability to modify search results. I guess Google Instant will be particularly appealing to people who search very frequently e.g. researchers. For Google it will be another product that can help to differentiate itself from its competitors.

Main learning point: a distinction can be made between “searching before you type” versus “searching as you type”. This ability to generate instant, dynamic results will help to speed up and simplify searches.

Related links for further learning:



Social media monitoring – brands want to know what’s going on

I’m learning about social media monitoring and it’s amazing to see how many different monitoring tools have sprung up over the last couple of years. Most tools out there seem to focus on “listening” or “filtering the noise.” What does this mean?

People use social channels like Facebook, Twitter or LinkedIn to talk and share whatever is on their minds. Brands have started using monitoring tools like Radian6 and Brandwatch to ‘listen in’ on the things people are saying online about their brands or products. Businesses can thus start monitoring real-time conversations and can then decide to act accordingly. From the case studies I’ve looked at, I feel that these seem to be common ways that organisations harness the feedback and insights generated through social media monitoring:

  1. To actively engage with customers – Identify who your key “influencers” or “brand advocates” are.
  2. Online reputation management – Pick up on conversations which could be damaging to your brand or product.
  3. To filter and segment online conversations – Using “keyword” or “sentiment” filters to segment and group conversations or comment into meaningful categories.

A simple argument in favour of adopting social media monitoring is that conversations about brands and products are happening anyway. Quick searches on Twitter monitoring tools like Twitterfall and Tweetdeck showve, by monitoring these comments, brands can at least respond or engage with customers to address or resolve their issues.

Like with traditional marketing research, online monitoring can be used to generate valuable market and customer insights. A good example is a recent monitoring exercise by Amazon Kindle to find out whether the introduction of Apple’s iPad had altered consumer perception of the Kindle. The exercise, using Brandwatch, generated insights around e.g. pricing and consumers‘ strong desires for a Kindle touchscreen.

Main learning point: businesses can monitor and analyze our conversations online. There’s a range of tools out there that help brands to keep track and make sense of things being said about their products or services. Subsequent action can vary from customer engagement to product innovation.

Related links for further learning:






It’s all about sharing: research collaboration tools

Wikipedia defines “collaboration” as a “recursive process where two or more people or work together in an intersection of common goals”. This morning I learned about “online research collaboration tools.” These tools are all about making life easier for academics by enabling them to share research papers and to collaborate on research projects. I always associated academics with serious and determined people spending a lot of time in dusty libraries browsing through medieval journals or searching in complicated databases, looking for that one invaluable citation.

However, tools like Mendeley and Google Scholar help students and academics alike to easily access a wealth of articles, notes and citations. Thomson Reuters’ Web of Knowledge provides access to more than 40m research papers for users to explore. Some key features that most online research collaboration tools seem to have in common:

  1. Organise research libraries in secure collaboration spaces to share with others.
  2. Access to a wide range of papers, notes and citations.
  3. Ability to customise personal research libraries using tagging and smart filters.
  4. Sharing of “virtual sticky notes” with other researchers.
  5. Network with fellow researchers, finding the experts in your area of interest.

Overall, I guess the social element is what makes these research collaboration tools stand out from their more static predecessors. Users can now easily create a network of fellow researchers they want to share their research data with. However, pioneers like Mendeley’s Victor Henning and Neil Saunders are quick point to out that these tools are not about creating another social network but are about “making the data social.”

Main learning point: Online research collaboration tools will open up academia and help researchers and students to easily share knowledge and collaborate on research projects.

Related links for further learning: