How do we search for information in a data world?


The first thing we often do now when confronted with a question is to search.

We open a browser and go to Google and get going.

The proliferation of smart devices and AI assistants like Alexa and Siri will only intensify this approach – we can no longer hope to know everything because there is just too much out there.

This is well understood when it comes to marketing – experienced internet marketers know that they need to study search histories and trends and design content that addresses the way in which people search for content.

We are starting to see this in documentation and support pages for some companies, where instead of browsing through a list of topics we are encouraged instead to search or ask a question and the system tries to answer it or find relevant information.

It also has ramifications when it comes to training – the traditional classroom based approach to professional development can give employees an overview, but the individual challenges they face in their work are usually addressed through a search.

So, is it useful to have a simple model of the purposeful activity that people go through when searching?

Possibly – and that is what is shown in the picture above.

This is a representation of Marcia J. Bates’ 1989 berrypicking model of searching online.

In this model, the user might start with just one feature of a situation, to create a search query.

For example, this post started with the search query model of information search online in order to investigate current models out there.

That led to a paper which set out a number of models, from bibliographic or directory based approaches to linear models where the researcher moves systematically from a vague understanding to a focused one.

Looking at the variety of sources, the one that stood out, however, was Bates’ berrypicking model, because it matched how we do things now.

So that led to modifying the query to refine and gather more information on the berrypicking model, until a satisfactory completion point meant that the model could be expressed in the form of an human activity model, as in the picture and accompanying explanatory text.

So, why is having such a model in mind useful – and why is it any more useful than simply following a standard marketing approach of following a checklist and looking for Google keywords.

The key reason is that having the model in mind allows us to better organise the learning process associated with the creation and presentation of information online.

We can ask ourselves whether we have selected the key features that matter from the user’s perspective?

We can come up with search queries and match them against search engine data, especially around long tail searches.

We can also compare how our content matches up against other content from a variety of sources and come up with a plan to modify or improve what we are doing.

Finally, we have little control over when a user feels satisfied, but we can aim towards helping them move towards that point with well designed material.

Most organisations will find that they are in the middle of a transition to a user-centric, search based and information rich world.

Focusing on how users search will be essential for how businesses stay in business in this future.

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