This article is one in a series on designing the search experience.
This article is one in a series on designing the search experience.
The 1981 edition of the Guinness Book of World Records carried an entry of the “shortest literary correspondence on record”:
The shortest literary correspondence on record was that between Victor Marie Hugo (l802-85) and his publisher, Hurst and Blackett, in 1862. The author was on holiday and anxious to know how his new novel Les Misérables was selling. He wrote “?”. The reply was ‘!’.
There is doubt as to whether the story is actually true, but if it ever did happen, it is a good example of context at play. Only those two people knew what was going on. Context in this case, is all of the unsaid that influenced all of the said.
Context is the information one brings to bear when understanding a situation. When it is missing or wrong, we say that the understanding is “out of context”. But when it is present, everything speeds up, becomes simpler and even enjoyable, like the claimed correspondence between Victor Hugo and his publisher.
Bringing context to search, we can say that context offers the situational signals we can use to design rich search experiences.
Let’s consider three search scenarios:
- A bank customer having problems withdrawing money when overseas
- An employee enquiring about paid paternity leave
- A new employee looking for minutes of meeting template
A bank customer having problems withdrawing money when overseas
The situation: A bank customer travels overseas on a business trip. He goes to an ATM but can’t seem to withdraw cash. He goes to the bank’s website and enters “cant withdraw money from ATM” into the search box.
The challenge: How might we lower the customer’s anxiety and help resolve the matter quickly?
Available contextual signals: We know that the customer is overseas (location). Also, because the customer is using a mobile device, we can gather the time of the day (time) and his GPS coordinates (location).
For starters, if we have a page about the problems withdrawing money from ‘overseas ATMs’, we should boost the relevancy factor of this page against the query. Next, if we have a list of bank branches, then we can offer the customers a path to resolve the issue by visiting the nearest branch. We can use the ‘time’ information first to check if the branch office is open or not.
An employee enquiring about paid paternity leave
The situation: It is happy times for this employee. His wife is due to deliver in a few months, and he wants to plan his paternity leave. He types in “paid paternity leave” into the search box.
The challenge: How might we help this employee quickly understand and apply for his paternity leave (he has a lot on his mind already)?
Available contextual signals: We know the ID of the person as he is logged into the intranet. We also know his rank and his entitlements.
The beauty of search in the enterprise is that you can leverage a lot of context. You can access HR, financial, sales and marketing systems and bring all of this data to bear on improving search relevancy. For the query on paternity leave, you can directly access the eligibility and entitlements to offer a simple answer like the one shown below.
A new employee looking for minutes of meeting template
The situation: A new employee has joined the project team. Eager to be useful and helpful she wants to attend a few meetings and offers to take notes. She types in ‘minutes of meeting template’ into the search box.
The challenge: How might we help this employee to learn the ropes faster and not make her feel overwhelmed with a chaotic information environment?
Available contextual signals: Similar to the paternity leave scenario we know something about this employee. We know that she is new. We also know she belongs to a particular project team. We can bring this and other details to bear on the search results and offer more relevant information, as shown below.
So we've established that contextual signals are useful for search. But how many types are there and how do we go about thinking about them?
Cennydd Bowles, a digital product designer who previously worked with Twitter, offers a list of contextual signals he calls DETAILS:
- Device: Using the native contextual signals that the device offers (e.g., it can take pictures)
- Environment: Using the signals in the environment (e.g., quiet or noisy)
- Time: Using temporal signals (e.g., time of a meeting)
- Activity: Using signals from a task (e.g., when creating a policy report)
- Individual: Using personal signals (e.g., the type of work)
- Location: Using signals of space and time (e.g., office locations)
- Social: Using social signals (e.g., popular items)
These seven types of contextual signals cover most cases and can be used when designing search experiences.
General relevancy, personalisation and recommendations
The three scenarios we covered earlier are actually three different ways to use contextual information:
|Scenario||Type of use|
|A bank customer having problems withdrawing money when overseas.||Improve general relevancy|
|An employee enquiring about paid paternity leave.||Offer personalised results|
|A new employee looking for minutes of meeting template.||Recommend relevant information|
Improve general relevancy
You can use contextual signals to boost specific relevancy parameters. The common signals are device, time and location. Improving general relevancy is easy to include and implement.
Offer personalised results
You can use the properties of the searcher to offer targeted search results (individual and social signals). Getting personalised results means tapping into personal data, usually locked away in dedicated systems. Thus, you may be looking at some level of system integration to get personalisation going.
Recommend relevant information
Recommendations go far beyond the simple type shown in the scenario. They can scale to the ones offered by Amazon, Netflix and Pandora. The recommender systems powering such sites use all sorts of contextual signals and their weights along with sophisticated mathematics to provide relevant recommendations. But the good news is that not all situations call for such powerhouse treatment. We can start with simple, but useful, recommendations.
Push vs. Pull
The trigger to all the three scenarios was the entering of a query. This is called a 'pull' action. But you can also automatically suggest results to users. This action is known as a 'push' action.
For example, in the screenshot below, Google Now knows that I have a flight to catch from Washington DC to Singapore via Dubai. It checks with relevant sources and finds that the flight is delayed. It then promptly alerts me about the delay. Google Now tries to predict queries based on what it knows about my context. Such recommendations can be cool or can scare the hell out of you at times (how did Google know?).
Designing contextual search scenarios
We have covered a lot of ground on what context is and how it can be used. We can map all of it on a 'search context canvas'. This canvas can help you think strategically about using context to improve search experiences.
Here’s how you fill out the canvas:
- Situation: Identify the situation you want to address. It could be something that users are complaining about or something you think can be improved.
- Challenge: Frame the challenge so that it addresses the situation.
- Why address it: Think through the user and business savings if this need is met. Your justification may help you get extra funds and resources when required.
- Contextual signals: Identify the contextual signals you can leverage to solve the problem. It could be one or multiple signals.
- Tactics: Think through the tactics you want to use. Are you going to use general relevancy or personalisation or recommendations or a combination of all three? Are going to use the push or pull approach? Then, what is required to make all this work? What changes must be put in place?
- Sketch: Finally, sketch out the interface that you expect to see. Don’t restrict yourself to a single sketch; try out many options.
It is important to remember that in terms of sequence, thinking about context happens along with understanding users and content. Studying users, content and context ensures that you start right. Interfaces and technologies can then bring the search experiences to life.
Context dramatically improves the search experience. It raises productivity and is enjoyable to consume when done right. With so much going for it, why haven’t organisations included context in their designs? The answer, which applies to much of enterprise search, is that organisations assume that context is automatic and all they have to do is to buy the right 'box'. Hopefully, this article has convinced you that this is not the case, and has instead inspired you to look for an opportunity to include context in your design.