Search Describes Solutions -- But What About Problems?

I previously said that Search User Interfaces (UI) have two jobs -- helping people find things, and educating them about the structure and contents of the data or catalog they're searching through. (I'll use "catalog" here under the assumption that I'm describing an e-commerce search system, but much of this post is relevant for other search domains.) The results, facets, and other features describe what exists in the catalog -- the solutions and products available.

But there's a third job that's often not addressed and not always well defined: helping users understand the structure of their problem, before they're ready to evaluate solutions. Standard search UI patterns aren't really designed for this. They assume that the user is already in the right mental state to evaluate what's on offer. The design challenge that I want to discuss, then, is to figure out how best to support education about problems in search interfaces.

In 1966, Eugene Schwartz published a now-canonical book about advertising. In it, he describes how buyers pass through a set of stages: unaware → problem-aware → solution-aware → product-aware → most-aware. This insight has driven generations of marketers' thoughts about how to meet potential customers where they are, providing the right information at the right time. (The stage names are clear, except for "most-aware", which refers to the stage of final evaluation before a purchase.)

Search systems and UI focus on the right half of this sequence. Potential customers at your shoe e-commerce store probably already have a sense of what they want or need, what general styles they tend to prefer, but perhaps they need to learn about the different models as they browse the site.

The left half of this sequence is traditionally delegated to various sorts of advertising and content marketing. Advertisement: "does your back hurt? maybe it's your shoes! http://shoes.com" helps consumers become aware of problems and potential solutions. Content marketing: a TikTok video about cushioning, arch support, and back pain lets consumers find language to describe their problem and potential solutions, getting them closer to product evaluation.

In my experience, and in general, there is a single user awareness journey, but the handoff between marketing and search system design is often not well considered or designed. Depending on the stakes, this may matter more or less. For low-stakes, simple purchases, users often arrive solution-aware, or even product-aware, and the gap is small. For higher-stakes, complex purchases (think a mattress, a car, injury-specific running shoes, B2B software), users may come to a website only problem-aware, or even unaware, and may need substantial orientation before they can reasonably evaluate alternatives.

This premature jump to solutions and products, before users fully scope and understand their problem, leads to particular ways that a business can struggle. Customers buy the wrong thing, are dissatisfied, might return it, and lose trust.

How can search systems and search UI design help? There are a few ways.

There is a substantial academic literature on how searchers' needs evolve during discovery (Bates, 1989 and Marchionini, 2006 are good starting points). Outside of academia, the influential e-commerce design organization Baymard Institute has a name for this at the query level: "symptom queries." When users search for "dry cough" or "stained rug," they're often disappointed by the search results. Modern semantic search can help somewhat, allowing products with descriptions like "removes stains from fabrics" to be retrieved, but the results and experience may still be non-optimal.

The underlying problem is that traditionally, taxonomies use the vocabulary of the manufacturer and cataloger: material, brand, size, color. They're not necessarily questions a shopper asks when they're at the problem-aware stage. One approach is to restructure the taxonomy, revealed through search filters and navigation, around problems to solve rather than properties of products. Problem-oriented facets might be "stays warm when wet" instead of "material: merino"; "good for sensitive skin" instead of "fragrance-free". Or occasion-based facets like "great gifts for teens." Just as facets help the user understand the structure of the solution and product space, they can also help the user understand more about the problem space, letting users recognize and name their problem as part of the search experience.

Other approaches that I've seen used effectively are guided search widgets (asking users where they are on the awareness journey) and embedded marketing content in search results. A widget with query-relevant marketing content, shown within or next to search results, lets users move left, towards problem and solution exploration, rather than forcing them right, towards specific products and the checkout funnel.

I think there's value in grounding these not-uncommon approaches in clear conceptual frameworks. Thinking about search's job in frameworks like Schwartz's, or the Christensen & Ulwick Jobs-to-be-Done approach, or even the information-science literature, can help ensure a strong handoff between marketing and on-site search.

The conceptual frameworks are clear, but actually implementing problem-oriented design raises practical questions.

Assigning problem-oriented facets at scale can be challenging, but less so now than in the past. First, understand how your potential customers think about and describe their problems and solutions -- the kind of insights that come from user research and marketing work. Then, you need to find a way to assign problem-based tags to every item. This second step used to require expensive human curation and maintenance, but machine-learning and AI-based labeling have drastically reduced the cost of this sort of operation. Any e-commerce site with a meaningful catalog and a good understanding of their customers' mental models should, at a minimum, evaluate problem-oriented facet labeling. The cost could be just pennies per SKU, and the benefits could be substantial.

Thinking about user journeys can also help teams select appropriate search metrics -- if users need to spend time gaining problem and solution awareness, then minimizing metrics such as "time to checkout" may actually be counterproductive.

Finally, it's worth noting that query text itself is an underused signal for a user's stage in the awareness journey. A user who types "best mattress for back pain" is thinking about problems and solutions, while one who types "Tempur-Pedic king" is thinking about products. This information can directionally drive personalized UI design. For users using problem vocabulary, include more editorial, links to content, orientation information, etc. For users using product vocabulary, surface and highlight filters and product comparison tools.

I don't think as many organizations do this as they should, or as well as they should. It's part of the handoff between marketing and search/product teams, and sometimes there is too much of a gap, so nobody thinks through the right approaches. Search teams are usually too focused on the words people are typing, and marketing teams are often just happy to get users onto the website at all. But there's real payoff for getting it right. Users who are supported through each step of the user awareness journey are much more likely to be happy with their purchase, which is what everybody wants.

Notes

• My thinking about this topic was inspired in part by a Venkatesh Rao blog post that goes much further in esoteric directions. Fun over-thought read. Search, Discovery, Pills, and Portals.
• This article was co-authored by AI systems. The initial ideas and direction were mine; the AI did extensive and very useful research as we discussed, I wrote the first draft by hand, and AI made additional suggestions. The diagram in particular should be credited to the AI, after much back-and-forth on the framework.
• Are you looking for support with search and discovery on your company's website? Does this post make you think I could help your company make great design or technology decisions? I'm a freelance consultant with extensive experience -- please reach out!