Overcoming the Problem of Online Product Search
Are you ready to hear an uncomfortable truth? Today’s e-commerce search mechanisms are still firmly based on technical concepts developed over 20 years ago. They often leave consumers frustrated and unengaged, resulting in churn or missed sales opportunities.
Facets and search bars are static mechanisms that reflect a technical search engine perspective. Recent personalization technology based on machine learning algorithms are trying to bridge the gap for e-commerce retailers to predict what consumers want. However, this simply perpetuates the technology-driven user experience that leaves little room for discovery and, at best, only produces incremental gains one percentage point at a time.
The human is expected to adjust to the needs of the machine, leaving no room for iteration, for fuzzy human thinking, for the concept of feedback.
It’s time e-commerce retailers embraced change like they did 20 years ago and rethink their approach to how consumers search for products on their websites.
The Problem With a Technology-Led Search Experience
When technology leads the search experience, retailers and consumers alike lose the human touch, and this is to our collective detriment.
For e-commerce retailers to achieve an uplift through personalization, they rely on large amounts of site-specific data (third/second/first-party data) to train machine learning algorithms. This process can take weeks if not months. With tighter data protection legislation and an increasing reluctance from consumers to hand over their personal details, these machine learning algorithms are being starved of the required data, which in turn reduces their ability to achieve a significant amount of uplift.
We need to take personalization to its logical next phase, where we escape its technology-led foundations and it becomes truly consumer-driven. Shifting the focus to understanding rather than guessing consumer intent provides a richer and more engaged experience, benefiting both the consumer and the retailer.
Becoming Truly Customer Centric Using Zero-Party Data
The good news is that the route to arriving at the next phase of e-commerce personalization isn't as radical as you may think.
We need to stop viewing e-commerce search through a technology-led, filter-based framework. Instead, we should embrace consumer engagement and interactivity and give the consumer mechanisms that encourage them to specify what they want as they progress through their journey. So simple, yet so revolutionary!
This provides highly valuable insight into their commercial intent, which allows accurate personalization using zero-party (“volunteered intent”) data. Contrast that with trying to guess their intent from third-, second- or even first-party data.
A New Approach to Solving an Old Problem
An important second step is that we must free ourselves from the constraints of 20-year-old technology thinking and adopt a more human approach.
Consumers think in terms of goals, not database queries. Once we've established consumers’ preferences, it makes sense to order products accordingly, rather than filter them.
This removes their fear of overfiltering and enables not-quite-right products to stimulate further feedback of preferences.
A more humanized search and discovery process accommodates how consumers think. It develops trust, drives loyalty, and leads to a win-win for all parties involved.
If we can transition search technology to take an interactive, iterative, engaged and communicative approach, e-commerce providers will be able to better understand consumer intent and provide a richer and more tailored experience for consumers.
We need to remember that people are at the heart of all of this. Yes, we have the technology to deliver various algorithms to help with online shopping experiences, but without the interaction, engagement and human touch, we simply cannot cannot begin to guess at what the consumer really wants. It's time to engage them and know.
Twan Vollebregt is the CEO and founder of Traverz, a provider of e-commerce personalization technology.