Search as a Multi-channel Experience

Mario’s grill rusted through and he’s ready to upgrade to a more durable one. He begins with a web search engine and clicks through to a store whose brand he likes. On that site he uses faceted search to refine to a handful of models whose attributes might meet his needs. He scrolls through the user reviews on those grills to see which ones other buyers trust, then prints out the reviews for the two he likes best. He checks local inventory online and finds a branch nearby that has both.

Mario uses his mobile phone to get directions to the store. Once there, he goes to the grill aisle and inspects them in person, reviews in hand. He discovers another model on clearance that he hadn’t noticed online. He looks up the model on a store kiosk, which is similar to the website, but has no user reviews. He turns to his mobile phone instead and reads user reviews. Now he has a top pick. He uses his mobile phone one last time to sanity check the in-store price against that of a web-only superstore. Feeling good, he drives home with a new grill.

This ethnography exemplifies an increasingly common multi-channel search experience. As people make purchases, they mix channels as they research and make purchases. In fact, in Profiling the Multichannel Consumer, Patti Freeman Evans of Forrester Research found that 70% of consumers research products online and then purchase offline. And in an earlier report from Forrester, Multichannel: In-Store Pickup Gains Importance, Brian Walker uses the estimate that the Web influences $397 billion per year of store sales, projected to grow to $1 trillion by 2012, or 1/3 of all retail sales. Freeman Evans broke down what constitutes online research. For example, 60% read customer reviews and 42% checked in-store availability before going to the store to buy.

Multi-channel no longer just means online and brick and mortar. Even web-only stores need to consider mobile and call center. And increasingly, people are accessing the web from new channels like their gaming console and connected TV. Each channel brings its own expectations to search.

If we were to repeat multi-channel search behavior ethnographies like this, we would eventually find a pattern: (1) People use multiple search features, across multiple modes of discovery. (2) People’s expectations of search features vary according to the context of the channel.

Modes of Search

One helpful model of search behavior places it on a continuum ranging from fact finding to discovery. And within that continuum, people use a variety of search features to support the different modes.

In fact finding, users know in advance what they’re looking for. For example, they already know the specific brand and model of grill they want. Some search features that might support fact finding include:

• Alpha-numeric string correction, which uses fuzzy matching so users can mistype a model name and still find it.
• Auto-phrasing, which detects when multi-word combinations are likely a compound, automatically boosting the relevancy of those results.
• Bar-code or QR code scanners, which use the camera of a mobile phone to directly retrieve product information.

At the other extreme of the continuum is discovery, where people don’t yet know what they want or how to describe it. For example, they know they want a more durable grill, but they don’t yet know the attributes that make a grill durable, or the brands they trust to build a reliable one. Some search features that support discovery include:

• Faceted search, which shows people the attributes associated with their results so they can browse and refine.
• User review search, which lets people read the frank feedback of other consumers, and possibly exposes the attributes of the reviewers through faceted search.
• Buying guide, product info sheet, and demo video search, which incorporate features of document search like text mining and advanced relevancy to show supplemental information alongside results from the product catalog.

Context of Channel

People’s expectations of search features vary according to the context of the channel. For example, they expect mobile to be location-aware, and in-store kiosks to be inventory-aware. They expect online to optimized for a big screen, and mobile for a small one. And they also expect the store to know which channel they used; for example, the call center should be prepared with different return information for an online shopper than a brick-and-mortar one.

Although the multi-channel search experience is already common, it is still not a well-designed experience. It’s a kluge. People face unnecessary gaps across channels, often because the channels aren’t aware of each other. For example, Mario couldn’t pass his shopping cart from his online search to his mobile, which would have let him bring user reviews to the store without printing them out. And the in-store kiosk Mario used didn’t include user reviews at all because it was managed by a brick-and-mortar team with little connection to the online store.

There’s a reason the experience is still poor. Retailers still aren’t organized to make multi-channel work. Different groups typically own the different channels, and they have no incentive, or even counter-incentives to cooperate. Even when groups do try to coordinate across channels, they still have difficulty knowing when a shopper crosses from one channel to the next, or even measuring how the channels affect each other. For example, Brian Walker found that “only 13% of Web managers at multichannel retailers view driving sales to their brick-and-mortar stores as a top priority.”

As an experience design discipline, multi-channel search is still in its infancy, and investment in it lags actual user behavior. That means there are still no best practices. However, there are early adopters whose experimentations might point the way towards the future.

• Home Depot: Given the nature of the home improvement business, they were one of the first to recognize that their shoppers were frequently researching online and buying in-store. As a reaction, they added extensive sets of how-to guides and product info sheets, and were one of the first to let people search online for local, in-store inventories.
• Borders: They have a strong loyalty program that carries across channels. Their email promotions are coordinated with their online search, so an offer in a promotional email clicks through seamlessly to their website. And their in-store kiosks are also closely tied to their online channel, so users can pass information from their home shopping cart to the store.
• B&H Photo Video: With a loyal audience comprised of professionals, B&H was one of the first to launch a smart phone app that helped buyers working in the field order replacement supplies or research emergency substitutes. Their merchandisers manage this with the same tools as their online channel, helping to coordinate the two.

Multi-channel search experience design is still in its early stages, but we already have a good idea of how to go about it. The key is to understand the context each channel sets for what a user expects of its search features. And stores need to understand how its customers transition from one channel to the next, and design search that helps them complete their tasks even as they switch channels.

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