How I Learned to Stop Worrying and Love the Search Bar

Leveraging A.I. for Online Search and Discovery

Search bars suck (probably yours too)

We are stuck with technology when what we really want is just stuff that works.” D. Adams

The current state of onsite search in digital retail is somewhat depressing.

80% of companies don’t optimize their search even though 30% of total revenues come through the search bar.

We touched on how bad search can be in our previous post (the TL;DR version of our critique is just searching for shelves online). While the market of SaaS solutions is becoming pretty crowded, our main contention with current (from-decent-to-nice) solutions is that they got the challenge all wrong: it’s 2017 and search should be an A.I. problem.

In fact, A.I. can give your customers a much more rewarding experience than “just” search: at Tooso, we call it search and discovery.

One search technology to rule them all

When discussing onsite search shortcomings, there are obvious and not-so-obvious use cases that need fixing.

The first that always comes to mind is getting customers that know what they want to buy from you. If I search for ‘blue cotton blazer’ I should get first blazers of a specific color (blue) and made of a specific material (cotton): this is what you get in fact on the high-end Italian fashion store Canali, but it’s easy to check that things get pretty confusing on many eShops (hint: Canali is using Tooso).

A second one — which will be the main topic of this post — is quite the opposite: how can we drive the conversion of users whose intentions are somewhat left unspecified? When a customer lands on your website and types a generic query like ‘jacket’, she may not know what to buy yet and/or she may not know what’s in store. In the real world, these two factors are often intertwined: the final buying decision is the result of preferences/desires given the total space of possible choices.

For this second use case, the challenge for the merchant is to help the buyer navigate this (possibly giant) space without frustrating her (“F%$ this, I’ll just go on Amazon”).

Is there a tech that solves both problems?

From search to discovery: some options

“To boldly go where no man has gone before.” J. T. Kirk

Let’s put the scenario in context. The following is an imaginary shop where the customer lands and types a simple, generic query, like ‘suits’:

Tooso test interface showing items from Canali digital store.

What are the options to engage with this customer? Let’s start with three potential solutions and why they won’t really work:

  • Old school UX, that is filters, sliders, checkboxes somewhere on the page. PRO: easy to implement and very Nineties: we love the Nineties. CONS: clumsy on mobile (which already accounts for ~20% of total revenues), no adaptive behavior.
  • Chat bots, that is chat-like interfaces overlaying the eShop main window. PRO: a dialogue is the most natural form of shopping experience as it mimics what happens in the physical world. CONS: while still clumsy on mobile, the main issue is that “it’s a little too human a little too soon”. A conversational interface encourages distracting questions, and technology is just not there yet to keep you entertained: I personally cannot resist asking ‘is P = NP?’ any time I find a bot, and the magic is immediately lost.
  • Visual search, that is visual interfaces allowing you to upload a picture (or pick a product) and find similar items visually (such as the snap feature in Snap). PRO: intuitive and rewarding when narrowing down items based on style. CONS: it still needs a search tool and possibly other UI elements to effectively guide the user in a catalogue.

Unhappy with the available options on the menu, our customers ultimately turned to the search experts (yes, that’s us) for some new ideas; since there is only one piece of HTML we control — the search bar — we transformed that constraint into a (patent pending!) virtue.


Back to the future (of the search bar)

Prediction is very hard, especially about the future.” Y. Berra

Technologically, we built Tooso “back-end first”: it was always our plan to build a SaaS product and all SaaS products start from APIs. However, philosophically we built Tooso starting from a “front-end dream”, i.e. give people an awesome search experience leveraging the latest A.I. and machine learning tools.

In particular, we always loved the idea of using the search bar as our one-click tool to fulfill our needs; with Tooso you can now use it also to refine your shopping journey.

For example (using the ‘suits’ scenario introduced above), the bar can overlay a small message asking you to specify a property that we believe will help you:

Tooso test interface showing the discovery process to refine search queries.

As you click again on the search bar and refine your query with a color (say, ‘blue suits’), a different suggestion may pop up (e.g. ‘how much would like to spend?’).

Tooso search bar knows how to best guide the customer’s journey.

How is that an improvement over other discovery processes?

  • It’s mobile friendly: as most eShops have already chosen a full width search bar in their app, nothing to be changed there!
  • It’s engaging, but focused: no interface or conversational distraction, as the customer is still fully in the context of the search bar.
  • It’s smart and adaptable: thanks to our superior A.I. technology, we can understand both the user’s intention and the underlying catalogue to always suggest the refinement most likely to drive the final conversion.

Our search and discovery feature is now in Private Beta and will be rolled out to our customers soon, in text and text + voice versions (featuring support for speech-to-text and text-to-speech technology).

See you, space cowboys

If you want to join the A.I. revolution in online shopping, sign up to reserve a spot in our early adopter program and don’t forget to follow us on Linkedin, Twitter and Instagram.

We would love to hear your thoughts on search and discovery, so feel free to reach out directly to jacopo.tagliabue@tooso.ai.

Acknowledgments

Many thanks to Maria Paola Sforza Fogliani and Katherine Yoshida for sharing with us their linguistic and fashion wisdom.