Every year, consumer expectations for on-site product discovery experiences grow higher. How do you know if your product discovery experience can compete?
In this article, we’ll cover 8 essential questions to ask when testing your product discovery experience, starting with functionality:
Functionality
Giving your users an immersive search experience is critical for performance, improving conversion rates, and ultimately increasing revenue. To ensure your user’s journey is fluid and intuitive, consider the following questions:
How fast is your search?
10 years ago, Amazon found that every 100ms of latency cost them 1% in sales. Google found an extra .5 seconds in search page generation time dropped traffic by 20%. Ensuring high speeds on your website is one of the first steps towards achieving a desirable retention rate.
How are products ranked on your site?
By far, the best product ranking signals come directly from users — what products they click on, add to cart, purchase, and more. Moreover, by ranking search results based on what products are most likely to lead to an increase in business KPIs, you can achieve attractive results. Manually ranking products across your entire product discovery experience on this basis is extremely difficult, if not impossible.
We’ve written extensively on this topic in the past – you can read more about this topic here.
Do your search & autosuggest systems use typo-tolerance, plurals, and NLP to help your users find what they’re looking for?
By correcting phonetic, fat finger and spacing errors automatically, you can ensure users don’t end up on zero-result pages that may cause them to leave. Moreover, NLP that infers user intent enables accurate search results and increases purchase rates, making NLP an important contributor to successful searches. Inferring intent is simply not a feature of traditional search engines.
Do your users get personalized search results based on their preferences, behavior, etc.?
According to Boston Consulting Group, “companies that use advanced personalization methods can realize an improvement of 20% or more in their net promoter scores. In addition, these retailers can see productivity gains of 6% to 10% and incremental revenue growth of 10% or more.” Great personalization allows you to improve the experience on your site for every individual down to minute details (like affinities towards organic foods for grocery retailers, or golf pants for apparel retailers) across your entire site — not just by showing different results based on basic demographic data.
You can read more of our articles on personalization here.
Optimization
User expectations for search and product discovery experiences are constantly on the rise. To ensure your product discovery experiences are meeting user expectations, consider building or improving the following questions:
How often does your search and discovery system have outages?
The greater your uptime, the less revenue you’ll lose. Users are impatient. If they reach your site and aren’t able to access it, they’ll almost certainly leave (and with a bad taste in their mouth).
At Constructor, we aim to have at least a 99.999% uptime across all our services.
What are you optimizing your search results for?
By optimizing your search for relevance in tandem with an important business KPI, you are able to generate search results that benefit both you and your users. Without this ability, your search results won’t benefit anyone. Optimizing for relevance should prevent something like ‘shoes’ showing up for a search for ‘laptop,’ and optimizing for business KPIs should ensure that the most attractive laptops (the ones most likely to lead to an increase in your business KPIs) should show up at the top.
You can read more about this topic here.
Does clickstream data fit into your ranking strategy?
How much do your product discovery channels (ex. recommendations, browse, search) learn and share data with each other?
Connection between product discovery channels is the backbone of any advanced system (ex. ML-reranking). Without it, useful data (like purchasing habits and affinities) is lost and cannot be used to improve user experiences in other areas of your product discovery experience. The more data you have, the better experience your users receive.